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DoD 2019.A STTR Solicitation
NOTE: The Solicitations and topics listed on this site are copies from the various SBIR agency solicitations and are not necessarily the latest and most up-to-date. For this reason, you should use the agency link listed below which will take you directly to the appropriate agency server where you can read the official version of this solicitation and download the appropriate forms and rules.
The official link for this solicitation is: https://www.acq.osd.mil/osbp/sbir/solicitations/index.shtml
Application Due Date:
Available Funding Topics
TECHNOLOGY AREA(S): Human Systems
OBJECTIVE: Develop and evaluate controls, displays, and/or decision aids that help maintain human-machine shared situation awareness during distributed operations conducted with manned and unmanned vehicles under possibly contested and degraded conditions.
DESCRIPTION: The importance of autonomy for realizing Air Force employment of multiple manned and unmanned teamed sensor platforms in future warfighting is well recognized. These new mixed-initiative interactive systems must enable human-machine collaboration and combat teaming that pairs a human’s pattern recognition and judgement capabilities with recent machine advances in artificial intelligence and autonomy to facilitate synchronized tactical operations using heterogeneous manned and unmanned systems. Agility in tactical decision-making, mission management, and control is also a requirement given anticipated complex, ambiguous, and time-challenging warfare conditions. For example, shifts from a centralized to a decentralized control structure, especially when communication links between the human and machine team members degrades, is plausible given unmanned vehicles will have onboard computational resources to flexibly serve as autonomous and capable teammates that can complete needed tasks. The envisioned distributed and networked operations will complicate human-machine coordination, especially when communications are intermittent, degraded, and/or delayed. This is in addition to the challenges of achieving multi-domain situational awareness/command and control. Current control station interface designs do not support information sharing and coordination to synchronize human-machine awareness whenever communications are restored. Improvements are necessary to realize effective human-machine teaming performance in mission operations, especially when alternating between centralized and decentralized control modes. Controls, displays, and decision support services are needed for the human operator to efficiently retrieve integrated contextual data that helps rapid restoration and maintenance of a shared understanding of relevant information that supports human-machine joint problem-solving, effective decision making, and ultimate task/workload balancing. This will require agent-assisted methods to identify critical mission events and associated information gaps, as well as intuitive interfaces by which the human and machine can rapidly gain shared situation awareness and dynamically coordinate any adjustments needed in the vehicles’ operations, with respect to the temporal, spatial, and mission relevant demands. Supplementing the control station with interfaces and services to restore and maintain situation awareness will result in more resilient operations. In sum, the controls and displays in the operator’s control station need to support human-machine shared awareness during distributed, disaggregated operations under a variety of communication conditions. Completion of this effort will involve identifying control and display requirements to support human-machine teamwork (i.e., cooperative tasking) for agile, efficient mission execution. This should include an analysis of requirements for a variety of communication conditions, as the design approach likely is situation dependent. For example, relevant questions include: What techniques can be employed to help keep the operator in-the-loop during communication loss? How best should the interfaces identify information gaps, present the machines’ actions during lost communications, and cue evolving collaboration/cooperation opportunities? How should communications be prioritized for re-establishing common ground after communications resume? What interaction modes/strategies are useful for supporting subsequent human-machine joint decision-making and task planning/execution? What mechanisms are best to specify alternatives, perhaps proactively, for different communication states/mission events? This effort addresses the design and evaluation of interfaces that support human-machine shared situation awareness. Aside from addressing (simulated or real) human and autonomy team members completing multiple tasks under varying communication conditions, the proposer can choose systems/tasks/mission(s) to utilize, as long as the effort considers at least two air vehicles (manned and unmanned). (Any simulated or representative system employed should maintain data at an unclassified level. Proposers should not require government equipment or facilities.)
PHASE I: Design/evaluate displays, controls, and/or decision aids to support operator-machine teaming to maintain shared awareness of manned and unmanned air vehicles operations with limited communications. Generate final report describing solution(s), evaluation results, and an experimental plan to establish usability improvements in Phase II. A feasibility demonstration is desirable, but not required.
PHASE II: Perform iterative test/refine cycles on Phase 1’s design, culminating in a proof-of-concept interface/decision support system. Using high-fidelity simulations, evaluate prototype’s effectiveness in maintaining human-machine shared awareness during distributed, disaggregated operations under a variety of communication conditions. Required Phase II deliverables include final report and software/hardware required to demonstrate the interface concept on a stand-alone capability and/or suitable to be executed in a USAF simulation that is mutually agreeable to the contractor and AFRL.
PHASE III: Applications include planning and executing any military or commercial (e.g., law enforcement) plan using highly autonomous unmanned vehicles in decentralized operations with limited communications. Some interfaces and methodologies will be applicable to other human-machine teaming applications.
REFERENCES:1. United States Air Force. (2015), Air Force Future Operating Concept: A View of the Air Force in 2035. Available at: http://www.af.mil/Portals/1/images/airpower/AFFOC.pdf.; 2. United States Air Force. (2015), Autonomous Horizons: System Autonomy in the Air force – A Path to the Future, Volume 1: Human-Autonomy Teaming. USAF Office of the Chief Scientist, AF/ST-TR-15-01.; 3. Patzek, M., Rothwell, C., Bearden, G., Ausdenmoore, B., and Rowe, A (2013). Supervisory control state diagrams to depict autonomous activity. In Proceedings of the 2013 International Symposium on Aviation Psychology, Dayton, OH.; 4. Draper, M., Calhoun, G., Hansen, M., Douglass, S., Spriggs, S., Patzek, M., Rowe, A., Evans, D., Ruff, H., Behymer, K., Howard, M., Bearden, G., Frost, E. (2017). Intelligent multi-unmanned vehicle planner with adaptive collaborative control technologies (IMPACT). International Symposium of Aviation Psychology.
KEYWORDS: Unmanned Vehicle, Human-machine Interface, Situation Awareness, Decision Support, Intelligent Agent, Communication, Distributed Operations, Human-machine Teaming
TECHNOLOGY AREA(S): Human Systems
OBJECTIVE: The objective of this program is to develop a three dimensional (3D) bioprinted tissue or organ that recapitulates and simulates human-level architectures, microstructures, and physiological conditions. Successful development of a platform that encompasses functionality of human organ(s) integrated into a single platform would allow for robust analysis human performance with the ease and flexibility in a small, light-weight, and transportable device. The first phase is to develop a 3D-bioprinted tissue with human cells that simulate complex multi-cell functions. The second phase will require integrated, real-time biosensors using chip or other microelectronic technology for sensing and analysis of kinetic biological signals of stress and resiliency. The resultant platform would ultimately provide a capability to respond in a physiologically-relevant manner and continually monitor unique biosignatures from physical stressors (such as extreme temperature or hypoxic environments) or environmental exposures (such as chemicals, particles, or radiation).
DESCRIPTION: The development of microfluidic technologies has catalyzed the merging of sensors, fabrication, and tissue engineering on the micro- and nanometer size regime. For example, the organ-on-chip construct allows for the ex vivo design of organ level architectures, microstructures, and physical conditions to bring life-relevant functionality of human organs packaged in devices commonly the size of a quarter. Over the last 5 years, the prevalence of microfluidic manuscripts have sky-rocketed, mainly for the purpose of developing sensing applications. One aspect of photolithography constructed microdevices is that they are prepared layer-by-layer and require sealing, interfacing, and aligning small channels to create passages for cell and matrix seeding, perfusion, and solution delivery. Therefore, due to this planar development process, the configuration of 3D features or cellular structures has been traditionally more difficult. However, using a bioprinter, complex 3D highly organized tissue structures can be rapidly created and integrated with precisely sized channels. The second component of this integrated platform will involve a sensor system that provides “real-time,” physiologically relevant alerts due to threats from various environmental stressors.
PHASE I: Create an integrated platform encompassing a select organ(s). The platform must have the ability to detect, collect, and display information after exposure to environmental stressors. The design concept can include, but is not limited to, microdevices with channels, wells and/or connections that create passages for cell seeding, perfusion, and experimental solution delivery. The resultant integrated platform must be an innovative concept and be associated with a theoretical algorithm or software. The human cells used must be specific to the unique perfusion and cell-types of the selected organ(s). This Phase will demonstrate the feasibility of producing a model capable of simulating an organ with key components, must be connected physically and fluidically to an external stimuli, and produce data that will allow for an understanding of exposure and the potential biosignatures of interest.
PHASE II: The second phase will require integration of a sensor system onto a microprocessor, such as a chip) to provide real-time, continual monitoring of biologically-derived signatures. The sensor system will provide electrical, biochemical, photo, and/or physical monitoring outputs in as a response to stimuli. The components of this sensor system need to be fully integrated into the tissue model in a small, 3D configuration in order to ensure portability and ease of use. The biosignatures should be relevant for detecting exposure, threat level, and/or resiliency parameters to maintain Airmen health, performance, and/or cognition. A test-bed validation of known biosignatures within the tissue or organ is necessary for product translation.
PHASE III: The portable device will be fully operational for up to 48 hours with ability to detect the health effects of physical stressors or environmental exposures through known biosignatures in real-time.
REFERENCES:1. Jinah Jang, Hee-Gyeong Yi, and Dong-Woo Cho (2016) : 3D Printed Tissue Models: Present and Future; ACS Biomater. Sci. Eng., Publication Date (Web): April 30, 2016 DOI: 10.1021/acsbiomaterials.6b00129; 2. 3D Bioprinting for Tissue and Organ Fabrication. (2016) Zhang YS, et al Ann Biomed Eng. 2016 Apr 28. [Epub ahead of print]; 3. Label-Free and Regenerative Electrochemical Microfluidic Biosensors for Continual Monitoring of Cell Secretomes. (2017) Shin SR et al., Adv Sci (Weinh). 6;4(5):1600522. doi: 10.1002/advs.201600522. eCollection
KEYWORDS: 3D Bioprinting, Sensor Development, Biosignatures, Organ On Chip
TECHNOLOGY AREA(S): Bio Medical
OBJECTIVE: Develop a non-contact sensor for cardiopulmonary vital sign monitoring. This sensor should remotely measure physiology and demonstrate real-time functionality. Government-furnished materials, equipment, and facilities will not be provided.
DESCRIPTION: The U.S. Air Force is interested in developing non-invasive sensor systems for use in special operations, command and control (e.g., human-machine teaming), and adaptive training, as examples. Such a system would monitor vital and physiological information of an Airman and provide that information for medical or cognitive interpretation. In some situations, it may be preferred to have these sensors be remote from the end-user’s perspective, maximizing utility and minimizing effects on day-to-day operations. While the application of this technology to medical monitoring is clear, proof-of-concept demonstrations have shown how physiological information can be used to estimate current cognitive capacity in the context of human-machine teaming, and this could be extended to facilitate individualized, adaptive training. However, currently-available sensors are not conducive to operational environments for reasons including but not limited to invasiveness, security, privacy, and daily use in a job performance context. Current state-of-the-practice in persistent cardiopulmonary vital sign monitoring requires physically-worn sensors. For example, standard clinical practice for pulse rate measurement requires adhesive electrodes that can irritate the skin with repeated use or bulky optical sensors that impede normal behavior (e.g., for pulse oximetry). In the commercial sector, sensor concepts have evolved to be integrated into numerous wrist- and abdomen-worn devices. However, these wearable devices are commonly known to have less-than-accurate characterizations of one’s physiology. Common characteristics of all wearable devices that may be less desirable in military-relevant settings include: limited battery life, required transmission of data through wireless protocols, short product life-cycles, single-user limitations, inability to access raw data, and fragility in operational conditions The focus of this topic is to develop and demonstrate cardiopulmonary sensor solutions that are more appropriate for these operational use cases. Ideal characteristics of such a sensor would provide remote, non-invasive measurement of the Airman’s vital sign physiology. In this context, we consider a sensor to be sufficiently ‘remote’ when the sensor-to-Airman distance is on the order of meters (e.g., sensors placed within a desk or workstation environment), at minimum. Recent work in the area of imaging photoplethysmography (iPPG) shows great promise in providing such a capability, although there are many other options, as well, some which are mentioned in the included references.
PHASE I: Design a concept for remote, noninvasive cardiopulmonary vital sign measurement that meets operational transition requirements. From this conceptual design, develop a breadboard system to determine technical feasibility. Establish performance goals for breadboard system and perform an analysis of prototype system performance in a laboratory environment.
PHASE II: Develop, demonstrate, and validate complete prototype system for remote, cardiopulmonary vital sign measurement, in real-time, with limited a priori calibration. Construct and demonstrate operation of the prototype in a relevant, simulated operational environment. Establish performance parameters through laboratory characterization experiments. Provide a practical implementation of the sensor given operational constraints. Deliver prototype system(s) to the government customer.
PHASE III: Technology transition facilitated from non-SBIR/STTR government sources (military or private sector). End-state vision is a system, meeting operational requirements, that can be used to research and develop aforementioned target applications. Pursue dual-use commercial applications (e.g., clinical).
REFERENCES:1. Kranjec, J., Beguš, S., Geršak, G., & Drnovšek, J. (2014). Non-contact heart rate and heart rate variability measurements: A review. Biomedical Signal Processing and Control, 13, 102-112.; 2. McDuff, D. J., Estepp, J. R., Piasecki, A. M., & Blackford, E. B. (2015, August). A survey of remote optical photoplethysmographic imaging methods. In Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the; 3. Teichmann, D., Brüser, C., Eilebrecht, B., Abbas, A., Blanik, N., & Leonhardt, S. (2012, August). Non-contact monitoring techniques-principles and applications. In Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE (pp. 1302-1305). IEEE.; 4. Estepp, J. R., Blackford, E. B., & Meier, C. M. (2014, October). Recovering pulse rate during motion artifact with a multi-imager array for non-contact imaging photoplethysmography. In Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on (pp. 1462-1469). IEEE.
KEYWORDS: Heart Rate, Physiology, Remote, Non-contact, Sensor, Patient Monitoring, Vital Signs, Imaging
TECHNOLOGY AREA(S): Materials
OBJECTIVE: Develop intelligent robot path planning process for grinding of aircraft propeller blades.
DESCRIPTION: Repair operations on aircraft propellers such as C130 are carried out by robotic grinding operations. The current process uses a fixed robot path for each blade geometry. An opportunity exists to intelligently customize the robot path for the specific defects found on a part. The proposed research would use coordinate measurement machine probing and 3D scanning techniques to build a model of the blade and then automatically generate customized robot grinding tool paths specific to the defects of the blade. The scanning should be automated as well with automation for filtering scan data and converting to a suitable format as a starting point 3D model for path planning. The scanned model and original CAD design of the part should be registered and aligned properly for path planning. The automatic path will then be made to correct defects by removing material from the scanned model to move into tolerance with the original CAD design. Additionally, the path planning system should focus on usability, flexibility, and supportability. Minimal training and learning curve should be required to use the path planning process. The software user interface should provide enough control to react to different blade geometries and defect types. The software should be easy to upgrade and allow modest refinements by users via plugins, scripts, and other end user software customizations.
PHASE I: Develop a proof of concept path planning system prototype. In this phase, the process will demonstrate making a robot path plan from 3D scan data. Customization of the path plan might be limited to only Z height corrections. The prototyping in this phase will provide key input to specifying and defining the path planning software to be delivered in phase II.
PHASE II: Develop the path planning system to a deployment ready state. Greater ability to make corrections in full 3D will be implemented. The path plans produced by the process will be verified on target robot systems. Ease of use will be evaluated using novice users. The goal of the phase II will be a working robot grinding software the results in measurable improvements in the rate of success of propeller blade repair.
PHASE III: Robotic grinding has many commercial applications. A successful system could be marketed to commercial aerospace industry as well as other defense customers. Additional markets might include the construction, automotive, and shipbuilding industries.
REFERENCES:1. Wang, W. and Choa, Y. “A Path Planning Method for Robotic Belt Surface Grinding”, Chinese Journal of Aeronautics, Vol. 24., Issue 4, August 2011.; 2. Li, S. Xie, X. and Yin, L. “Research on Robotic Trajectory Automatic Generation Method for Complex Surface Grinding and Polishing”, ICIRA 2014: Intelligent Robotics and Applications, 2014.; 3. Sufian, M., Chen, X. Yu, D., “Investigating the Capability of Precision in Robotic Grinding”, Automation and Computing (ICAC), October 2017.
KEYWORDS: Grinding, Robotic, Path, Intelligent
TECHNOLOGY AREA(S): Weapons
OBJECTIVE: Develop a 3D imaging approach that meets the spatial and temporal requirements needed for tracking and aim-point maintenance in the presence of target-pose changes for directed-energy (DE) missions.
DESCRIPTION: Target-pose changes tend to be the “Achilles’ heel” to modern tracking and aim-point maintenance solutions for realistic DE missions. Provided well-characterized targets, there are approaches that perform well (e.g., centroid and correlation tracking ); however, for realistic DE missions, tracking and aim-point maintenance techniques must function with uncharacterized targets that inevitably change pose. Such engineering constraints necessitate the development of a 3D imaging approach that can characterize targets (through target-depth information ) and perform tracking and aim-point maintenance functions in the presence of target-pose changes. A recent dissertation effort, for instance, developed a 3D imaging approach  using spatial heterodyne . This STTR topic looks to develop a 3D imaging approach which meets the spatial and temporal requirements needed for integration into DE systems. For realistic DE missions, the associated laser-target interaction does not provide a mirror-like reflection and in the presence of distributed-volume aberrations, results in speckle and scintillation, in addition to anisoplanatism, at the receiver. The identified approach must also be robust against low signal-to-noise ratios; size, weight, and power constraints; and latency in the tracking loop. The end goal of this STTR topic is to develop (Phase I and II) and demonstrate (Phase III) a 3D imaging approach that can characterize targets and perform tracking and aim-point maintenance functions in the presence of target-pose changes for realistic DE missions. As such, a Phase I effort shall develop a 3D imaging approach via detailed theoretical and numerical studies that verify wave-optics calculations for a variety of ranges and resolutions. A Phase II effort shall then develop experiments that verify the wave-optics calculations. For this purpose, facilities at AFRL could provide the scaled-laboratory environment needed to explore a variety of ranges and resolutions. A Phase III effort could then demonstrate 3D imaging at distances greater than 1 km in a field environment with moving targets. Such testing shall ensure commercialization of the developed approach.
PHASE I: To achieve the identified Phase II objectives, a Phase I effort shall focus on the following deliverables. • Performing wave-optics calculations for a variety of ranges and resolutions. These calculations shall identify scalability and include the relationship between the aperture, the distributed-volume aberrations, and the 3D targets of interest. This step shall ensure that the developed approach is ready for a Phase II effort.
PHASE II: To achieve the identified Phase III objectives, a Phase II effort shall focus on the following deliverables. • Performing scaled-laboratory experiments (potentially at AFRL) in order to verify the wave-optics calculations performed in a Phase I effort. This step shall ensure that the developed approach is ready for a Phase III effort.
PHASE III: Military application: Demonstrating the developed approach in a field environment at distances greater than 1 km with moving targets. This step shall ensure that the developed approach is ready for realistic DE missions. Commercial Application: The successfully demonstrated 3D imaging approach shall translate into a high-fidelity solution that is available to the DoD.
REFERENCES:1. P. Merritt and M. Spencer, Beam Control for Laser Systems 2nd Edition, Directed Energy Professional Society, Albuquerque, NM (2012).; 2. R. Ng, M. Levoy, M. Bredif, G. Duval, M. Horowitz, and P. Hanrahan, “Light Field Photography with a Hand-held Plenoptic Camera,” Stanford Tech Report CTSR 2005-02, 1-11 (2005).; 3. J. W. Stafford, B. D. Duncan, and D. J. Rabb, “Phase gradient algorithm method for three-dimensional holographic ladar imaging,” App. Opt. 55(17), 4611-4620 (2016).; 4. M. F. Spencer, “Spatial Heterodyne,” Encyclopedia of Modern Optics II Volume 4, 369-400 (2018).
KEYWORDS: 3D Imaging, Tracking, Aim-point Maintenance, Beam Control, Adaptive Optics
TECHNOLOGY AREA(S): Sensors
OBJECTIVE: Develop a vibration imaging approach that meets the spatial and temporal requirements needed to perform high-fidelity characterizations of extended, non-cooperative targets (aka combat identification) at extended standoffs with an aperture that has dual purpose for both directed-energy (DE) and intelligence, surveillance, and reconnaissance (ISR) missions.
DESCRIPTION: Vibration imaging offers a distinct way forward with respect to combat identification at extended standoffs for both DE and ISR missions. In practice, vibration imaging offers many advantages over a single-pixel laser Doppler vibrometer . This is said because vibration imaging simultaneously acquires and resolves velocity data over an extended spatial area. Given a single-pixel laser Doppler vibrometer, speckle is a dominant noise source, since the signal fades caused by speckle lead to velocity estimates which have spikes and an elevated noise floor. Via simultaneous data acquisition with a focal-plane array, vibration imaging offers the ability to spatially average which ultimately enables speckle-noise mitigation. Vibration imaging works via the use of doublet-pulse vibrometry . Here, the collection of multiplexed digital-holography data enables us to simultaneously measure the complex-optical field associated with two laser pulses separated in time [3, 4]. By estimating the phase difference between the two received pulses, we can then measure the target’s velocity . In turn, vibration imaging enables us to perform target identification at extended standoffs. Such functionality offers promise for both DE and ISR missions, where it is important to know the characteristics of extended, non-cooperative targets. This added functionality will ultimately enable future DE and ISR assets to determine, for example, whether the engine is running or not (at a distance that is safe for inspection). It will also enable us to tell how fast the speckle is changing, which is currently an unknown. With this in mind, many DE and ISR solutions assume that the received speckle is either correlated or uncorrelated frame to frame; thus, it is important that we characterize this phenomena in the near future, so that we can move forward with the development of future DE and ISR assets. The end goal of this STTR topic is to design (Phase I and II) and demonstrate (Phase III) a vibration imaging approach that meets the spatial and temporal requirements needed to perform high-fidelity characterizations of extended, non-cooperative targets at extended standoffs. As such, during a Phase I effort, a detailed theoretical and numerical analysis shall be performed to explicitly verify wave-optics calculations for a variety of ranges and resolutions. A Phase II effort shall then develop experiments that verify the wave-optics calculations. For this purpose, facilities at AFRL could provide the scaled-laboratory environment needed to explore a variety of ranges and resolutions. A Phase III effort could then demonstrate vibration imaging at distances greater than 1 km in a field environment with moving targets. Such testing shall ensure commercialization of the developed approach.
PHASE I: To achieve the identified Phase II objectives, a Phase I effort shall focus on the following deliverables. • Performing wave-optics calculations for a variety of ranges and resolutions. These calculations shall identify scalability and include the relationship between the aperture and the extended, non-cooperative targets of interest while at extended standoffs. This step shall ensure that the developed approach is ready for a Phase II effort.
PHASE II: To achieve the identified Phase III objectives, a Phase II effort shall focus on the following deliverables. • Performing scaled-laboratory experiments (potentially at AFRL) in order to verify the wave-optics calculations performed in a Phase I effort. This step shall ensure that the developed approach is ready for a Phase III effort.
PHASE III: Military application: Demonstrating the developed approach in a field environment at distances greater than 1 km with moving targets. This step shall ensure that the developed approach is ready for both DE and ISR missions. Commercial Application: The successfully demonstrated vibration imaging approach shall translate into a high-fidelity solution that is available to the DoD.
REFERENCES:1. P. Castellini, G. M. Revel, and E. P. Tomasini, “Laser Doppler Vibrometry,” An Introduction to Optoelectronic Sensors, 216-229 (2009); 2. P. Gatt et al., “Phased Array Science and Engineering Research (PHASER) Program Final Report,” TR CDRL-A001-01, Lockheed Martin Coherent Technologies (2015) [Dist. C, Export Controlled].; 3. S. T. Thurman and A. Bratcher, “Multiplexed synthetic-aperture digital holography,” App. Opt. 54(3), 559-568 (2015).; 4. M. F. Spencer, “Spatial Heterodyne,” Encyclopedia of Modern Optics II Volume 4, 369-400 (2018).
KEYWORDS: Vibration Imaging, Vibrometry, Combat Identification, Beam Control, Digital Holography, Spatial Heterodyne
TECHNOLOGY AREA(S): Weapons
OBJECTIVE: Develop a synthetic scene generation package that meets the baseline technical requirements, connects to other simulation tools, and operates efficiently in high performance computing (HPC) environments.
DESCRIPTION: Synthetic scene generation software produces images of distant targets within their background. Such synthetic images reduce our dependence on expensive field tests. Some applications in the area of directed energy include testing tracking algorithms or real-time tracking hardware, informing a beam control system in a broader high energy laser simulation, and studying target acquisition and aimpoint identification [1,2]. Applications outside of directed energy include remote sensing, laser radar, night vision, munitions targeting, and space situational awareness [3,4]. Unfortunately, the community uses a large number of different scene generation codes, each with its own advantages and disadvantages. While some codes meet most of the baseline technical requirements, they lack critical interfaces, documentation, and compatibility with high performance computing (HPC) environments; or vice versa. Thus, programs often waste significant funds by creating their own scene generation code or by developing single-use interfaces and modifications to existing software. This STTR topic will enhance the practical and technical capabilities of one of those codes in three ways in order to create a product which is more broadly useful. First, this topic will modify the code for efficient execution and cross-code communication in HPC environments. This change will allow us to quickly exercise high-fidelity models of laser systems by leveraging HPC resources. Second, it will modularize and document the code, and improve interfaces, allowing connections to diverse laser physics models and hardware testbeds. Third, it will improve the technical capabilities to meet the baseline requirements of high energy laser system modeling. The end goal of this STTR topic is to develop a scene generation package which is useful for many applications. As such, a Phase I effort shall produce a software development plan that will meet the requirements for technical capabilities, interfaces, documentation, and HPC-compatibility. It will also conduct proof of concept tests on an HPC system. A Phase II effort shall execute the software development plan and demonstrate full capability in relevant HPC environments. A Phase III effort could then focus on advanced, research-grade capabilities which would make the final product state-of-the-art in a number of areas. Such capabilities shall ensure commercial success of the end product.
PHASE I: To achieve the identified Phase II capabilities, a Phase I effort shall focus on the following deliverables: • Perform an interface requirements analysis. • Create a software development plan. • Develop a plan for execution on HPC assets. • Conduct proof of concept tests on relevant HPC systems.
PHASE II: A Phase II effort shall create a scene generation product which is useful for a broad range of applications. • Convert all modules for execution on HPCs. • Enhance the technical capabilities as needed. • Include software-to-software interfacing (i.e. an API) with Matlab and other codes. • Document the modules and their interfaces. • Perform a demonstration of full capability in a relevant HPC environment.
PHASE III: A Phase III effort shall develop the advanced technical capabilities needed by future programs. • Target heating and damage • Depth-resolved imaging • Earth shine and sky glow • Clutter, horizon, cloud structure, and water surface structure • Astronomical backgrounds • Multiple illuminators with backscatter
REFERENCES:1. M. A. Owens, M. B. Cole, M. R. Laine, “Integration of Irma tactical scene generator into directed-energy weapon system simulation,” Proc. SPIE 5097 (2003).; 2. N. R. Van Zandt, J. E. McCrae, and S. T. Fiorino, “PITBUL: a physics-based modeling package for imaging and tracking of airborne targets for HEL applications including active illumination,” Proc. SPIE 8732, 87320H (2013).; 3. J. F. Riker, G. A. Crockett, and R. L. Brunson, “The time-domain analysis simulation for advanced tracking (TASAT),” Proc. SPIE 1697, 297-309 (1992).; 4. D. Crow, C. Coker, and W. Keen, “Fast line-of-sight imagery for target and exhaust-plume signatures (FLITES) scene generation program,” Proc. SPIE 6208, 62080J (2006).
KEYWORDS: Synthetic Scene Generation, Image Synthesis, Rendering, Computer Graphics, Target Tracking, Beam Control, High Performance Computing, Application Programming Interface (API)
TECHNOLOGY AREA(S): Sensors
OBJECTIVE: Deliver analysis, design, optical components, and controls for system to optimally couple light from Sodium Guide Star laser (FASOR, Toptica) by manipulation of the beam's polarization state, modulation of laser, or combination of two.
DESCRIPTION: Coupling of Sodium Guide Star light into the sodium layer is dependent upon characteristics of the light illuminating the layer and the alignment of the sodium atom in the layer. The sodium atoms tend to align their dipole with the magnetic field of the earth. This results in varying returns dependent upon the geographic location of the guide star laser and geometry of the illumination relative to the magnetic field. Strong returns from the sodium layer independent of geographic location and illumination geometry is needed to enable responsive space situational awareness capabilities for imaging dim LEO satellites and detecting proximity objects in GEO. Controlling polarization of the Guide Star laser relative to the sodium layer has potential to improve returns. Techniques to modulate the polarization to match Larmor precession of the sodium atoms could allow significant improvement in Guide Star efficiency. Other techniques for modulating the Guide Star beam and controlling polarization with the end goal of optimizing returns are of interest.
PHASE I: 1) Develop concepts to optimize Sodium Guide Star laser return through modulation and/or polarization control. 2) Work with sponsoring facility to determine initial proof of concept and testing methods.
PHASE II: 1) Refine design of optical components based on testing in Phase I. 2) Fabricate improved optical components and control system based on sponsoring facility requirements. 3) Deploy optical components and conduct on-sky testing to determine operational performance of the system.
PHASE III: 1) Demonstrate assembled prototype unit ready to deliver to field along with an estimate of the life cycle cost. 2) Deliver, install, and test at least one prototype at Air Force operated electro-optic tracking facility.
REFERENCES:1. “Improving sodium laser guide star brightness by polarization switching,” Tingwei Fan, Tianhua Zhou, & Yan Feng, Scientific Reports, 22 January 2016 (https://www.nature.com/articles/srep19859.pdf); 2. “Sodium Laser Guide Star Brightness, Spotsize, and Sodium Layer Abundance,” Jian Ge, et. al., GE ’98 (http://www.oir.caltech.edu/twiki_oir/pub/Palomar/PalmLGS/LgsLinks/ge98.pdf); 3. “Sodium Guidestar Radiometry Results from the SOR's 50W Fasor,” Jack Drummond, Steve Novotny, Craig Denman, Paul Hillman, John Telle, Gerald Moore, AMOS Technical Conference, 2006 (https://amostech.com/TechnicalPapers/2006/Lasers/Drummond.pdf)
KEYWORDS: Guide Star Laser, Sodium Layer, Polarization, SSA
TECHNOLOGY AREA(S): Info Systems
OBJECTIVE: To develop methods that produce “human-like” decision capabilities. This methodology will be used to improve computer interpretation of visual scenes without human intervention.
DESCRIPTION: Human decision making is an area that has been studied extensively but with little consensus in how it is actually implemented in the brain. Current attempts to correlate neural activity in the brain with externally observed human responses seems to indicate that the Bayesian paradigm is a key component of that neural processing. For example, “Studies of human cue integration, both within modality (e.g. stereo and texture) and across modality (e.g. sight and touch or sight and sound), consistently find cue weights that vary in the manner predicted by Bayesian theory” , , , , . In addition to lending support to the Bayesian paradigm, understanding how humans integrate various modalities of sensor inputs will lend considerable insight into how computers can integrate heterogeneous data sources such as infrared, visual, and RF, to name just a few. In conjunction with the Bayesian hypothesis of neural coding, it is of key interest to determine how population of neurons encode uncertainty . As other researchers have reported human decision making appears to have the unique ability to glean information from visual scenes by the mechanism of reducing the uncertainty or entropy , . In the latter reference some progress has been made in applying the entropy idea to object localization in images. Recent attempts to apply human decision making ideas have centered about neural networks. These approaches have not focused on the perceived qualities of the brain in decision making, and are somewhat restricted for surveillance applications due to their limitations in accommodating changing environments for which they are trained. It is desired to emulate human decision making using more holistic approaches. These include, but are not limited to, the availability of multi-modal data, the use of hierarchical decision making, confidence factors associated with intermediary decisions, and feedback mechanisms to detect and correct erroneous intermediary decisions.
PHASE I: Identify statistical approaches that emulate human decision making for surveillance applications based on partial information obtained from multiple sensors to achieve objectives (e.g. detection, localization and tracking). Quantify performance gains relative to conventional algorithms. Use synthetic data sets to demonstrate effectiveness. A baseline approach in common use should be used for performance comparisons.
PHASE II: Further refine and develop the statistical models and algorithms for radar signal processing tasks. Conduct high fidelity demonstration/validation of algorithm performance, based on finer grained simulations. Develop a baseline embedded computing approach for meeting tactical timeline requirements for chosen applications. Quantify performance gains relative to conventional algorithms
PHASE III: Military applications may include: improved detection, localization, and tracking of various emitters in diverse military scenarios, having potential applicability across the entire DOD ISR enterprise. Commercial applications may include fields such as law enforcement, medical, and automotive
REFERENCES:1. Zhou, F., et al, “Affective parameter shaping in user experience prospect evaluation based on hierarchical Bayesian estimation”, Expert Systems with Applications, Elsevier, Jul. 2017.; 2. Knill, D.C., A. Pouget, ``The Bayesian brain: the Role of Uncertainty in Neural Coding and Computation'', Trends in Neuroscience, Dec. 2004.; 3. Korn, C.W., D.R. Bach, “Heuristic and optimal policy computations in the brain during sequential decision-making”, Nature Comm., Jan. 2018.; 4. Dayan, P., L.F. Abbott, Theoretical Neuroscience, MIT Press, 2001.
KEYWORDS: Autonomous Vehicles, Human Decision Making, Hierarchical Statistical Models
TECHNOLOGY AREA(S): Info Systems
OBJECTIVE: Develop a new high-fidelity modeling and simulation (M&S) framework that addresses the need for voluminous and high-quality Multi-INT training data for deep learning networks that would be too expensive and infeasible based on costly field experiments. The focus of this effort is on multiphysics-based modeling of radio frequency (RF) signals in realistic physical and contested environments. Effective training methods for deep learning systems are essential for improving the performance of autonomous systems.
DESCRIPTION: A key enabler for improved system performance while reducing operator workload is autonomy powered by next generation machine intelligence. However, for such deep learning systems to be effective, massive amounts of realistic and relevant “training data” is required . Given the highly sensitive and variable nature of RF collection and exploitation, it is simply not possible to conduct field experiments capable of meeting these requirements. Fortunately, commercially available next generation high-fidelity physics-based M&S tools have been developed that can form the basis for an RF “virtual reality” Multi-INT Deep Learning (VR-MDL) environment (see for example ). Thus, the goal of this project is to develop an M&S environment to address the robust training needs of deep learning networks and other machine intelligence and cognitive systems such as DARPA/AFRL KASSPER and CoFAR projects [3-5]. The VR-MDL environment should be capable of supporting all physical elements of the RF collection process, from raw multichannel, multiplatform in-phase and quadrature (I&Q) signals, through the various RF processing chain (e.g., mixing, amplifiers, analog-to-digital conversion, etc.). The output of this effort should be a general-purpose M&S environment that is agnostic to the particular machine learning algorithm or architecture.
PHASE I: Develop a baseline design for a VR-MDL environment. The design should have the potential of achieving the aforementioned goals of producing massive amounts of high-fidelity, physics-based, RF training data generated via realistic CONOPS. Quantitative analyses and experiments shall be conducted that establish the scalability of the proposed VR-MDL approach. Basic M&S examples shall be conducted in Phase I that establish the viability of the training data generated by comparing it with actual collected data with the same type of sensor and scenario being modeled by the VR-MDL M&S tool.
PHASE II: Further refine and develop the VR-MDL design from Phase I, and enhance the complexity and sophistication of the VR scenarios conducted. The output of Phase II should be a VR-MDL tool that is ready to enter low-rate initial production (LRIP) at the beginning of Phase III.
PHASE III: The proposer will identify potential commercial and dual use applications such as non-military applications of deep learning techniques. These could include training for autonomous systems such as self-driving cars and unmanned air systems (UAS) operating in civilian airspace.
REFERENCES:1. X.-W. Chen and X. Lin, "Big data deep learning: challenges and perspectives," IEEE access, vol. 2, pp. 514-525, 2014.; 2. RFView(TM). Available: http://rfview.islinc.com; 3. R. Guerci, R. M. Guerci, M. Ranagaswamy, J. S. Bergin, and M. C. Wicks, "CoFAR: Cognitive fully adaptive radar," presented at the IEEE Radar Conference, Cincinnati, OH, 2014.; 4 L. Bell, C. J. Baker, G. E. Smith, J. T. Johnson, and M. Rangaswamy, "Cognitive radar framework for target detection and tracking," IEEE Journal of Selected Topics in Signal Processing, 9(8), 1427-1439, 2015.
KEYWORDS: Multi-INT, Deep Learning, Autonomous Systems, Cognitive Systems, Sensors, Electronics, Modeling And Simulation
Diagnostics for Performance Quantification and Combustion Characterization in Rotational Detonation Rocket Engine (RDRE)
TECHNOLOGY AREA(S): Space Platforms
OBJECTIVE: The objective of this STTR is to transition diagnostic techniques for characterization of the fuel-oxidizer detonation from laboratory usage to Air Force rotation detonation rocket engine (RDRE) applications to increase understanding critical physics, support engineering development, as well as providing validation data for simulations. In this STTR, advanced diagnostic measurement suites are sought to quantify the performance and characterize the detonation combustion process of RDREs, including but not limited to intrusive and non-intrusive pressure, temperature, species and surface heat-transfer measurements in both time-averaged and temporally resolved manners. The sought diagnostic suite is to be integrated into existing experimental/testing RDRE rigs. It is highly desired for deployed diagnostic sensors in the suite to withstand the high-pressure, high-temperature and high-acceleration environment of detonative combustion within actual RDRE operation, up to an order of 1 µs of temporal resolution and a factor of 100 dynamic range in pressure and temperature.
DESCRIPTION: The Rotating Dentation Rocket Engine (RDRE) consists of a quasi–steady state operational mode where one, or more, detonation waves travel around a closed circuit transverse to the propellant injection in an annular channel. The incoming, propellant mixture from the oxidizer and fuel plenums is periodically combusted by a detonation wave traveling at approximately the Chapman–Jouguet velocity, DCJ. In laboratory devices, DCJ typically ranges between 1–3 km/s resulting in a 4-50 kHz frequency depending on annulus diameter and number of transverse detonation waves. The detonation waves increase pressures of the injected propellants by a factor of 10-20, resulting in a higher energy release efficiency. Immediately behind the transverse detonation wave, the high-pressure combustion products expand and accelerate. In the high-pressure regions immediately following the transverse detonation wave, the localized high pressure of the combustion products temporarily halts propellant injection. As a result, injection, combustion, and combustion product acceleration are all closely linked in these devices. Constant volume, or detonative, combustion theoretically extracts more energy from the fuel-oxidizer mix, thereby increasing energy conversion system performance. In rocket propulsion, devices such as RDREs use a series traveling detonation waves to realize this potentially more efficient energy extraction scheme. The detonation wave time separation over a single injector has been measured to vary between 20-250 µs. The fast, repeating rapid detonation wave coupled with the harsh combustion environment produces a highly dynamic pressure and temperature field that is beyond the ability of existing combustion diagnostic techniques presently employed in conventional deflagration combustion research. This solicitation is seeking to develop advanced diagnostic suite to quantify the performance and characterize the detonation combustion process for the rotation detonation rocket engine (RDRE), including but not limited to intrusive and non-intrusive pressure, temperature, species and surface heat-transfer measurements in both time-averaged and temporally resolved fashion. The sought diagnostic suite is to be integrated into actually experimental/testing RDRE rigs. It is highly desired for deployed diagnostic sensors in the suite to withstand the high-pressure, high-temperature and high-acceleration environment in actual RDRE operation, up to an order of 1 µs of temporal resolution and a factor of 100 dynamic range in pressure and temperature.
PHASE I: In Phase I, an offeror shall provide a creditable design of such suite based on a typical experimental testing device relevant to Air Force RDRE development with sufficient substantiations. Key components in Phase I include: (1) a conceptual design for quantifying the performance and characterizing the detonation combustion process of the RDRE with scientific substantiation, leading to the conceptual design review (CoDR); (2) Demonstration of selected sensors in conceptual design, leading to the censor substantiation review (CSR); (3) a preliminary design of such advance suite integrated into an Air Force relevant RDRE device with engineering substantiations and additional needed scientific substantiations, leading to the preliminary design review (PDR) and a Phase II proposal. In the Phase I proposals, offerors shall use a publically available RDRE configuration to present their diagnostic approach/ strategy and scientific logic for achieving the measurement objective mentioned above. At beginning of Phase I execution, information of an Air Force relevant baseline RDRE experimental/testing rig will be provided to winning offerors.
PHASE II: In Phase II, winning offeror shall (1) complete critical design, leading to the critical design review (CDR) and (2) build the designed advance diagnostic suites, integrate the suite into the provided Air Force RDRE rig and demonstrate the suite’s capability to achieve the measurement objective listed above.
PHASE III: Phase III, based on progresses in Phase II and RDRE development needs, further enhance and extend the advanced diagnostic suite developed in Phase II to an expanded range of measurement objectives.
REFERENCES:1. B. R. Bigler, E. J. Paulson, and W. A. Hargus, Jr., “Idealized Efficiency Calculations For Rotating Detonation Rocket Engine Applications,” AIAA-2017-5011, AIAA Propulsion and Energy Forum, Joint Propulsion Conference, 10-12 July 2017, Atlanta, GA.; 2. F. A. Bykovskii, S. A. Ahdan, and E. F. Vedernikov, “Continuous Spin Detonations,” Journal of Propulsion and Power, Vol. 22, No. 6, pp. 1204–1221, Nov-Dec 2006.; 3. F. K. Lu and E. M. Braun, “Rotating Detonation Wave Propulsion: Experimental Challenges, Modeling and Engine Concepts,” Journal of Propulsion and Power, Vol. 30, No. 5, pp. 1125–1142, Sep-Oct 2014.; 4. M. L. Fotia, F. Schauer, T. Kaemming, and J. Hoke, “Experimental Study of The Performance of A Rotating Detonation Engine With Nozzle,” Journal of Propulsion and Power, Vol. 32, No. 3, pp 674–681, May-Jun 2016.
KEYWORDS: Diagnostics, Rotating Detonation Rocket Engine, Detonation, Time Resolved Combustion Measurements, Isochoric Combustion, High Pressure
TECHNOLOGY AREA(S): Sensors
OBJECTIVE: Develop algorithms to automate the processing of incoming data streams from a diverse and dynamically changing set of sensors to detect, locate, and classify seismic events and flag suspicious events (i.e. possible nuclear tests) for human analysts at extremely low miss rates and the lowest possible false alarm rates.
DESCRIPTION: The automatic system the Air Force uses to monitor the globe for test nuclear explosions processes incoming data streams from hundreds of seismic stations and arrays, including those of the United Nations’ Comprehensive Test Ban Treaty Organization’s (CTBTO) International Monitoring System (IMS), among others. In near real time the system creates catalogs of seismic sources, and identifies and flags suspicious events for human analysts. The system can be overwhelmed when large earthquakes are followed by thousands or tens of thousands of aftershocks. Similarly, current systems can neither process the orders of magnitude more signal detections nor dynamically incorporate the hundreds to thousands of new sensors that will be required to push detection and classification thresholds down to meet mission requirements. New algorithmic approaches are needed to meet this challenge. The most promising approaches are machine learning (ML) methods. The seismic data volumes involved are appropriate for ML methods and the availability of HPC resources makes their processing feasible. The first challenge is to apply ML methods to rapidly and accurately automate the recognition of similar signals in very large data sets (e.g. Yoon, et al., 2015). Most observed seismic signals are repeated (repeating earthquakes, aftershocks, and mining explosions) and their recognition will speed processing by simplifying the association problem. That is, associating all signals across the network with the set of hypothesized events that are most likely to have generated the signals is NP hard (e.g. Arora et al, 2017; Benz et al., 2017). Any signals identified as similar to signals associated with a previously identified event can immediately be associated with a similar repeat event. In addition, the system will need to autonomously identify sets of common nuisance signals generated near stations (e.g. ice quakes at high latitudes, sonic booms near military airfields) and use those to cull signals that are not of monitoring interest. Upon detection of new signals that are not similar to previous signals, the system must then distinguish the signal type (e.g. identify the seismic phase), determine the event location most likely to have generated that signal and other signals recorded across the network (determining which signals are associated with each other, and with a single hypothesized event, is the NP hard problem), and discriminate the source type. The method must also robustly adapt to changes in network configuration and components. Instruments will range from permanent high fidelity 3-component seismometer arrays dedicated to and designed for nuclear explosion monitoring to individual sensors operating for other purposes (e.g. seismic hazard monitoring) that can be opportunistically added “on-the-fly” in regions of interest.
PHASE I: Deliver a final report that 1) evaluates the performance of existing machine learning algorithms applied to components of the network processing problem, including signal detection, identification of repeated similar events, signal classification, event building (i.e. determination of the likeliest set of seismic events that could be the source of the detected signals), and event location and classification, and 2) lays out a plan and rationale for further algorithm refinement, and incorporation of the algorithms into a system that will efficiently process incoming data streams from a dynamic network to accurately identify signals of interest (i.e. possible nuclear tests).
PHASE II: Develop an end-to-end system that incorporates refined versions of algorithms tested in phase 1. Demonstrate substantially improved performance with respect to signal detection and classification, and event formation, location, and classification, of the new system over that of existing state-of-the-art systems (e.g. those of the CTBTO’s or the US Geological Survey’s National Earthquake Information Center [NEIC]. The catalogs of both and the data used are available). The system should be validated with real data streams (e.g. from the IMS or the NEIC networks). Performance metrics should include miss rates and false alarm rates relative to catalogs that have been vetted by human analysts. The system’s ability to adapt on the fly to new data sources should be validated by the addition and deletion of data streams from stations not typically used for monitoring, such as from regional hazard monitoring networks.
PHASE III: In coordination with scientists and engineers from AFRL and AFRL’s operational customer, the Air Force Technical applications Center (AFTAC), transition the system to AFTAC for further evaluation and testing with AFTAC’s data. Delivery must include thorough documentation, users’ manual, case examples, support, and training to ensure effective transition. The system will also have commercial application in regional and national networks used to monitor seismic hazards, volcano monitoring, and induced seismicity (e.g. from mining, geothermal, and fracking).
REFERENCES:1. Yoon, C. E., O. O’Reilly, K. Bergen, and G. Beroza, Earthquake detection through computationally efficient similarity search, Science Advances, 04 Dec 2015, Vol. 1, no. 11, DOI: 10.1126/sciadv.1501057; 2. N. S. Arora, S. Russell, and E. Sudderth, NET-VISA: Network Processing Vertically Integrated Seismic Analysis, Bulletin of the Seismological Society of America, Vol. 103, No. 2a, doi: 10.1785/0120120107; 3. Benz, H., C. E. Johnson, J. M. Patton, N. D. McMahon, P. S. Earle, GLASS 2.0: An Operational, Multimodal, Bayesian Earthquake Data Association Engine, American Geophysical Union, Fall Meeting 2015, abstract id. S21B-2687
KEYWORDS: Nuclear Explosion Monitoring, Machine Learning, Similarity Search
TECHNOLOGY AREA(S): Space Platforms
OBJECTIVE: Develop application-level approaches to performing high assurance software segregation of processes and data developed in the context of a real-time embedded system.
DESCRIPTION: The United States Department of Defense (DoD) continually designs, acquires, and deploys best in class, highly complex and capable embedded systems. Due to their often high cost, low-density, long development time lines, and the mission criticality of the services they may provide, DoD embedded systems have a high value to defense of DoD systems. As we have embraced enhanced embedded system computing capabilities, in most aspects we have become increasingly vulnerable to multiple types of cyber threats. This topic will investigate next-generation approaches to, and the test and verification of, methods that ensure the high-assurance isolation and separation of data and processes from other data and processes within the context of the software of a resource-constrained, real-time, space platform system. Current space platforms require solutions to enabe defense-in-depth against cyber threats, resulting in a system where a single compromised software module cannot propagate throughout the entire system. Furthermore, legacy implementation of multi-level security (MLS) onboard a weapon system requires a dedicated computer and cryptographic system for each level. This topic will investigate new and emerging approaches to address these problems entirely within software, enhancing cyber resiliency while enabling MLS within a single computer at the application-layer, and dramatically reducing the size, weight, power, and cost of hosting multiple software payloads at varying security levels. Current state-of-the-art solutions, as discussed in reference 1, to this problems are not principally developed to provide high-assurance segregation within the system, are limited in the degree of segregation being provided, and impose significant computational overhead that would be unacceptable to a real-time system. The intent of this topic is to develop a prototype approach to data and process segregation that can be fielded as part of a representative ground space platform test bed.
PHASE I: Final report with approaches and methods for data and process segregation within real-time embedded systems, techniques for verification of this data/process segregation, and an executable proof of concept demonstrating the capabilities.
PHASE II: Working implementation of methods (architecture, algorithm, etc) of data/process segregation, working implementation of verification and validation techniques, a repeatable demonstration of methods using an agreed-upon embedded development environment using an agreed-upon real-time operating system and software, and final technical report.
PHASE III: Implementation of developed technologies within an existing ground testbed representative of a selected Air Force architecture. The ground test bed computing architecture will be of a multicore ARMv8-A instruction set architecture.
REFERENCES:1. Samuel Laurén, Sampsa Rauti, and Ville Leppänen. 2017. A Survey on Application Sandboxing Techniques. In Proceedings of the 18th International Conference on Computer Systems and Technologies (CompSysTech'17), Boris Rachev and Angel Smrikarov (Eds.). AC; 2. Hajime Inoue and Stephanie Forrest. 2002. Anomaly intrusion detection in dynamic execution environments. In Proceedings of the 2002 workshop on New security paradigms (NSPW '02). ACM, New York, NY, USA, 52-60. DOI=http://dx.doi.org/10.1145/844102.84411; 3. Cosimo Anglano. 2006. Interceptor: middleware-level application segregation and scheduling for P2P systems. In Proceedings of the 20th international conference on Parallel and distributed processing (IPDPS'06). IEEE Computer Society, Washington, DC, USA, 374-374.
KEYWORDS: Application-level Segregation, Application Sandboxing, Cybersecurity
TECHNOLOGY AREA(S): Space Platforms
OBJECTIVE: Develop next generation energy storage technology that will meet cycle life requirements for DoD Spacecraft and demonstrate >400 Wh/kg full cell performance.
DESCRIPTION: Mass of spacecraft components, especially of the power system, can be a significant portion of the overall spacecraft mass. The need for efficient energy storage in space platforms is paramount as expected lifetime and power needs continue to rise. Increased satellite power needs and the drive to reduce size and mass of power system components necessitates the development of advanced energy storage devices with improved energy density >400 Wh/kg and long life. Batteries used in space must be compatible with 5-year ground storage followed by 15-year operational lifetimes for geosynchronous orbits or up to 60,000 charge and discharge cycles required for low earth orbit. Given unique Air Force energy storage needs, a next generation energy storage technology achieving >400 Wh/kg with the cycle life required in space would be instrumental to achieving higher power spacecraft for enhanced missions. Advanced materials, cell designs, new chemistries, or a combination of these are needed to achieve higher energy density cells. Potential pathways include, but are not limited to, Li-S, graphene batteries, alternative anodes, and CNT additives. These and other methods should achieve >400 Wh/kg on a cell level, discharge rates of 1C, and cycle life of 5000 cycles at 70% depth of discharge. Technologies must maintain the same safety and reliability standards as current lithium ion (Li-ion). Advances in Li-ion are not excluded from consideration, but proposals will need to demonstrate technical pathways to achieve stated specific energy goal at the cell level.
PHASE I: Demonstrate proof of concept for improvements to >400 Wh/kg energy density, cycle life, and rate requirements of the proposed energy storage technology. Present experimental data to show feasibility of the innovative solution. Describe an initial design for prototype along with performance estimates. Outline an improvement plan to accomplish stated metric(s).
PHASE II: Demonstrate significant improvements in the cited metric(s) from Phase I. Demonstrate proof of concept with the fabrication and testing of advanced cell materials and design meeting the requirements (specific energy, cycle life, rate requirements, safety, etc.) outlined in this solicitation. Provide cost projection data to substantiate the design, performance and operation costs. Fabricate and deliver prototype units for potential use on flight experiments and testing. Include a detailed design and performance analysis of prototype cells.
PHASE III: Work with a system integrator to refine requirements and perform flight validation testing of the developed energy storage technology. Build and fly Class D hardware demonstration for space environment.
REFERENCES:1. Xu, Kang, Electrolytes and interphases in Li-ion batteries and beyond, Chemical Reviews 114, 11503-11618 (2014).; 2. Hassoun, J. & Scrosati, B., Review - Advanced in anode and electrolyte materials for the progress of lithium-ion and beyond lithium-ion batteries, Journal of the Electrochemical Society 162, A2582-2588 (2015).
KEYWORDS: High Specific Energy, Space Power Systems, Next Generation Chemistry, Battery, Cathode, Anode
TECHNOLOGY AREA(S): Sensors
OBJECTIVE: This STTR will develop computational imaging systems with application to space missions. New advances in onboard processing hardware enable the Air Force to consider the revolutionary benefits of computational imaging systems for space. These systems may significantly outperform all-optical systems.
DESCRIPTION: The last two decades in imaging science have witnessed a revolution in the way that optical systems may be designed. Driven by the ubiquity of robust computational resources, imaging systems may now be co-designed with both optical and computational elements in ways that can reduce optical design complexity, outperform traditional all-optical systems and even enable entirely new measurement modalities. All three of these benefits of computational imaging may be exploited by space based systems to enable both new functional capabilities and new sensor/constellation CONOPS. This STTR seeks development of computational imaging systems with application to space missions. New advances in onboard processing hardware enable the Air Force to consider the revolutionary benefits of computational imaging systems for space. Of particular interest here are computational imaging systems that combine both optical and computational elements in ways that have the potential to outperform traditional (all-optical) imaging systems. This topic covers computational imaging systems that offer benefits in one or more area: 1) Enhanced imaging performance (spatial/temporal/spectral resolution); 2) significantly shorter development schedule (trivial optical alignment); 3) expedited calibration (cross-calibration of ubiquitous systems); 4) drastically reduced size/weight/cost (alternative scaling laws to all-optical systems); 5) decreased system acquisition time (COTS optics & detectors); 6) new sensor/constellation CONOPS (e.g. on-orbit processing, distributed communications, etc.). It’s expected that systems will be designed/evaluated in terms of: survivability of onboard computational hardware, optical alignment tolerances, susceptibility to spacecraft jitter, practical scaling of optics sizes, and suitability to visible and IR optics/detectors.
PHASE I: - Report of measured/estimated system performance limitations - Baseline system design details – optics, algorithms, etc. - End-to-end single system CONOPS recommendations.
PHASE II: - Prototype computational imaging space based system. - Report of measured system performance limitations related to space flight conditions. - Refined system design details – optics, algorithms, alignment procedures, etc. - Laboratory-based system CONOPS demonstration.
PHASE III: Phase III work is expected to culminate in a space rated demo computational imaging system.
REFERENCES:1. Cossairt, Oliver S., Daniel Miau, and Shree K. Nayar. "Gigapixel computational imaging." Computational Photography (ICCP), 2011 IEEE International Conference on. IEEE, 2011.; 2. Sun, Baoqing, et al. "3D computational imaging with single-pixel detectors." Science 340.6134 (2013).; 3. Velten, Andreas, et al. "Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging." Nature Communications 3 (2012): 745.
KEYWORDS: Computational Imaging, EO/IR Systems, Space Systems
TECHNOLOGY AREA(S): Weapons
OBJECTIVE: The goal of this STTR topic is to develop an integrated multifunctional structural platform that houses nano-sensing elements, to enable a cargo pocket sized (nano) UAS to extract environmental information while surviving and navigating through extremely difficult environments.
DESCRIPTION: Palm-sized UASs, weighing on the order of tens of grams apiece and capable of fitting within a combat fatigue cargo pocket, are proving to be capable personal platforms in urban environments including inside structures due to their ease of transport, inherent stealthiness, and ability to penetrate small spaces. However, such environments are plagued with obstacles of various types, ranging from walls and structures to cables and vegetation that must be avoided or otherwise mitigated to prevent a “crash”. Emerging techniques involve the use of vision sensors and algorithms that allow autonomous negotiation of hazards, including in the dark and in both indoor and outdoor spaces. However, the small mass of such platforms makes them extremely susceptible to fluctuating wind conditions, in particular turbulence found in close-ground environments, which can disrupt computed flight trajectories. Work by other researchers is addressing wind gust sensing with appropriate control strategies to mitigate the effects of turbulence. However, there will still be cases in which wind gusts will temporarily override the abilities of any controller or even the dynamically available thrust from platform actuators. Collisions with hard environmental objects are thus unavoidable, and it is desirable for a platform to be designed such that the “cost” of a collision is a temporary delay of flight for several seconds rather than a mission-ending crash. One approach is to add a “cage” or other structural forms of protection around the platform to prevent contact between rotors or other actuators in the environment. However, when fabricated with conventional materials, such cages are either too heavy or provide protection in limited directions. Furthermore, if they can survive rough contact events, their structures can only tolerate a few impact events before breaking. New research in materials science is leading to the development of materials that can handle repeated stress and impact events. Some examples include composites whose structure is inspired by organisms, for example, the mantis shrimp [ref 2]. In addition to structural issues with crash events, the ability for efficient and effective flights are limited due to the mass of the platform and limited energy storage capacity. As such, adding sensing elements to these platforms reduces the efficacy of flight missions. For example, use of conventional sensors that implement thin films adds significant weight, and limits sensitivity or response times needed. In addition, the number of gas analytes that can be interrogated is constrained. The use of nanowire gas sensors and sensor arrays have the potential to solve these limitations. Nanowire-based gas sensors often provide a fast response time, enable ultrasensitivity, and provide a means to analyze multiple gaseous species. This is primarily due to their high surface-to-volume ratio based on their extremely fine diameters. Thus, they provide a way to detect only a low concentration of gas molecules via minute changes in the electrical properties of the sensing elements. In addition, because of their minimal size, these sensors can be very light weight and use significantly low amounts of power. However, there are many challenges to realizing ultrasensitive and durable nanowires. For example, metal oxide-based systems can fail in a brittle manner rendering them ineffective in robust arenas or utilize too much power. Conversely, polymer-based systems have limited performance based on ambient temperatures or sensitivity to humidity. In order to overcome this, a platform is needed that can integrate sensing elements into physically and chemically robust platforms that can be mounted on nano UASs. In addition, these platforms should perform with minimal mass addition, low power usage and still demonstrate sensitivity. The goal of this topic is to prototype a holistic nano UAS with integrated sensing, structural elements, and hardware having the following characteristics: • Capable of autonomously detecting and homing in on chemicals of interest for both civilian and military applications using on-board sensors; • Capable of navigating through close ground and indoor environments with only top-level human input, while surviving wind-induced collisions with environmental features at up to 10 meters/sec; • Can fit within a cargo pocket.
PHASE I: Through a combination of experimentation, analysis, and simulation, implement and test components of a mechanically and chemically robust sensory platform that is light and utilizes low power. Demonstrate a basic platform that can detect various gases. This work may include breadboard level testing of select components, structural or sensing, including limited flight testing, if feasible, to identify initial uncertainties and areas to address for Phase 2.
PHASE II: Prototype a nano UAS that meets the general characteristics listed above. Perform flight testing of the prototype system in both laboratory and representative environments. Research efforts and test environments should address both civilian and military applications.
PHASE III: Transition the technology for both civilian and military applications. Dual use applications include facilities monitoring, environmental testing, remote sensing of chemical or biological weapons, search and rescue, and ISR
REFERENCES:1. https://www.flir.com/products/black-hornet-prs/ ProxDynamics Black Hornet Nano UAS http; 2. Weaver, J., Milliron, G., Miserez, A., Evans-Lutterodt, K., Herrera, S., Gallana, I., Mershon, W., Swanson, B., Zavattieri, P., DiMasi, E., Kisailus, D. “The Stomatopod Dactyl Club: A Formidable Damage-Tolerant Biological Hammer,” Science, 336 (2012) 1; 3. Barrows, G. et al “Vision Based Hover in Place”, 50th AIAA Aerospace Sciences Meeting, Nashville TN, January 2012.; ALTERNATE REFERENCE SHOWING CENTEYE NANO DRONE https://www.youtube.com/watch?v=YTi8bjbZJ4s
KEYWORDS: Resilient Structure Nanowire Gas Sensor Nanowire Gas Sensor Array Olfactory Ultrasensitivity Or Olfactory Ultra Sensitivity Ultrasensitive Nanowire Or Ultra Sensitive Nanowire Multifunctional Structure And (Micro Air Vehicles Or MAV Or Nano Air
TECHNOLOGY AREA(S): Weapons
OBJECTIVE: Develop controlled (tunable) spatially-varying materials for investigating reflectance and transmission of visible light, high resolution, high apparent temperature, broad-band solution for infrared hardware-in-the-loop scene projection.
DESCRIPTION: New methods have recently shown that photonics crystals can be spatially varied in a smooth manner without causing any discontinuities and defects in the lattice. This results in a new phenomenology such as self-collimation of a light around a sharp bend without loss intensity. This can also lead to the development of a single lattice with disparate functions like beam bending, focusing, and polarization conversion. Moreover, the lattice can be shaped in such a way that the collimated beams are not limited by Snell’s law and the lattice can collect and focus light without the limiting effects of refraction. The purpose of this topic is to use the concepts of spatially-variant photonic crystals with added biological inspired randomness and material. Many biological systems of interest have small index of refraction and have diamond and gyroid structures. In electromagnetic and photonic systems, randomness has been shown to provide wide band gaps and to suppress side lobes of array antennas and frequency selective surfaces. This combination between SVP and randomness should provide more omnidirectional behavior, greater immunity to damage and deformations, and identification of conspecifics and friend/foe. Moreover, it may be possible to broaden the bandwidth, self-collimate over a wider range of angles, achieve stronger properties from low refractive index materials, and control light even more abruptly.
PHASE I: Investigate the transmission and reflection intensities of visible and near-IR light in random SVPCs with low index of refraction material. • Investigation of two types of lattices is desired: diamond and gyroid lattices with low index of refraction. • Perform material study to determine the range of indices of refraction closely resembling lattices in the insect world while achieving the expected functionality. • Investigate tuning mechanism(s) that allow the lattice to work in the visible and near-IR bands. • Full simulation of wave propagation and band-gaps using COMSOL, MEEP/MPB, or in-house developed software using open source languages. All codes and models are to be shared with AFRL. • Prototype fabrication of the lattice to test basic functionality in the lab in a given band: propagation around sharp bends and light focusing.
PHASE II: Fabricate and demonstrate several tunable lattices for each type (diamond and gyroid) and test in the visible and near-IR spectra • Tunability • Multiplexing • Light focusing • Propagation around sharp bends • Behavior of different polarizations of light • Controlled reflection and transmission • Controlled band gap structure
PHASE III: Fabricate multiplexing optical devices for fast and robust high bandwidth communication; Fabricate light funnels for investigating biological sensing. Other devices are feasible but are restricted to government projects and use not mentioned in this write up.
REFERENCES:1. Raymond C. Rumpf and Javier Pazos, "Synthesis of spatially variant lattices," Opt. Express20, 15263-15274 (2012); 2. Michielsen K, Stavenga D. Gyroid cuticular structures in butterfly wing scales: biological photonic crystals. Journal of the Royal Society Interface. 2008;5(18):85-94. doi:10.1098/rsif.2007.1065.; 3. Ingram A., Parker A. A review of the diversity and evolution of photonic structures in butterflies, incorporating the work of John Huxley (The Natural History Museum, London from 1961 to 1990). Philosophical Transactions of the Royal Society B: Biological Sciences. 2008;363(1502):2465-2480. doi:10.1098/rstb.2007.2258.; 4. Kuilong Yu, Tongxiang Fan, Shuai Lou, Di Zhang, Biomimetic optical materials: Integration of nature’s design for manipulation of light, Progress in Materials Science, Volume 58, Issue 6, July 2013, Pages 825-873
KEYWORDS: Photonic Crystals, Color From Structure, Self-collimating, Multiplexing Lattice
TECHNOLOGY AREA(S): Weapons
OBJECTIVE: Develop a hardware-in-the-loop simulator for future navigation concepts that use magnetic field anomaly sensors. Develop a magnetic field global database and physical field generator to include sensors in laboratory flight simulations of Air Force vehicles.
DESCRIPTION: Hardware-in-the-loop (HWIL) simulation is used to evaluate guidance, navigation, and control implementations in Air Force flight vehicles during their development. Navigation is critical in performing a mission that requires achieving a predetermined position, following a specific inertial flight path, or observing an object at a known location. While GPS allows for a vehicle to accurately navigate, if GPS cannot be relied upon, alternative means of navigation must be found. Supplements to navigation might use terrain maps, star and planet locations, optic flow, sky polarization, electro-magnetic mapping, and numerous other phenomena to bound the drift in pure inertial navigation solutions. Use of known maps of geographically varying magnetic field vectors, similar to using known maps of terrain features, has been proposed to augment conventional navigation approaches. It has been hypothesized that some animals accurately travel large distances augmented by sensors that detect variations in magnetic field strength. To investigate the potential benefit of this approach to the Air Force, replicating the Earth’s magnetic field variations in a hardware-in-the-loop facility is desired. Such a hardware-in-the-loop simulator currently does not exist. Availability would allow the Air Force to fly missions with integrated guidance, navigation, and control concepts in a ground test facility and assess the limitations of magnetic field mapping approaches with and without GPS. Magnetic field maps with varying levels of resolution exist and are publicly available. The highest definition maps maintained by the National Center for Environmental Information provide global information on geomagnetic anomalies. These maps include the geomagnetic main and crustal field, providing magnetic field values (total field, dip, and declination) at any point above or below the Earth's surface with a 28 km resolution. A constant challenge for HWIL testing is to ensure that the facility does not influence the results of the test through simulator errors or time delays introduced into closed-loop control systems. It is desired that the simulator exceeds the resolution of the sensor being testing and accuracy is sufficient to allow for repeatable test results. Geomagnetic sensor resolution is typically on the order of 100 uGauss. A study will need to be accomplished to determine simulator vector component accuracy requirements and dynamic range given expected earth field variations and sensor accuracy.
PHASE I: Perform an initial requirements study for the simulator. Engineer a conceptual design and establish a computational model of field resolution, uniformity, dynamic range, and accuracy. Acquire publicly available databases, design an architecture for database lookups, and document an interface protocol for facility simulation computers. Experimentally establish feasibility using a surrogate sensor.
PHASE II: Finalize the simulator design. Procure components sufficient to build a prototype of both the scene generation system and the magnetic field emulator. Establish and document the simulator calibration approach assuming know sensor characteristics. Work with government researchers to establish a set of verification test cases to compare digital truth vs. sensed time histories along simulated flight paths. Install the prototype simulator in the AFRL KHILS facility to enable Air Force research.
PHASE III: Work with prime DoD contractors to enhance the simulator to meet their requirements. Build final production simulators and transition to contractor facilities for support of internal research of alternate navigation methods. Integrate the simulator with other navigation simulators, e.g., celestial.
REFERENCES:1. M.J. Caruso, C. H. Smith, T. Bratland, R. Schneider, A New Perspective on Magnetic Field Sensing, Honeywell, 1998.; 2. Nair, M., A. Chulliat, A. Woods, P. Alken, B. Meyer and R. Saltus, New approach to quantify uncertainty for high-resolution magnetic reference models, Industry Steering Committee on Wellbore Survey Accuracy (ISCWSA) 45th meeting, March 17, 2017, The Ha; 3. Maus, S., M. C. Nair, B. Poedjono, S. Okewunmi, J. D. Fairhead, U. Barckhausen, P. R. Milligan, J. Matzka, High Definition Geomagnetic Models: A New Perspective for Improved Wellbore Positioning, IADC/SPE Drilling Conference and Exhibition, 6-8 March 2012, San Diego, California, USA, isbn: 978-1-61399-186-2, doi: 10.2118/151436-MS, March, 2012.; 4. Alken, P., A. Chulliat, M. Nair, B. Meyer, R. Saltus, A. Woods, N. Boneh, New advances in geomagnetic field modeling, Industry Steering Committee on Wellbore Survey Accuracy (ISCWSA) 44th meeting, September 22nd, 2016, Glasgow, Scotland.
KEYWORDS: Magnetic Anomaly Grid, High-definition Geomagnetic Field, Hardware-in-the-loop, Alternate Navigation, Scenario Generation, Flight Control
TECHNOLOGY AREA(S): Weapons
OBJECTIVE: Enable efficient development of mesoscale-informed high explosive reactive flow models using highly efficient numerical methods for use in system level simulations of Air Force weapons.
DESCRIPTION: Reliable employment of a weapon requires a firm understanding of the behavior of the explosive and its response to surrounding environment. The two primary concerns in the design of explosives for specific munition applications are 1) the reliability of explosive to detonate only when desired and 2) the controlled nature of the energy release during initiation and detonation. Sensitivity and energy release depends on a range of factors including but not limited to, meso-structural characteristics (void fraction, particle size and shape, binder fraction) of the explosive, age of the explosive, and the loading conditions (mechanical and thermal) of the explosive during handling, transport and storage. The effect of micro-structural features on initiation is currently a topic of interest to mesoscale modeling. An accurate reactive flow model is required to simulate explosive detonation. Reactive flow models may be developed by calibration to experimental data or by numerical simulation. Developing reactive flow models using numerical simulations requires large ensembles of 3D mesoscale simulations, and current mesoscale simulation codes require supercomputing level resources to build a model for a single explosive formulation. To increase the practicality of numerically developing accurate reactive flow models, significant improvements in computational efficiency are needed. This topic seeks strategies and implementations to achieve these efficiency gains, such as: 1) adaptive mesh refinement to focus computational effort around the regions of interest and 2) the use of high order numerical methods.
PHASE I: Develop a numerical strategy that addresses the tasks identified in the topic description, a plan for implementation in a simulation code, and a plan for comparison of the simulation code’s relevant metrics against other numerical methods. Demonstrate proof of concept of the modeling strategy on simplified test problems.
PHASE II: Implement the methodology from Phase I in a suitable simulation code. Deliver source code and documentation for the simulation tool. Demonstrate and document improvements achieved using these advanced numerical methods in the mesoscale simulation capability with problems of Air Force interest.
PHASE III: Further development and refinement of highly efficient numerical algorithms implemented in previous phases. Integrate into production-ready simulation tools and make available for commercial use. Develop and document efficient numerical algorithms to enable interoperability with widely-used commercial and research codes, if no such algorithms are available.
REFERENCES:1. Rai, Nirmal K., and H. S. Udaykumar. “Mesoscale Simulation of Reactive Pressed Energetic Materials under Shock Loading.” Journal of Applied Physics, vol. 118, no. 24, 2015; 2. A. Dubey, A. Almgren, J. Bell, M. Berzins, S. Brandt, G. Bryan, P. Colella, D. Graves, M. Lijewski, F. L. offler, B. O'Shea, E. Schnetter, B. V. Straalen, and K. Weide, A survey of high level frameworks in block-structured adaptive mesh refinement pac; 3. Zhang, X., and Shu, C-W. “Maximum-Principle-Satisfying and Positivity-Preserving High-Order Schemes for Conservation Laws: Survey and New Developments.” Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 467, no. 2134, 2011, pp. 2752–2776
KEYWORDS: Numerical Methods, High Order, Adaptive Mesh Refinement, Mesoscale Modeling, Simulation
Guided Automation of Molecular Beam Epitaxy for Swift Training to Optimize Performance (GAMESTOP) of New Materials
TECHNOLOGY AREA(S): Materials
OBJECTIVE: The objective of this topic is to reduce the time to optimize new thin film materials by coupling state of the art control schemes with in-situ characterization techniques. This topic is aimed at molecular beam epitaxy (MBE) growth, although similar approaches can be employed in other epitaxial growth processes.
DESCRIPTION: This topic is looking at combining recent developments in machine learning and optimization routines with novel in-situ characterization techniques to guide epitaxial growth for the rapid development of new materials. Molecular beam epitaxy is one of the most controllable deposition techniques producing the highest quality thin film materials. However the parameter space to optimize the material and thus the performance of an electronic or electro-optic device is extremely wide. Typically, the fluxes from each individual effusion cell, the substrate material and growth temperature are the key process variables effecting the growth rate and key material characteristics such as surface roughness, alloy composition, doping level, and radiative lifetime. Therefore, developing a new thin film material grown via MBE is a complex process involving many growths in which extensive characterization is used to determine the process/property correlations to produce an optimized material response. This topic is aimed at reducing the time to optimize new materials by coupling state of the art control schemes such as machine optimization, stimulated annealing algorithms, and neural nets to manage the MBE growth via in-situ characterization techniques allowing for the determination of doping, alloy composition, carrier mobility, etc. Obviously, the choice of characterization techniques will depend on the material/device characteristic to be optimized. As a minimum, composition, doping, substrate temperature and layer thickness should be measured/controlled. The machine learning may be performed using areal information or from sequential growths. Approaches will be evaluated on the rate at which they converge to the solution. Areal approaches will require imaging sensors and/or accurate models for the process variables and imaging sensors for the dependent material characteristics but potentially give vastly more information per growth than sequential growth approaches. Several key functionalities must be demonstrated in these proposals. First, a clear understanding of which and what types of sensors can be used in the MBE process should be demonstrated and why they are important in optimization. Optimization routines must be able to handle multiple sensor inputs as well as provide feedback providing closed loop control between growth parameters and relevant characteristics. This includes trade-off in properties such as mobility and carrier concentration. For instance, a device with the best mobility and the highest carrier concentration would be ideal, however as carrier concentration goes up the mobility goes down, so there is an optimum solution. Also, optimization routines must be able to search for global minimum in a multiple dimension growth parameter space which may contain local minima. Offerors should estimate convergence rates and discuss how the situations used to obtain these estimates are similar to the MBE process in terms of complexity
PHASE I: With the complexity of the MBE process, there exists different levels of properties/parameters, some basic (Level 1) such as material thickness, composition, surface roughness, etc. that are easier to characterize in-situ and have direct correlation to end device performance. Then there are more specific properties/parameters (Level 2) such as material interface properties, mobility, carrier or sheet concentration and carrier lifetimes that are more difficult to determine in-situ, but greatly influence overall device performance. In Phase I it is desired that control and optimization of at least all Level 1 properties be performed. Offerors must specify material systems which they have access to. At a minimum this should include an InAlGaAs based system. Optimization of initial parameters must be demonstrated in a region of process space to be defined. The exact problem to be optimized will be specified after Phase I is awarded. This approach is being used to allow a fair evaluation of progress and development potential of the different learning and measurement suites being used at the conclusion of Phase I. Ex-situ measurements will be allowed in Phase I but a clear path must be demonstrated for implementation of the sensors and measurements in the system to allow in-situ measurements with similar accuracy during Phase II. The success of the learning algorithm will be determined by the number of growths needed to reach the optimized conditions.
PHASE II: The Phase II effort will integrate the in-situ sensors into the system and perform/demonstrate further optimization. Final device characteristics will be optimized during Phase II and an overall system with sensors will be developed. A marketing plan will be developed
PHASE III: In Phase III the system will be commercialized and marketed. Additional capabilities will be added based upon the needs/desires of potential end users.
REFERENCES:1. “Molecular Beam Epitaxy: Fundamentals and Current Status”, M. A. Herman and H. Sitter, Springer Series in Material Science 7, Springer Verlag; 2. “Materials Fundamentals of Molecular Beam Epitaxy”, Jeffery Tsao, Academic Press; 3. Pavel Nikolaev, Daylond Hooper, Frederick Webber, Rahul Rao, Kevin Decker, Michael Krein, Jason Poleski, Rick Barto & Benji Maruyama, “Autonomy in materials research: a case study in carbon nanotube growth”, Computational Materials Volume 2, Article number: 16031 (2016).; 4. Yue Liu , Tianlu Zhao , Wangwei Ju , Siqi Shi , “Materials discovery and design using machine learning”, Journal of Materiomics, Volume 3, Issue 3, September 2017, Pages 159-177.
KEYWORDS: Molecular Beam Epitaxy (MBE) Growth, Thin Film Materials
TECHNOLOGY AREA(S): Materials
OBJECTIVE: Develop, demonstrate and validate a processing model to predict the physical and mechanical properties of structural carbon-carbon materials for aeroshells. Compatibility with industry standard design and modeling software is anticipated.
DESCRIPTION: The US Air Force has a need for improved understanding and modeling of processes used to manufacture structural carbon-carbon (C-C) materials used in hypersonic aeroshells. At least for short durations, C-C has the capability to withstand very high temperatures while maintaining structural integrity. Even though these materials have been used for decades, their manufacturing (mfg) processes are still a craft. In addition, the effects of variations in the starting materials and processing conditions are largely unknown. Over the years, some starting materials have become obsolete and the effects of changing these materials even slightly are unpredictable. Therefore, every time a new process or starting material is contemplated for use on a DoD weapon system, a new property database must be generated. In addition, physics-based prediction of the capability of new processes to create high quality materials and structures does not exist. Improved understanding and modeling of the manufacturing processes used to make C-C composites is anticipated to lead to improved properties, increased process repeatability, as well as reduced manufacturing and qualification costs and decreased manufacturing times. The C-C processing model may be empirical (physics- and chemistry-based), analytical, numerical, or a combination, but should, to the degree possible, reflect the underlying physics and chemistry of the system. The starting materials and their physical configuration (i.e. prepreg, 3-D woven preform, etc.), component geometry, processing methods and parameters (temperature, pressure, etc.), and other relevant factors should be taken into consideration. Two of the most widely-used commercial processing methods to make structural C-C should be included in the model under this effort. The resulting processing model should accurately predict final component geometry, density, mechanical and physical properties, and variations within the component. The model/modeling architecture should be flexible enough to incorporate new processes and/or customization of current processes in the future. Geometry and other relevant information should be able to be easily imported into the model, and results should be able to be exported to existing design and analysis software (i.e. FEM software) commonly used in the aerospace industry. The model should run in a reasonable period of time to allow multiple analyses so that the optimum processes can be selected for a given part geometry and starting material. In Phase I, the model should focus on a simple flat panel geometry with a single fiber geometry. In Phase II, the model shall demonstrate that it can accurately predict the properties of an additional, more complex geometry component with a variation in cross section. In addition, the model’s flexibility shall be demonstrated by modeling an additional, more complex fiber geometry. The contractor shall perform validation and verification (V&V) of the model. To aid in transitioning the model for use by industry, it is anticipated that the model may be offered in the future as a module or add-on to currently available commercial-of-the-shelf (COTS) modeling software. The contractor should keep technology transition in mind as the model is created to help ensure successful transition.
PHASE I: Perform a requirements analysis and create a document specifying all of the functionality that should be included in the C-C processing model. Obtain data and background information needed to create the model. Demonstrate the feasibility of a C-C process modeling concept for at least one C-C material system and process. Perform V&V of the Phase I model.
PHASE II: Refine the modeling approach defined in Phase I. Create C-C processing model for an additional C-C mfg process, a more complex geometry, and a more complex fiber architecture. Incorporate effects of defects & variability. Demonstrate ability to predict material properties based on process nominal values. Demonstrate sensitivity of predictions to manufacturing parameter input variability. Perform model V&V. Determine interoperability with industry standard design and analysis software.
PHASE III: Finalize model refinement & validation. Develop appropriate technology transition strategies that focus on commercialization of the developed modeling tools. Develop a business strategy that ensures the software can continue to be upgraded as new information and modeling techniques become available.
REFERENCES:1. Vignoles, Gerard L., et al., “Analytical stability study of the densification front in carbon-or ceramic-matrix composites processing by TG-CVI,” Chemical Engineering Science, vol. 62, no. 22, pp. 6081-6089, Nov 2007.; 2. Ravikumar, N.L., et al., “Numerical simulation of the degradation behavior of the phenolic resin matrix during the production of carbon/carbon composites,” Fullerenes, Nanotubes and Carbon Nanostructures, vol. 19, No. 5, pp. 353-372, Jul 2011.; 3. Dietrich, S., et al., “Microstructure characterization of CVI-densified carbon/carbon composites with various fiber distributions,” Composites Science and Technology, vol. 72, no. 15, pp. 1892-1900, 2012.
KEYWORDS: Carbon-Carbon Composites; Process Modeling;
TECHNOLOGY AREA(S): Bio Medical
OBJECTIVE: Develop and demonstrate a low-cost, portable blood coagulation sensor that can measure a patient’s coagulation status and the factors influencing it in near real time (less than 10 minutes).
DESCRIPTION: Bleeding and clotting disorders caused by coagulation defects (coagulopathy) are implicated in about 80% of deaths in the operating room and about 50% of trauma-related deaths [ref. 1]. A high priority military capability gap has thus been recognized to be able to immediately recognize and correct coagulopathy [ref. 2]. Impaired coagulation can lead to uncontrolled hemorrhage, or may cause increased clotting resulting in deep vein thrombosis, pulmonary embolism or stroke. Depending on the type of coagulation defect, bleeding disorders are treated by transfusing red blood cells, platelets or factor concentrates, and thrombosis risk is managed with injectable or oral anticoagulants. Since, each coagulation defect necessitates distinct interventions, the prompt and frequent monitoring of the underlying defect is essential. Current point-of-care devices only measure clotting time; therefore, additional laboratory tests are required for quantifying clot formation rate, clot strength, fibrinogen levels, fibrinolysis, and platelet function to reveal the underlying coagulation impairment. Mechanical devices based on viscosity measurements (TEG, ROTEM) do better, and have become used more often during surgeries, but these devices, while of value, require a fixed, vibration isolated environment, and are large, expensive, require expertise in sample preparation and use (recent advances, less so), and are not as fast as desirable. Several companies are working toward developing devices aimed at measuring blood analytes relevant to coagulopathy of trauma, under a previous SBIR topic, DHP15-012, “Real-Time Small-Volume Blood Sampling and Analysis for Coagulopathy of Trauma Analytes”. These, if commercialized, would give valuable information (and would likely have applicability beyond coagulopathy), but likely would still be unable to give a full picture of individualized coagulation defects to guide individualized treatment. The objective of this topic is therefore to develop and demonstrate a commercially viable system which can measure clotting time as well as the factors which a mechanical system can measure, but in an easily portable point-of-care system (goal of less than one pound), which is easy to use, and which can give results in a much shorter time (less than 10 minutes), noninvasively or with a very small blood draw (goal of 25μl or less, enabling multichannel analysis). By enabling comprehensive profiling of blood coagulation in minutes at the operating table, at the bedside, or in the field, the desired system will advance clinical capability to treat patients with impaired coagulation, assess risk for hemorrhage and thrombosis, tailor and monitor treatment based on individual coagulation deficits and improve blood resource management.
PHASE I: Identify or develop a concept for a small, portable point of care coagulopathy diagnostic, capable of measuring clotting time and clotting strength, and quantitatively identifying the factors causing clotting defects and guiding treatment, in a short time (less than 10 minutes). Build at least a laboratory prototype and show its performance on volunteers and on stored blood samples, if applicable. Compare the results to standard testing protocols, including on mechanical testing devices. Describe a phase II plan for developing portable devices and demonstrating their use at point-of care. Devices based on laser scattering have been demonstrated at academic institutions [refs. 3, 4], which might be a basis for meeting the topic objective, but any promising concept will be considered. Other possibilities might include, for example, augmenting existing devices with a bio-MEMS (Micro-Electro-Mechanical Systems) component.
PHASE II: Produce prototype hardware, based on Phase I work, which could form the basis for later phase commercialization. Gather appropriate test data to validate the prototype designs. Such data could include multiple measurements on stored human blood samples (under exemption conditions established by the U.S. Army Medical Research and Materiel Command (MRMC) Human Research Protection Office (HRPO), showing diagnostic accuracy in comparison with current mechanical devices, potentially animal testing, and potentially human data obtained through the nonsignificant risk device investigational device exemption (IDE), with local IRB approval, and meeting the requirements of MRMC HRPO. Plan to demonstrate the prototype hardware in operation to relevant DOD medical personnel along the way, and incorporate suggestions to improve the final product. Develop and deliver, in Phase II, a plan to engage with the FDA on the topic device in phase III. Develop and validate potential phase III designs for commercialization, reflecting the FDA plan deliverable.
PHASE III: Were a Phase III effort on this topic to be successful, there could be multiple pathways to military and dual use civilian commercialization. In trauma care, commercialization would provide greatly improved management of surgical and trauma patients, allowing clinicians to determine whether blood loss is due to surgical causes or coagulopathy, an otherwise major challenge. A commercial technology would enable individualized blood transfusion and anti-thrombotic therapy, allowing tailoring of therapy based on the actual needs of each patient, reducing the risks of inappropriate transfusion or anti-thrombotic therapy [ref. 5]. A successful commercialization would result in improved blood resource management and reduced health care costs, by providing better guidance as to when and how to blood transfuse. The topic sought capability would also enhance hospital blood transfusion practices, optimize blood resource utilization and reduce side-effects from over-transfusion. A very great contribution of a successful commercialization would be oral anticoagulation (blood thinner) management. Blood thinners are used often for periods after surgery and over a lifetime for many procedures. Over 15 million people worldwide receive oral anticoagulants to prevent venous and arterial thrombosis. Use of these requires very frequent monitoring to be sure a narrow therapeutic window is achieved – too much can cause hemorrhage and too little dangerous blood clots. Blood thinners, in themselves, are responsible for a large loss of life in the U. S. and worldwide. The topic capability would allow for frequent, inexpensive-point-of-care measurement in the home, together with the possibility of notifying medical help for anomalies, using standard communication protocols.
1: Hoyt DB, Bulger EM, Knudson Mea. Death in the operating room: An analysis of a multi-center experience. The Journal of trauma. 1994
2: 37:426-432 (https://journals.lww.com/jtrauma/Citation/1994/09000/DEATH_IN_THE_OPERATING_ROOM__AN_ANALYSIS_OF_A.16.aspx)
3: U.S. Department of Defense – Military Health System (MHS), Capability Gap Closure Analysis 2015 (https://ccc.amedd.army.mil/ScientificPapers/2015%20Combat%20Casualty%20Care%20Research%20Program%20Capability%20Gap%20Closure%20Analysis.pdf)
4: Hajjarian, Z., Tripathi, M.M. & Nadkarni, S.K. Optical Thromboelastography to evaluate whole blood coagulation. J Biophotonics 8, 372-381 (2015) (https:doi:10.1002/jbio.201300197)
5: J. R. Guzman-Sepulveda, J. R., DeCampli, W. M., and Dogariu A., Intraoperative Assessment of Blood Coagulability using Coherence-gated Light Scattering, Biophotonics Congress: Biomedical Optics Congress 2018, OSA Technical Digest, paper CW4B.5, (https://doi.org/10.1364/Translational.2018.CW4B.5)
6: Schochl H, Maegele M, Solomon C, Gorlinger K, Voelckel W. Early and individualized goal-directed therapy for trauma-induced coagulopathy. Scand J Trauma Resusc Emerg Med. 2012
7: 20:15 ( https:doi:10.1186/1757-7241-20-15)
KEYWORDS: Trauma, Coagulopathy, Thrombosis, Blood Thinners, Surgical Induced Coagulopathy, Coagulopathy Induced Hemorrhage, Coagulation Diagnostic
TECHNOLOGY AREA(S): Weapons
OBJECTIVE: Develop a compact, highly efficient high-power microwave (HPM) L-band and S-band source with hardened subsystems and tubes to enable the Radiofrequency- High-Power Microwave (RF-HPM) system to produce sufficient directed energy to stop vehicle and vessels engines.
DESCRIPTION: This STTR topic is seeking to develop two sets of compact, robust/mobile, highly efficient multiple or single frequency and waveform agile HPM source designs. One of these HPM sources will operate in the L-Band frequency range (0.5 to 1.5 GHz), and the other in the S-Band frequency range (2.0 to 4.0 GHz). Waveforms in these two frequency bands, at sufficient Effective Radiated Power (ERP) at the target, have proven to be effective counter-electronic HPM directed energy weapons, which interfere with the electronics on-board vehicle and vessel engines in such a way as to stall/stop these engines. Therefore, these HPM weapons have military utility for RF Vehicle Stopping, RF Vessel Stopping, and neutralization of other relevant targets where electronics are on board. The final system design should be optimized for long range vehicle and/or vessel engine stopping, with or without waveform agility (multiple frequencies). The final system design should also be optimally driven and designed to produce higher overall system output power that’s greater than conventional HPM sources (> 30MW for L-Band and > 10 MW for S-band sources) in the same or smaller overall form-factor (SWAP/C2) as conventional HPM sources. These final designs, can also result in two separate optimized HPM systems (i.e., one in the L-Band and one in the S-Band) or a single multi-frequency (short or long pulse), with pulse repetition rate of 100 - 300 Hz. [Ref 2]. This STTR topic’s concept and follow-on prototype seek to increase the peak power out of a new HPM (e.g., magnetron) tubes designs, and increase waveform/frequency agility in order to stop vehicle and vessel engines at greater ranges via HPM counter-electronic effects on the targeted engines while maintaining current conventional HPM System MTBF. As this is a directed energy weapon system, the design shall project a collimated/focused beam of HPM energy on to the target with an effective spot-size and with a real-time agile gimballed system and a low-light level/thermal imaging weapon sight be able to “acquire” the target and then be able to “hit the target” and keep the HPM energy on a moving vehicle or vessel target. This HPM energy with an effective “power on target” shall neutralize vehicle and vessel engines and by keeping this energy on the targets, be able to keep the vehicle engines stopped. This “hold down” capability shall not exceed the safe permissible exposure limits (PEL) as established by DoD Instruction 6055.11 [Ref 3]. The proposed system will integrate this single or multiple frequency HPM source into a small compact form-factor (see performance specifications provided below). These higher power HPM sources and their associated peripheral systems will include the following capabilities/performance specifications: 1. A compact RF-HPM source design with a minimum ERP of 30-40 MW in L-Band and 10-15 MW in S-Band 2. An effective vehicle stopping ranges in excess of 300 meters and an effective vessel stopping range of 100 meters 3. Pulse widths from short pulse widths of tens of nanoseconds at pulse repetition rates of greater that 150 Hz to long pulse widths of 100s of microseconds at pulse repetition rates of greater than 100 Hz 4. An overall system size and weight, with the antennas, under 150 ft3 and 3000 lbs (at 30-40 MW) in L-band and 25 ft3 and 750 lbs (at 10-15 MW) in S-band 5. Beam spot-size with an effective “power on target” shall be no larger than1/2 the width of the target at range. 6. RF-HPM source design with higher system output power with system mean-time-between-failures (MTBF) of > 3000 hours (commensurate with current L and S-band HPM sources) 7. Power consumption shall be optimized for overall system SWAP/C2 and can be supplied by compact gas generators, batteries, or via a hybrid generator/battery system.
PHASE I: Develop a conceptual design for an optimized set of HPM Vehicle and Vessel Stoppers that operate in either the L or S-Bands or both and meet or exceed the design performance specifications in the Description. Determine the technical feasibility of the concept design and model key elements that can be developed into a useful product for the Marine Corps through analytical modeling and simulation to provide initial assessments of the concept performance. Provide a Phase II development plan with performance goals and key technical milestones, and that addresses technical risk reduction as well as military suitability issues, such as overall system size, weight, power consumption, thermal cooling, and system cost.
PHASE II: Develop a full-scale vehicle and/or vessel stopper prototype that can be employed from a conventional DoD small tactical vehicle such as Joint Light Tactical Vehicle (JLTV or a Medium Tactical Vehicle Replacement (MTVR). Evaluate the prototype to determine its capability in meeting the performance goals defined in the Phase II development plan. Demonstrate system performance through prototype evaluation and modeling or analytical methods over the required range of parameters mentioned in the Description, including numerous deployment cycles. Use evaluation results to refine the prototype into an initial design that will meet Marine Corps requirements. Prepare a Phase III development plan to transition the technology to Marine Corps use.
PHASE III: Support the Marine Corps in transitioning the technology for Joint Service and Marine Corps use. Develop additional RF-HPM Vehicle and Vessel Stopper prototype demonstrators, optimized for additional small tactical DoD platforms to include other small military vehicles, vessels, and unmanned systems. Evaluate and determine each design’s operational effectiveness and added capabilities achieved in an operationally relevant environment. Support the Joint Non-Lethal Weapons Directorate (JNLWD)/Marine Corps for test and validation to certify and qualify the system for Joint Service to include Marine Corps use. Vehicle and vessel stopping operational needs are common to many other U.S government agencies as well as for civilian law enforcement such as the Department of Homeland Security (DHS) (specifically Secret Service and Customs and Border Protection), Department of State (DoS), Department of Justice (DoJ),)—all of which desire this long-range capability [Ref 1]. This need has strengthened recently given the weaponization of vehicles by terrorist organizations and groups. The ability to non-lethally interdict a threatening incoming vehicle and/or vessel has utility in many security checkpoint and crowd control applications to include several municipal applications.
1: "Joint Operating Environment 2035." DoD Joint Staff
2: dated 2016. (Uploaded to SITIS on 11/28/2018)
3: Current NSWC-Dahlgren RF-HPM Vehicle Stopper Design Brief, 2017. (Uploaded to SITIS on 11/28/2018)
4: 3. DoD Instruction 6055.11. "Protecting Personnel from Electromagnetic Fields". Change 1, 10/10/2017. http://www.esd.whs.mil/Portals/54/Documents/DD/issuances/dodi/605511p.pdf?ve
KEYWORDS: High Power Microwaves; Radio Frequency; Directed Energy; Vehicle Stopping; Vessel Stopping; Non-Lethal Weapons
TECHNOLOGY AREA(S): Air Platform, Electronics, Battlespace
OBJECTIVE: Augment traditional first order logic sensor resource management approaches by employing Bayesian inference approaches that leverage information that is accumulated over a surveillance mission in a confined area of interest.
DESCRIPTION: Recent advances [Ref 3] in machine learning (ML), deep learning (DL), and other artificial intelligence (AI) techniques have shown great promise in delivering significant improvement in radar system performance for both surveillance (detection and tracking) and imaging functions. So-called “cognitive” systems seek to combine the optimization of sensor resources and capabilities with ML and data mining techniques to provide an autonomous system that, given a high-level descriptor (e.g., mission plan, Operational Situation/Tactical Situation (OPSIT/TACSIT)), will automatically adjudicate the target environment and provide human operators with actionable information or even take certain actions on its own (e.g., modification of platform flight pattern) in response to what has been learned. The objective is to develop a software-based system, prototyped in MATLAB with the final product in Java, that can make any given radar system “cognitive” by automatically understanding its native hardware capabilities and executing the most appropriate radar function at any given moment in the operational timeline in response to dynamic in-situ conditions present in a typical Navy maritime surveillance environment. Bayesian inference is a strong basis for this application as learning or experience can be used to update the probability for a hypothesis that is guiding radar tasking. Many of the Navy maritime surveillance missions involve surveilling the same geographical area over a mission or across multiple missions. Such operations offer the opportunity to significantly enhance mission success through learning-based resource management. Clearly demonstrating how the proposed approach enhances performance beyond that possible from first order logic expert driven approaches and how the proposed approach is trained and maintained are considered critical.
PHASE I: Complete a top-level design and demonstrate the feasibility of its approach to improve sensor utilization using Bayesian inference as an addition to first order logic approaches in sensor resource management. In order to facilitate the analysis, the sensor suite may be limited to radar only but the approach should be easily expandable to other Navy sensor systems such as electro-optic/infrared (EO/IR) and electronic support measures (ESM). Perform an analysis that assumes operation of the airborne sensor system is in a geographically constrained operational area with multiple revisits over the course of a mission. Operational maritime environment information will be provided by the Navy. The Phase I effort will include prototype plans to be developed under Phase II.
PHASE II: Develop a prototype system based upon the Phase I design to provide and demonstrate that legacy radar systems can be modified to provide the improved timeline utilization and mission success. Perform performance assessments quantifying vessel tracking, track maintenance, and imaging using target layouts and behaviors representative of operational maritime environments provided by the Navy. Deliver a detailed report and prototype system.
PHASE III: Complete development, perform final testing, and integrate and transition the final solution to Naval airborne maritime surveillance platforms. The high-level control logic to be utilized here is applicable to a wide range of applications including law enforcement and border control surveillance operations.
REFERENCES:1. Guerci, J. Cognitive Radar: The Knowledge-Aided Fully Adapted Approach. Boston: Artech House, 2010. http://www.gbv.de/dms/ilmenau/toc/629620326.PDF; 2. Haykin, S. Cognitive Dynamics Systems: Radar, Control, and Radio. Canada: Cambridge University Press, 2012. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6218166; 3. Abad, R. et.al. “Basic Understanding of Cognitive Radar.” IEEE ANDESCON, 19-21 October 2016. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7836270
KEYWORDS: Sensor Resource Management; Maritime Surveillance; Artificial Intelligence; Machine Learning; Command And Control; Cognition
TECHNOLOGY AREA(S): Air Platform, Materials
OBJECTIVE: Develop and demonstrate innovations in tailoring ply interfaces to improve damage tolerance and durability of rotorcraft components.
DESCRIPTION: Composites offer unique opportunities for designing rotorcraft components that are not offered by traditional monolithic materials. In addition to structural efficiency, composites also offer improved fatigue resistance than metal and superior resistance to environmental effects. However, composite fabrication design and fabrication are more challenging, especially for high-performance designs involving interfaces of multiple material systems (e.g., glass/epoxy and carbon/epoxy in the same component). Interlaminar failure often dictates the design. Ply drop-offs are usually the location of damage initiation sites. If more than one composite system is used (e.g., carbon/epoxy with glass/epoxy), the interface between the two systems is a weak point and a potential site for damage initiation. These areas often have sharp strain gradients and/or residual thermal stresses due to Coefficient of Thermal Expansion (CTE) mismatch. Tailoring the interface between adjacent plies by using techniques such as nano-stitching or by embedding graphene sheets has the potential of improving damage resistance by moving the damage to a lower-strain area. Nano tubes and graphene sheets are given only as an example; any non-nano solution will also be considered. Although it is not required, it is recommended that the small businesses work with the original equipment manufacturers (OEMs) to ease future transition.
PHASE I: Define and develop a concept to use interface tailoring and demonstrate feasibility at a coupon level. It is recommended that the feasibility be demonstrated by qualitative and mechanical testing. Suggested ASTM standards for testing include D2344, D0339, and D5379. The tests are not mandatory and the offerors can propose tests best suited for their solution. The Phase I effort will include prototype plans to be developed under Phase II.
PHASE II: Using results from Phase I, prove the concept at a component level such as a rotorcraft component that sees complex out of plane loads and is prone to delamination in a lab or live environment. Potential component includes but not limited to rotorcraft flex-beams, composite cuff and yoke. Refer to JSSG-2006 [Ref 1] for general requirements for Navy structures.
PHASE III: Mature the technology for possible insertion in Future Vertical Lift (FVL). Concurrently, it is recommended that the proposer work with an existing OEM for potential transition to an existing platform. The cost pressures in commercial aviation are even more constrained than in military aviation. Commercial aviation is also leading the way in replacing metallic airframe structures with composites. Thus, the technology will be highly applicable to commercial aviation for reducing production costs.
REFERENCES:1. JSSG-2006, Department of Defense Joint Service Specification Guide: Aircraft Structures, 30 October 1998. http://everyspec.com/USAF/USAF-General/JSSG-2006_10206/; 2. “NanoStitch.” n12 Technologies, Cambridge, MA. https://www.compositesworld.com/cdn/cms/FM2016-N12-NanoStitch.pdf; 3. ASTM D5379 / D5379M - 2. “Standard Test Method for Shear Properties of Composite Materials by the V-Notched Beam Method.” West Conshohocken: ASTM International, 2018. https://www.astm.org/Standards/D5379; 4. ASTM D2344 / D2344M - 16. “Standard Test Method For Short-Beam Strength of Polymer Matrix Composite Materials and Their Laminates.” West Conshohocken: ASTM International, 2018. https://www.astm.org/Standards/D2344; 5. ASTM D3039 / D3039M - 17. “Standard Test Method For Tensile Properties of Polymer Matrix Composite Materials.” West Conshohocken: ASTM International, 2018. https://www.astm.org/Standards/D3039; 6. Villoria, R., Hallander, P., Ydrefors, L., Nordin, P., and Wardle, B. “In-plane Strength Enhancement of Laminated Composites Via Aligned Carbon Nanotube Interlaminar Reinforcement.” Composites Science and Technology, 2016, pp. 33-39. https://www.sciencedirect.com/science/article/pii/S026635381630687X
KEYWORDS: Composites Design; Composites Manufacturing; Interfacial Reinforcement; Damage Tolerant; Ply Drop-Off; Rotorcraft Component
TECHNOLOGY AREA(S): Air Platform
OBJECTIVE: Develop an optimized fabrication process for quantum cascade lasers (QCLs), such as facet passivation and high thermal conductivity coatings, in order to mitigate the impact of the QCL’s operating lifetime due to catastrophic optical damage (COD).
DESCRIPTION: Employment of high-power QCLs for aircraft protection against shoulder-fired heat-seeking missiles is among the most critical applications for these devices. The ongoing Common Infrared Countermeasures (CIRCM) program represents the first program of record for the QCL technology. The program puts QCLs on the path toward wide acceptance in DoD applications. CIRCM is focused on the development of, and transition to, a large throughput production of a compact and lightweight QCL-based Directed Infrared Counter Measure (DIRCM) system, capable of addressing the threats posed to rotary wing aircraft by the proliferation of the Man-portable air defense system (MANPADs). A relatively low (conservative) continuous wave optical power on the order of 1W is targeted in this program. However, a higher optical power, exceeding 5W for a single emitter, would significantly improve system characteristics. The maximum optical power level for state-of-the-art QCLs is primarily limited by COD of the output laser facet: QCLs tend to fail at optical power densities on the order of 10MW/cm2, which roughly corresponds to total power level of 3W for narrow-ridge (10micron-wide) devices. Despite the fact that QCLs are projected to be the cornerstone of a number of next generation infrared systems for various DoD applications, COD failure mechanisms have not been studied for these devices. The lack of reliable experimental data on laser failure and the absence of a practical COD model make it impossible to properly evaluate mean time between failure (MTBF) for future infrared products comprising QCLs. Preliminary QCL COD elevations [Ref 1] show that the two most typical failure scenarios for high-power buried-heterostructure QCLs mounted epi-down on submounts with a high thermal conductivity are: (1) Rapid degradation (on a scale of microseconds) in laser performance occurs when optical power density at the output facet significantly exceeds 10MW/cm2. Output facet inspection in this case shows a significant damage with a drop of melted material often observed near the active region area. The inspection results suggest that, similar to short-wave infrared diode lasers, the QCL damage occurs due to a thermal runaway process that results in the active region material melting, an irreversible damage to the laser. The positive feedback loop responsible for the QCL rapid degradation has never been clarified for QCLs and there is no active research being carried out to increase the COD threshold and, therefore, increase optical power level for traditional Fabry-Perot emitters. (2) For a lower power level, in the range from 5 to 10MW/cm2, hermetically packaged QCLs can reliably operate for >1,000h [Ref 2]. However, eventually they still catastrophically fail. The most likely explanation for the failure is device aging accompanied by defect diffusion to the output facet at elevated temperatures, which in turn lowers COD threshold. Again, the natures of the defects, time-scale for their development, and conditions that influence their formation have never been studied for QCLs. Therefore, it is the goal of this topic to develop optimum fabrication processes, such as facet passivation and high thermal conductivity coatings that will mitigate the aforementioned reliability issues.
PHASE I: Design and demonstrate feasibility of a model capable of identifying the positive feedback loop responsible for the thermal runaway in QCLs, describing the rapid output facet degradation, and determining the COD threshold for typical edge emitting QCLs. The model development will require fitting to thermal and time-resolved optical experimental data. The Phase I effort will include prototype plans to be developed under Phase II.
PHASE II: Develop a prototype fabrication process employing the model designed in Phase I. Perform experimental data collection to refine the model via study of immediate (microsecond scale) damage at high power level, long term degradation, and defects formation analysis. Based upon the improved device model, develop QCLs with increased COD threshold (higher power single emitters) and estimate MTBF for various operational conditions.
PHASE III: Develop a cost-effective process for manufacturing high-reliability QCLs that are to be transitioned and integrated into DIRCM systems for field deployment in a Navy platform. Commercialize the technology based on the reliability evaluations from this program for law enforcement, marine navigation, commercial aviation enhanced vision, medical applications, and industrial manufacturing processing.
REFERENCES:1. Lyakh, A., Maulini, R., Tsekoun, A., Go, R., and Patel, C.K.N. “Tapered 4.7µm quantum cascade lasers with highly strained active region composition delivering over 4.5 watts of continuous wave optical power.” Optics Express, 2012, Vol. 20, Issue 4, pp. 4382-4388. https://doi.org/10.1364/OE.20.004382; 2. Miftakhutdinov, D., Bogatov, A., and Drakin, A. “Catastrophic optical degradation of the output facet of high-power single-transverse-mode diode lasers.” Quantum Electronics, Vol 40, No 7, 2010. http://iopscience.iop.org/article/10.1070/QE2010v040n07ABEH014340; 3. Hu, Y., Wang, L., Zhang, J., Li, L., Liu, J., Liu, F., and Wang, Z. “Facet temperature distribution of a room temperature continuous-wave operating quantum cascade laser.” Journal of Physics D: Applied Physics, Vol 45, No 32, 15 August 2012. http://iopscience.iop.org/article/10.1088/0022-3727/45/32/325103; 4. MIL-STD-810G, Department of Defense Test Method Standard for Environmental Engineering Considerations and Laboratory Tests. United States Department of Defense. 31 October 2008. http://everyspec.com/MIL-STD/MIL-STD-0800-0899/MIL-STD-810G_12306/
KEYWORDS: QCL; Wall-Plug Efficiency; Thermal Load; Scaling; MWIR; Brightness
TECHNOLOGY AREA(S): Sensors, Electronics, Battlespace
OBJECTIVE: Develop and demonstrate an array of quantum cascade lasers with integral (chip-level) wavelength beam combining.
DESCRIPTION: Many threats to surface ships employ infrared (IR) imagers and detectors. These include lethal threats such as anti-ship cruise missiles as well as aircraft and unmanned aerial systems performing routine surveillance. In all cases, shipboard countermeasures are needed and lasers are a fundamental component of any electro-optic/infrared (EO/IR) countermeasure suite. For compactness and simplified power and control circuitry, semiconductor lasers are a highly attractive solution. However, in order to achieve the output powers required, multiple individual laser diodes must be combined in a laser “module” with a single output. This represents a considerable cost in manufacturing as the exacting tolerances required result in high component costs and labor-intensive assembly processes. The assembly cost of the laser diode combiner accounts for as much as half the cost of the finished laser module alone. The quantum cascade laser (QCL) has demonstrated attractive qualities that make it particularly well suited to wavelength beam combining (WBC). Wavelength beam combined QCL designs have been demonstrated as feasible in achieving acceptable output power [Ref 2, 3, 4], although the resulting laser modules are expensive. This cost can only be reduced through implementation of automated assembly processes and through higher levels of integration at the component level. Since the QCL is a solid-state device produced by the accustomed semiconductor fabrication processes, it seems logical that higher levels of integration can be applied to reduce cost, consistent with common experience across the electronics industry. The Navy requires a technology that lowers the cost of laser modules by combining multiple QCLs and integrating the wavelength beam combining structure on the semiconductor chip (on-chip). The wavelengths of interest lie primarily in the mid-wave infrared (MWIR) wave band (3.7-4.8 µm specifically). However, the long-wave infrared (LWIR) wave band (7.8-11.5 µm) is also of interest and the technology may be demonstrated in whichever wave band is deemed the easiest to demonstrate the proposed technology. While on-chip coherent laser combining in the near-IR has been demonstrated, coherent combining is not acceptable for this effort. However, the quality of the combined output beam is highly important. It is desired that the beam exhibit nearly diffraction limited operation with M2 factor, as defined by ISO Standard 11146, of 2.0 being the minimum and M2 factor of 1.5 or less being the goal. The overall loss in the combining structure is of great importance, as it is the demonstration of efficient on-chip combining that is the goal of this effort. For this purpose, a single QCL output power of 500 mW (minimum at room temperature) with device efficiency of 8% is considered achievable in the MWIR band. In the LWIR band, a single QCL power of 200 mW and efficiency of 5% is considered reasonable. Therefore, the combining structure should be realized in a semiconductor family suited to QCL fabrication (such as InGaAs/InAlAs quantum wells on an indium phosphide (InP) substrate or an InP-based epilayer integrated with silicon) and the individual QCLs in the device must ultimately achieve these power levels. The power handling capability of the combining structure must therefore anticipate the combination of power from an integrated array of such QCLs. For this effort, demonstration of on-chip combining of a five QCL array is considered the minimum goal and the ability to combine up to 20 devices is highly desirable. The combining efficiency (combined optical power out divided by the sum of the power produced by the QCLs) [Ref 2, 3, 4] should be made as high as possible with a goal of 80%. Furthermore, even though coherent combining is not wanted, each individual QCL operating wavelength must be fixed and repeatable (from device to device) within the operating band. For wavelength beam combining, each QCL in the array must operate at a different wavelength that is determined by the optical path. Therefore, the combining structure (or some other structure integrated on the chip) must enable the wavelengths of the individual QCLs to be selected during design.
PHASE I: Propose a concept for an on-chip wavelength beam combined QCL array meeting the objectives and performance parameters detailed in the Description. Demonstrate feasibility by a combination of analysis, modelling, and simulation. Include in the feasibility analysis predictions of combining efficiency and output beam quality as a function of the number of individual QCLs in the array. Develop a Phase II plan. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a prototype solution in Phase II.
PHASE II: Based on the results of Phase I and the Phase II Statement of Work (SOW), demonstrate the concept for an on-chip wavelength beam combined QCL array by production of prototype devices that meet the requirements defined in the description and are generic devices not intended for any specific system application. This is expected to be an iterative process, likely resulting in the fabrication and testing of multiple prototypes. At the conclusion of Phase II, deliver a minimum of three sample prototype devices to the Government for characterization and evaluation.
PHASE III: Support the Navy in transitioning the technology for Government use. Since the design and prototypes resulting from Phase II are generic, the company will assist in applying the design for specific system applications such as countermeasures. This is expected to entail selection of device dimensions and adjustment of corresponding process parameters in order to produce on-chip combined QCL arrays at specific wavelengths (within the chosen IR band) that combine to produce output power determined by the number of individual QCLs integrated in the array. The final product will therefore be a related family of devices, each device being a highly integrated QCL array with a single high-quality wavelength combined output beam suitable for application in multiple DoD systems including airborne and shipboard IR countermeasures. In non-military applications, QCLs are mainly used in scientific instruments, especially for laser spectroscopy. These devices typically contain a single QCL diode and yield low power as the cost of combing multiple QCLs is prohibitive. This technology would provide higher-power laser sources to the scientific community at reasonable cost.
REFERENCES:1. Zhao, Yunsong, and Zhu, Lin. "On-chip coherent combining of angled-grating broad-area diode lasers.” 2012 Conference on Lasers and Electro-Optics (CLEO), May 2012. https://www.osapublishing.org/oe/abstract.cfm?uri=oe-20-6-6375; 2. Razeghi, Manijeh, et al. "Recent progress of quantum cascade laser research from 3 to 12 µm at the Center for Quantum Devices.” Applied Optics 56, 1 November 2017: H30-H44. https://www.osapublishing.org/ao/abstract.cfm?uri=ao-56-31-H30; 3. Vitiello, Miriam Serena, et al. "Quantum cascade lasers: 20 years of challenges.” Optics Express 23, 20 February 2015: 5167-5182. https://www.osapublishing.org/oe/abstract.cfm?uri=oe-23-4-5167; 4. Razeghi, Manijeh, et al. "Recent advances in mid infrared (3-5µm) Quantum Cascade Lasers.” Optical Materials Express 3, 10 October 2013: 1872-1884. https://www.osapublishing.org/ome/abstract.cfm?uri=ome-3-11-1872
KEYWORDS: Quantum Cascade Laser; Shipboard Countermeasures; Mid-Wave Infrared; Wavelength Beam Combining; Laser Modules; On-Chip Combining
TECHNOLOGY AREA(S): Sensors, Electronics, Battlespace
OBJECTIVE: Develop a low-noise prototype triaxial magnetometer by leveraging recent advances in atomic magnetometers.
DESCRIPTION: Advancements over the last decade in atomic vapor magnetometers have resulted in room temperature devices with sensitivities rivaling Superconducting Quantum Interference Devices (SQUIDs). At the same time, these advances have also reduced the Size, Weight, and Power (SWaP) of commercially available devices by an order of magnitude making them a good match for unmanned Navy systems. While these devices typically readout a scalar magnetic field, other work has considered methods to create atomic triaxial magnetometers such as: applying alternating current (ac) signals to scalar magnetometers in one or more vapor cells, measuring multiple resonance peaks, or using Nitrogen Vacancy (NV) centers in diamond. Creating a magnetometer that provides accurate vector readings as well as a scalar field value provides more information from these sensors thereby minimizing the number of sensors needed for Navy applications. This STTR topic seeks a prototype atomic-based magnetometer that can simultaneously read out the orthogonal magnetic field components with an amplitude noise spectral density of less than 0.3 pT/rtHz from 1 mHz to 100 Hz, which is similar to commercially available scalar magnetometers. The magnetometer should work in real-world conditions including a dynamic range of plus or minus 100 µT on each axis, no dead zones, and an accuracy of 1 nT over the temperature range of 0-50°C. The final sensor should fit in a form factor less than 5 cm x 5 cm x 20 cm, should weigh less than 1 kg including the electronics, and use less than 20 watts of electrical power. The full vector read-out will provide more information than a scalar value, presenting additional correlations that can further improve magnetic detection. Magnetometer will be assessed for far field signature detection at the South Florida Ocean Measurement Facility (SFOMF). A device should cost less than $10k, similar to the chip scale atomic magnetometers currently being commercialized, with design considerations to reduce costs with larger production volumes. Proposals that will leverage prior atomic magnetometer development should include performance data in the frequency range required for this STTR topic.
PHASE I: Design and develop a concept for an atomic-based triaxial magnetometer. Demonstrate the ability to measure a vector magnetic field over the dynamic range of ±100 µT in a bench-top sensor and report the amplitude noise spectral density from 1 mHz to 100 Hz and other requirements provided in the Description. Create models and simulations that shows the feasibility of the design. Develop a Phase II plan. The Phase I Option, if exercised, will include the design specifications and capabilities description to build a prototype solution in Phase II.
PHASE II: Based upon the Phase I design and the Phase II Statement of Work (SOW), deliver, for testing and certification, four prototype triaxial magnetometers that will meet the requirements of the SOW and Description. Demonstrate that the 1 nT accuracy is independent of orientation with respect to Earth’s background field. Integrate the device components into a sensor for testing in a simulated operational environment. Identify components driving the cost and power of the device, and identify measures that could be implemented to reduce the cost and power. A Phase III plan will be required to transition.
PHASE III: Assist the Navy with transitioning the technology to Navy use. Ruggedize and mature the sensor and implement cost-reduction measures to provide a minimal-cost product for Navy acquisition. The technology is expected to transition to submarines. Triaxial magnetometers are used for attitude control on satellites and for geologic exploration of deep structures in the Earth. Long-term accuracy and scalar value are of interest for both applications and an atomically stable sensor should outperform existing solid-state devices.
REFERENCES:1. Seltzera, S. J. and Romalis, M. V. “Unshielded three-axis vector operation of a spin-exchange-relaxation-free atomic magnetometer,” Applied Physics Letters Vol. 85, No. 20 (2004); http://physics.princeton.edu/romalis/magnetometer/papers/Seltzer%20-%20Vector%20Magnetometer.pdf; 2. Yudin, V. I., et al. “Measurement of the magnetic field vector using multiple electromagnetically induced transparency resonances in Rb vapor.” Physical Review A 82, 033807 (2010). http://adsabs.harvard.edu/abs/2011PhRvA..83a5801C; 3. Braje, Danielle, et al. “Broadband Magnetometry and Temperature Sensing with a Light Trapping Diamond Waveguide.” Nature Physics, 11, 393-397 (2015). https://arxiv.org/abs/1406.5235; 4. Wolf, Thomas, et al. “A Subpicotesla Diamond Magnetometry.” Phys. Rev. X, 5, 041001 (2015). https://arxiv.org/abs/1411.6553; 5. Fang, Kejie, et al. “High-Sensitivity Magnetometry Based on Quantum Beats in Diamond Nitrogen-Vacancy Centers.” Phys. Rev. Lett. 110, 130802 (2013). http://adsabs.harvard.edu/abs/2013PhRvL.110m0802F
KEYWORDS: Magnetometry; Atomic Magnetometers; Triaxial; NV Centers In Diamond; Environmental Magnetic Fields; Orthogonal Magnetic Field Components
TECHNOLOGY AREA(S): Ground Sea
OBJECTIVE: Develop technology to provide affordable power-dense electrical rotating machines (motors and generators) for shipboard application.
DESCRIPTION: The Navy is embarking on an aggressive and innovative Power and Energy Program for application on future surface ships and underwater vehicles. Enabling an Integrated Power and Energy System (IPES) on smaller surface combatants will allow smaller ship classes to implement high-power/energy weapons and sensors, such as larger directed energy weapons, sensors with further range and fidelity, and higher-speed operations. With the advent of prime mover power generation and high-power directed weapons, the Navy is striving to distribute an order of magnitude increase in electrical power without increasing system space and weight, or reducing efficiency. Future Navy Ships will require more powerful rotating machines to fit within similar volumes as the current equipment to accommodate new high-power/energy weapons and sensor systems currently under development. The Navy seeks to develop technology necessary to support design, construction, and qualification of affordable power-dense electrical rotating machines (motors and generators) for shipboard application. Affordable is described as being similar in cost to current non-power-dense representative machines (motors or generators described below) chosen by the proposer. Large machines tend to be custom designs based on commercial practices ranging from hundreds of kW to tens of MW for motors and hundreds of kW to hundreds of MW for generators. Power density of the above electrical equipment must be increased in order to allow everything to fit on appropriately sized ships. This increase in power density will require new techniques for heat removal, increased magnetic flux densities, and increased mechanical stresses simultaneously. Advances in power electronics have allowed reductions in power converter size. However, rotating machines have not seen comparable improvement due to physics limitations, lack of business case for typical commercial applications, and limited industry base. Increasing power density in the large rotating machines (generators, large motors) will make more space available for advanced weapons and sensor systems and the power distribution and conditioning equipment necessary to provide electrical power to them. Increased space availability is realized due to usage of a more power-dense machine. The increase in power density may also produce spatial savings within the distribution and power conditioning equipment by improving power quality and reducing the amount of power conversion equipment needed to meet mission system power requirements. A goal of this effort would be to deliver a system that provides 50% more power without an increase in weight or space requirements. This will enable high-energy weapons and sensors to be deployed on ship platforms that would otherwise not have sufficient margin to power these systems. The Navy seeks technologies to develop a high-power density rotating machine that features an increase in power density of at least 50% more than the present state of the art (i.e., 1.5 times the power in the same volume as a current representative machine). The proposer will identify representative motors or generators that they will modify to meet the requirements of the topic. The proposer will also recommend test fixtures and methodologies to support environmental, shock, and vibration testing and qualification to meet the requirements covered under MIL-S-901 [Ref 3] and MIL-STD-167 [Ref 4]. The proposer will also provide related risk assessments and cost estimates for a fully developed shipboard unit. These technologies may include the use of high-energy Permanent Magnet materials and/or advanced cooling techniques such as liquid cooled rotors. The proposer should not focus on any changes that would increase the operating speeds for generators packaged with diesels and gas turbines above 15 MW and for motors used for propulsion directly coupled to the propeller shaft not less than 30 MW, as the effects of increased speed are known and the focus should be on developing other technology solutions. As the technology progresses past initial prototype development, the Navy will determine appropriate systems for replacement with the prototype developed by this STTR topic for operational evaluation, including required safety testing and certification.
PHASE I: Develop a concept for a high power density rotating machine and demonstrate the feasibility of the concept in meeting Navy needs, as well as establish that it can be feasibly developed into a useful product for the Navy. Ensure that the concept discusses the salient features of the performance as well as the physical and functional characteristics of the proposed system. Submit modeling results for the proposed technology with best practice assumptions to estimate realistic efficiency numbers and best estimates of ancillary equipment. Develop a Phase II plan. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a prototype solution in Phase II.
PHASE II: Based on the results of Phase I and the Phase II Statement of Work (SOW), develop, fabricate, test, and deliver a prototype of the machine as identified in the Description to the Navy for evaluation. Prior to delivery of the prototype to the Navy, perform lab testing to yield results for analysis to meet established specification requirements. Ensure that the prototype is of suitable scale to demonstrate the scalability to the larger power levels of shipboard power generation and propulsion and that it meets the performance goals established in the Description. Deliver the prototype to Navy personnel to be evaluated to determine its capability in meeting the performance goals defined in the Phase II SOW and Navy requirements for a high energy density rotating machine. Authenticate machine performance capabilities to meet detailed requirements through prototype evaluation (land-based testing) and modeling or analytical methods over the required range of parameters including numerous operating cycles. Use evaluation results to refine the prototype into an initial design that will meet Navy requirements. Conduct a risk assessment and develop a cost estimate for a naval shipboard unit. Prepare and develop a Phase III installation, testing, and validation plan to transition the technology to Navy use.
PHASE III: Support the Navy in evaluating the prototype delivered in Phase II and assist in transitioning this technology for Navy use. The Navy will determine appropriate systems for replacement with the prototype developed for operational evaluation, including required safety testing and certification. Working with the Government, provide detailed drawings and specifications and document the final product in a drawing package to the Navy for transition into demonstrations and development programs. As stated in the Description, past advances in power electronics have allowed reductions in power converter size. The Navy will be able to utilize these advances as well as the new solution that yields an increase in power density. Other transition opportunities for this technology include commercial ship and offshore systems that could benefit from reduced volume of mechanical equipment. However, rotating machines have not seen comparable improvement due to physics limitations, lack of business case for typical commercial applications, and limited industry base.
REFERENCES:1. Kuseian, John. “The 2015 Naval Power and Energy Systems Technology Development Roadmap.” http://www.navsea.navy.mil/Portals/103/Documents/Naval_Power_and_Energy_Systems_Technology_Development_Roadmap.pdf; 2. Markle, Stephen P., PE, PMS 320 Director & Program Manager. “Surface Navy Electrical Leap Forward.” Sea-Air-Space Exposition Presentation 1.1., 03 April 2017. http://www.navsea.navy.mil/Portals/103/Documents/Exhibits/SAS2017/Markle-ElectricShips.pdf?ver=2017-04-03-155727-897.; 3. Military Specifications: Shock Tests. H.I. (High-Impact) Shipboard Machinery, Equipment, and Systems, Requirements for (17 MAR 1989), MIL-S-901. http://everyspec.com/MIL-SPECS/MIL-SPECS-MIL-S/MIL-S-901D_14581/; 4. DoD Test Method Standard: Mechanical Vibrations of Shipboard Equipment (Type I-Environmental and Type II-Internally (NOV 2005), MIL-STD-167-1A. http://everyspec.com/MIL-STD/MIL-STD-0100-0299/MIL-STD-167-1A_22418/
KEYWORDS: Rotating Machine; High Energy Density; High Power Density; Electric Ship; Electric Drive; Next Generation Integrated Power System (NGIPS)
TECHNOLOGY AREA(S): Sensors, Electronics, Battlespace
OBJECTIVE: Develop an Optical Emulator of complex Electromagnetic Maneuverability (EM) systems with Nanophotonics structure.
DESCRIPTION: Electromagnetic (EM) properties such as EM cross section (EMCS) or antenna gain are often measured in anechoic chambers. However, for very large structures such as submarine or other highly complex platforms, this could be expensive or impractical due to the sheer size of the structure. Computer simulation is a very helpful tool, but the processing time increases exponentially with the scale of the model about the wavelength, making the solution intractable for large systems. Also, these complex codes can easily diverge or present artifacts that should be identified by other means. This is new innovative technology of using Nanostructure and optics to determine periscope venerability. Currently, this is not commercially available. Considering Maxwell's equations are invariant under dilatation transformation, it is possible to make the measurement on reduced size models and using proportionally higher frequencies. By conserving the scale factor between model and wavelength, the solution is identical. In the past, scale models of the structure of interest have been used with a reduced factor of the interested structure of a few tens in scale and kept into the radio frequency (RF) domain. Today, with the emergence of nanophotonics and the access to sub-micron 3D printing machines, it is possible to measure all the EM properties of complex RF systems in the near infrared (NIR) (1 micron) by reducing the size by a factor 105. At that scale, an entire Virginia-class submarine (~150 meters) can be recreated to a length of 1.5 cm and can easily fit in a tabletop measurement setup. The advantages of this approach are faster computation (1/365) and much cheaper than the full-scale measurement (1/250). Using such a large-scale factor also means that it is possible to reproduce large radar clutter such as sea clutter to measure the Radar Cross Section (RCS) measurement of the submarine near marine wave boundary. The NIR wavelength range provides critical advantages over other spectral regions. First, there are many transparent dielectric materials available in the NIR, such as organic polymers, that can be used and engineered to reproduce the complex permittivity of the material observed at RF. Second, there are many optical sources such as femtosecond pulsed fiber laser that can be used for ranging, or supercontinuum laser that can be used for spectral analysis. Third, by using 2D detector, it is possible to determine the specific part of the structure: periscope, communication antenna, stabilizer fin, conning tower, hull, or even wake pattern that is responsible for the RCS signal. This imaging technique gives information similar to Inverse Synthetic Aperture Radar (ISAR), which is a radar technique using Radar imaging to generate a two-dimensional high-resolution image of a target. It is analogous to conventional SAR, except that ISAR technology utilizes the movement of the target rather than the emitter to create the synthetic aperture and without the back projection computation (and artifact). The proposer will demonstrate, at its company location, a femtosecond pulsed laser to perform holographic time-of-flight measurements, which allows retrieving the 3D information of the prototyped Naval platform (10’s of mm in size) model. This type of holographic measurement is similar to the ranging mode of operation of RADAR. In addition, the proposer will demonstrate the capability of immediately identifying the location and the nature of the strongest scatters and glints from the proposed Navy structure of interest. This ability allows for an intuitive interaction with the structure model to eliminate these sources of unwanted scattering and minimize the RCS from visible to RF range. The proposer should identify the RF permittivity of conductors and dielectrics like concrete and vegetation that will be reproduced as nanoparticles. The proposer should develop plasmonic nano-antennas that behave as their RF counterpart using current technology. Future state of the 3D printing technique will be able to create any structure in nano scale, in only a few hours, compared to current manufacturing technology to create a scale model submarine or other structure, which currently takes more than couple of months. Since the RCS measurement by itself can take only a few minutes, this technique offers an extremely fast turnaround between Computer Added Design (CAD) modification and measuring the impact of the change on the RCS signature. This fast turn-around provides a critical advantage on the ability to create a RADAR in stealth structure. The proposer shall demonstrate such antennas by benchtop emulator and can include active emitters, so that antenna placement as well as interferences should evaluate at their far field emission and be measured. The long-term Navy vision is an electromagnetic “wind tunnel” system where, from a CAD model of the structure of interest, a scale model can be manufactured by 3D printing. By integrating different materials, conductor and dielectrics, the model will accurately reproduce the RF properties of the original structure. Active antennas will then be added to specific locations to test for obstruction and interferences. The electromagnetic signature will be obtained with 2D sensors all around the model for a fast and high-resolution measurement. Turnaround time from CAD file to measurement has been proven to be less than a day.
PHASE I: Provide a concept for an Optical Emulator of complex EM systems with nanophotonics to solve the Navy’s problem, and demonstrate the feasibility of that concept based on model-based engineering (MBE), simulation, and modeling. Conduct a feasibility study that includes manufacturing, source, detector, and material scaling. Develop a Phase II plan. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a prototype solution in Phase II.
PHASE II: Build and demonstrate a prototype design of the system from the proof of concept of EMCS technology. Provide a compact demonstration of the prototype’s ability to measure the EMCS of a submarine model in near marine boundary as well as sea clutter as defined in Phase I and Phase II Statement of Work (SOW). Ensure that the RCS measured data compares to the simulation for accuracy and reliability. Ensure that the range demonstrates the ability to identify the structure responsible for the EMCS signal. Deliver a small, compact, desk top, field-operational prototype optical emulator to the Navy. Demonstrate femtosecond pulsed laser to perform holographic time-of-flight measurements at company location, which allows retrieving the 3D information of the model. This type of holographic measurement is similar to the ranging mode of operation of RADAR. In addition, demonstrate the capability of immediately identifying the location and the nature of the strongest scatters and glints from the proposed Navy structure of interest. This ability allows for an intuitive interaction with the structure model to eliminate these sources of unwanted scattering and minimize the RCS from visible to Radio Frequency range. Deliver a bench-top, prototyped RCS measurement instrument and related software and Actual training or training materials/manuals to the Navy for the transition this technology.
PHASE III: Assist the Navy in transitioning the technology. RCS range prototype delivered to the Navy will be used for Submarine, Littoral Combat Ship (LCS), DDG, or any other NAVAL Platform. This technology can be used to scale down and test many different commercial structures such as buildings, cruise ships, and other structures.
REFERENCES:1. Knott, E. F. “Radar Cross Section Measurements.” Springer Science & Business Media, 2012, https://www.springer.com/us/book/9781468499063; 2. Coulombe, M., Horgan, T., Waldman, J., Szatkowski, G. and Nixon, W. “A 524 GHz Polarimetric Compact Range for Scale Model RCS Measurements.” Tech. Rep., DTIC Document, 1999, https://www.uml.edu/docs/Coulombe%2C%20Antenna%20mess_tcm18-42196.pdf; 3. Goyette, T. M., Dickinson, J. C., Waldman, J. and Nixon, W. E. “A 1.56-thz compact radar range for W-band imagery of scale-model tactical targets.” https://www.uml.edu/docs/Goyette%2C%20radar%20range%20tac_tcm18-42363.pdf; 4. Rosenberg, L. and Watts, S. “High Grazing Angle Sea-Clutter Literature Review.” Electronic Warfare and Radar Division, Defence Science and Technology Organisation, Edinburgh South Australia 2013), https://pdfs.semanticscholar.org/20b7/9bf18d96ba26b519cca5b979d165c9d5aea1.pdf; 5. A. Marandi et al., “Network of time-multiplexed optical parametric oscillators as a coherent Ising machine.” Photonics Nature, Vol 8, 937 (2014); 6. S. Utsunomiya et al., “Mapping of Ising models onto injection-locked laser system.” Optics Express, Vol 19, 18091 (2011)
KEYWORDS: Radar Cross-section; Meteorological Instrumentation; Laser Beam Propagation; Maritime Environment; Turbulent Boundary Layer; Nano Photonics
3-Band PicoSecond High Energy Compact (SWaP) Laser System for Marine Wave Boundary Layer Atmospheric Characterization Instrument Development
TECHNOLOGY AREA(S): Sensors, Electronics, Battlespace
OBJECTIVE: Develop a 3-wavelength band (Ultra Violet (250 nm), Visible (500 nm), Near infrared (1 um) Pulsed Fiber Laser System for Marine Wave Boundary Layer Atmospheric characterization.
DESCRIPTION: The Navy seeks technology that is oriented toward a deeper experimental and theoretical understanding of maritime turbulence and laser light propagation in the marine boundary. Ocean evaporation is occurring within a very thin molecular layer at the surface. However, there are indications that turbulent structures in the ocean and atmospheric mixing layers play a critical role in determining the water vapor flux. Current measurement techniques, such as Doppler Velocimetry (LDV) technique, are limited to resolutions of 0.5 meters or greater and fall short of the required millimeter level resolution. A new type of spectral imaging modality and instrumentation is required that will increase our understanding of ocean evaporation and lead to better tools for measuring and modeling the near-marine boundary layer for optical and radio frequency Naval applications. This generalized understanding will significantly enhance beam optic directors, adaptive optics, and other turbulence mitigating techniques to enhance the reach and effectiveness of communication and defensive and offensive laser light engagement in the marine boundary layer. The overall objectives of this STTR topic are to: 1) develop a system capable of measuring atmospheric turbulence near the ocean surface (0 to 60 feet), 2) develop models that can predict turbulent effects given a set of atmospheric and marine surface conditions, such as surface temperature, humidity, pressure, wind speed, wave, fog etc., that can effects marine wave boundary layer atmosphere and 3) develop a metrological instrument based on Raman light detection and ranging (LIDAR). A 3-band laser is an attractive solution offering high power across 3 octaves from the near-IR (NIR) to the Deep Ultraviolet (DUV). Such a multi-wavelength laser offers unique capabilities that allow measurement and modeling of key elements of the near surface marine layer by enabling the accurate fitting to Rayleigh and Mie scattering models from simultaneous analysis of 3 wavelengths. Adapting existing models or creating new physics-based models using data retrieved from the 3-band compact Raman laser system, at picosecond pulse in each band at minimum 1 mJ per pulse energy at 1 kHz repetition rate has the potential to enhance substantially Navy capabilities for deployed high power lasers operating the marine environment. The potential source will the based on the mature fiber laser technology and will make possible compact and power efficient laser systems capable of producing simultaneous UV, visible, and IR radiation at sufficient pulse energy, repetition rate, pulse width, and average power to characterize relevant maritime environments. The platform laser technology should be amenable to the development of a 3-band Raman laser system with Size, Weight, and Power (SWaP) for the integration into submarine sail and cost to facilitate widespread deployment as metrological tool for marine wave boundary atmospheric characterization. The 3-band laser also is the part of High Energy Laser (HEL) closed loop circuits to control the HEL beam on target. The proposed 3-band picosecond Raman laser shall be able to integrate into HEL system for target ranging and detection. It is expected that the application will require a laser system with performance at or exceeding greater than 10W of average power in each band (UV, VIS, IR), pulse energies greater than 1 mJ, temporal pulse width of less than 1 ns for suitable ranging, pulse repetition rates between 1 kHz and at most 5 kHz, and a stable, narrow laser bandwidth of a few wavenumbers or less sufficient to distinguish Raman lines. Laser frequency drift (mitigated by stabilization schemes) may also be of concern at system level. At present to no such system is available to characterize the atmosphere simultaneously in all above three bands.
PHASE I: Develop a concept for a laser system based on model based engineering (MBE) as described in the Description. Demonstrate the feasibility of that concept through laser architecture modeling, simulation, and theoretical calculation. Ensure that the laser is capable of delivering producing greater than 10 W of average power in each band in stable picoseconds, with conversion efficiency in the high-power amplifier of approximately 45% including the combined loss and the unabsorbed pump. Show the laser emitted spectrum of the amplified pulses at different output powers at 3 separate band. Develop a Phase II plan. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a 3-band picosecond Raman laser prototype solution based on MBE in Phase II.
PHASE II: Develop and deliver a prototype of a 3-band picosecond Raman laser system based on the concept developed in Phase I and the Phase II Statement of Work (SOW). Work with the Government to develop the test criteria for the prototype 3-band laser system. Deliver a 3-band laser system to the Navy for the evaluation of performance and further characterization for the purpose of Raman back scattering to characterize atmospheric, temperature, pressure, and humidity. Support the Navy for validation and additional testing to be qualified and certified for Navy use.
PHASE III: Support the Navy in transitioning the technology to Navy submarine platforms as a metrological tool for marine wave boundary data collection. 3-Band picosecond Raman laser technology shall have both commercial and DoD applications. This technology can improve a commercial ship’s localized weather condition prediction and update the weather software for safe operation—thereby improving LIDAR detection for range at day, night, and all-weather operations for both commercial and DoD applications.
REFERENCES:1. Katz, Richard A. and Manzur, Tariq. "Laser beam propagation through an atmospheric transitional and turbulent boundary layer", Proc. SPIE 9456, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security, Defense, and Law Enforcement XIV, 945615 (May 23, 2015). https://doi.org/10.1117/12.2182680; 2. Hufnagel, R. E. and Stanley, N. R. “Modulation Transfer Function Associated with Image Transmission through Turbulent Media”, J. Opt. Soc. Am., 54, 52-61 (1964). https://doi.org/10.1364/JOSA.54.000052; 3. Wasiczko Thomas, Linda M., Moore, Chistopher I., Burris, Harris R., Suite, Michele, Smith Jr., Walter Reed, and Rabinovich, William. “NRL's Research at the Lasercomm Test Facility: Characterization of the Maritime Atmosphere and Initial Results in Analog AM Lasercomm”, Proc. SPIE, 6951, Atmospheric Propagation V, 69510S (April 18, 2008). https://doi.org/10.1117/12.783791
KEYWORDS: Raman LIDAR; Meteorological Instrumentation; Laser Beam Propagation; Maritime Environment; Turbulent Boundary Layer; 3-band Raman Laser System; Picosecond Laser, 10-12 Second
TECHNOLOGY AREA(S): Sensors, Electronics, Battlespace
OBJECTIVE: Research and develop a comprehensive software Surf Zone scene generation, target insertion, and sensor performance model.
DESCRIPTION: The Navy is interested in technologies that facilitate automated target recognition capabilities for previously unseen Surf Zone (SZ) environments and target threats. Typically, algorithms are optimized based on available test data sets, of which most is Beach Zone (BZ) data. This may hinder the assessment and optimization of system performance in new environments and for new target threats. Such constraints may lead to outliers in the operational performance of the system when generalizations of past performance are extended to specific unseen locales and target types. To address these issues, in lieu of conducting numerous costly data collections, there is a need for a comprehensive system model to generate images simulating those acquired in SZ environments and/or with new target types. The technologies developed under this topic will decrease costs by lowering the number of flight tests necessary for algorithm development and enable performance estimations in areas of interest where imagery is lacking. With costs for a SZ test approximately $750k and improving modeling and simulation efforts, testing is the focus area for cost saving efforts. This program’s technological contributions are the following: a tool that inserts new target threats into existing multi-spectral images; a tool that generates Coastal Battlefield Reconnaissance and Analysis (COBRA) equivalent synthetic scenes from other airborne Intelligence, Surveillance, and Reconnaissance (ISR) sensors imagery; and a radiometric model of COBRA’s multi-spectral camera. Additionally, this capability will improve COBRA’s SZ Probability of Detection (PD) and Probability of False Alarm (PFA), which are COBRA Key Performance Parameters, against new target threats and environments. Currently, no end-to-end simulation of the dynamic SZ environment exists. Previous SZ research efforts have only led to static SZ models that breakdown under the SZ’s true dynamic conditions. These models have several problems including non-rotational assumptions for internal wave velocities, inability to simulate complex free surfaces near the wave crest, and accuracy limitations. The comprehensive model to be developed will include sub-models for the SZ environment, targets, platform, and passive and active sensors. For potential techniques applicable to the comprehensive model, see references 2-5. SZ environment models can be cued from existing information sources, such as imagery collected by other airborne sensors. To represent the changing SZ conditions, SZ environment models will be dynamic and will include wave dynamics (including breaking and object motion), foam, turbidity, and flotsam. Target models will allow insertion of targets into the scene, including mines and obstacles. The platform model will include aspects of the sensor platform affecting image acquisition, including platform position, orientation, and sensor pointing. The passive sensor model will provide a parametric, multi-spectral radiometric response given the scene radiometry generated by the other models whereas the active sensor model will provide a response based on specified wavelength interrogation. The Navy will provide imagery, metadata, and a data description to the awardee(s).
PHASE I: Develop a concept for a comprehensive SZ modeling tool. Prepare conceptual designs for each model component, including target, SZ scene background, platform, and sensor. Demonstrate the feasibility to generate a limited set of dynamic SZ scenes with realistic radiometric properties. Develop a Phase II plan. The Phase I Option, if exercised, will expand the SZ scenes to a wider variety of SZ conditions, develop design specifications and capabilities description to build a comprehensive modeling tool prototype solution in Phase II, and work with the Navy to develop a list of potential test environments.
PHASE II: Based on the results of Phase I and the Phase II Statement of Work (SOW), develop and deliver a comprehensive modeling tool prototype, and evaluate the scene generation model and radiometric models against previously collected imagery to determine whether the models meet performance goals as defined. Ensure that the prototype parameter will be at the mine-like object (MLO) level, as opposed to the minefield level. Demonstrate model performance through prototype testing and detailed analysis. Prepare a Phase III development plan to transition the technology to Navy use.
PHASE III: Support the Navy in transitioning the technology for Navy use on the COBRA program by working closely with the current prime contractor to integrate the technology. Utilize the models and software tools to improve performance of the COBRA Block I System. Support updates to the COBRA Technical Data Package (TDP) to support the Navy in transitioning the design and technology into the COBRA Production baseline for future Navy use. Support the Navy for test and validation to certify and qualify the system for Navy use. The technology developed here can be applied to commercial activities that require performance evaluation of multi-spectral remote sensing systems for applications such as forestry, agriculture, and Intelligence Preparation of the Operational Environment (IPOE). Models could support commercial applications such as airborne-based detection and tracking of distressed swimmers in high surf, detection of sharks for swimmer safety in populated waters, monitoring of mammals for boater safety, and erosion monitoring of shoreline, surf zone, and subsea reefs.
REFERENCES:1. "AN/DVS-1 Coastal Battlefield Reconnaissance and Analysis (COBRA)." The US Navy – Fact File. Last update 4 October 2017. http://www.navy.mil/navydata/fact_display.asp?cid=2100&tid=1237&ct=2; 2. Shaw, G. and Burke, H. “Spectral Imaging for Remote Sensing." Lincoln Laboratory Journal, Volume 14, No.1, pp. 3 – 28, 2003. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.69.1178&rep=rep1&type=pdf; 3. Fanning, J., Halford, C., Jacobs, E., and Richardson, P. “Multispectral Imager Modeling." SPIE Vol 5784, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing, 2005. https://doi.org/10.1117/12.604056; 4. Keen, Wayne, Tanner, Michael, Coker, Charles, and Crow, Dennis. “GPU based synthetic scene generation for maritime environments." SPIE Vol 7663, Technologies for Synthetic Environments: Hardware-in-the-Loop Testing XV, 2010. https://doi.org/10.1117/12.851782; 5. “The Digital Imaging and Remote Sensing Image Generation Model.” The Digital Imaging and Remote Sensing Laboratory at Rochester Institute of Technology. http://dirsig.org/; 6. Song, C. and A. I. Sirvientea, 2004, “A numerical study of breaking waves”, Physics of Fluids 16, 2649.; 7. Liu, Y., 2012 “Numerical study of strong free surface flow and breaking waves.” PhD thesis, The Johns Hopkins University.; 8. Wang, Z., Yang, J. & Stern, F., 2016, “High-fidelity simulations of bubble, droplet and spray formation in breaking waves.” J. Fluid Mech. 792, 307–327.; 9. Miyata, H., et al., 1996, “Numerical simulation of three-dimensional breaking waves, Journal of Marine Science and Technology.” Volume 1, Issue 4, pp 183–197.; 10. Lubin, P. & Glockner, S. 2015 “Numerical simulations of three-dimensional plunging breaking waves: generation and evolution of aerated vortex filaments.” J. Fluid Mech. 767, 364–393.; 11. Lubin, P., Glockner, S., Kimmoun, O. & Branger, H. 2011 “Numerical study of the hydrodynamics of regular waves breaking over a sloping beach.” Eur. J. Mech. (B/Fluids) 30 (6), 552–564. http://dx.doi.org/10.1016/j.euromechflu.2011.01.001
KEYWORDS: Target Insertion; Multispectral Scene Generation; Radiometric Sensor Model; Coastal Battlefield Reconnaissance And Analysis (COBRA); Surf Zone Model; Active Sensor Model Based On Specified Wavelength Interrogation
TECHNOLOGY AREA(S): Ground Sea
OBJECTIVE: Develop a “plug and play” inspection-class Remotely Operated Vehicle (ROV) compatible non-intrusive means to attach specialized Explosive Ordnance Disposal (EOD) tools to underwater threat objects to enable standoff neutralization of targets on the seabed and in the water column.
DESCRIPTION: The Navy needs the ability to non-intrusively attach specialized Explosive Ordnance Disposal (EOD) tools delivered by an inspection-class Remotely Operated Vehicle (ROV) to neutralize or dispose of underwater threat objects including naval mines and underwater improvised explosive devices (IEDs) from a standoff location. Solutions will be designed to integrate with the Teledyne SeaBotix vLBV300 and the Next Generation EOD Underwater Response Vehicle. Employment procedure must not require specialized skills for human command and control beyond those required for the employment of the associated EOD tool. The ocean is one of the most challenging environments for underwater attachment using adhesion and/or other mechanical means. While mechanical means provide extremely strong bonds, many cases arise where neither welding nor mechanical fasteners are practical. For example, welding and joining require long application times, are noisy, create vibrations, and generally require the work of a skilled diver. In the case of adhesives, water prevents good mating of the adhesive with the object surface, it diffuses along the interface to assist crack growth, it softens the adhesive, and it hydrolytically degrades the adhesive over time. Perhaps more challenging is the presence of biofouling. Plant and animal matter on the surface prevents contact between the adhesive and the underlying object surface. In cases where the adhesive bonds with the biofilm itself, the poor mechanical integrity of the biofilm leads to detachment at small mechanical loads. Subject tools are neutrally buoyant in seawater and emplaced on a threat object using ROV manipulators. Underwater adhesives promise the simplicity of placing two surfaces in contact. The process can be performed quietly and without requiring permanent modification of the target vessel. Though commercial adhesives exist, most suffer from two major limitations: application/curing speed and resistance to biofouling. Two-part adhesives are most common. The polymerization initiates when two polymeric precursors are mixed together. The speed of the cure necessarily has to be slow in order to provide enough time for mixing and application. Ultraviolet (UV) curing is a faster option and has the additional advantage of being initiated by UV light after deployment on a surface. However, UV curing can only be used with UV-transparent objects and it also fails on thicker adhesive joints. The Navy has particular interest in strong underwater adhesives or other non-intrusive attachment systems that can be integrated onto an inspection-class ROV to deliver specialized EOD tools. Potential attachment methods must be able to be adapted to EOD tools without modification and must not increase the influence signature (i.e., noise, magnetic, vibration) of the ROV. The attachment mechanism must be sufficiently robust to ensure a neutrally buoyant tool will remain in place on the target in typical, near-shore ocean current and wave-action surge environments where horizontal water velocities on the seabed can get up to between 10 and 14 meters per second are common. For adhesive solutions, the desired adhesive should require that the ROV hold the tool in place for 1 minute or less and curing times for final bonding should be in 5 minutes or less, but only after it is deployed on a surface. It should work on all surface types including glass reinforced plastic, aluminum, steel, fiberglass, varying degrees of underwater biofouling (e.g. coral, algae, etc.), and in water temperatures from 32° – 100° Fahrenheit. For bio-materials, the adhesive should either penetrate through the biofilm to the underlying substrate or include a built-in cleaning method for purging the biofilm during application. The goal is to formulate an adhesive or other non-intrusive attachment system that is fast, easy to apply, securely holds tools in place for up to 48 hours (~8 tide changes) once attached, and can be employed by an ROV. The development effort shall include an analysis of the feasibility of production, storage, transport, and deployment by the ROV, including articulation of setup time as a field-configurable payload.
PHASE I: Develop a concept for a non-intrusive means to attach specialized EOD tools to underwater threat objects that works on all surface types, including bio-materials, and meets the requirements in the Description. Include in the concepts how the proposed solution would be integrated onto the Teledyne SeaBotix vLBV300 and the Next Generation EOD Underwater Response Vehicle. Demonstrate feasibility through modeling and simulation. Develop a Phase II plan. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a prototype solution in Phase II.
PHASE II: Develop and deliver a prototype adhesive or other mechanical attachment system based on the results of Phase I and the Phase II Statement of Work (SOW), and validate it with respect to the requirements stated in the Description. Address integration of the prototype with the Teledyne SeaBotix vLBV300 and the Next Generation EOD Underwater Response Vehicle. Ensure demonstration via anchoring a mock neutralizer or specialized payload to a stationary object. Note: Phase II demonstrations need not be performed offshore but would ideally be performed in tanks containing ocean water to simulate marine conditions to a practical extent, and would include current and wave-action surge conditions or simulated conditions typical of near shore ocean environments.
PHASE III: Support the Navy in transitioning the technology to Navy use in the Low Observable, No Collateral Damage (LO/NCD) Neutralization Future Naval Capability (FNC). If successful, rapidly curing underwater adhesives and/or other novel attachment approaches and field configurable systems for application using a small ROV would have immediate commercial applications for underwater repair and construction.
REFERENCES:1. Shaw, S.J. “Adhesives in demanding applications.” Polymer International, 41, 193-207 (1996). http://onlinelibrary.wiley.com/doi/10.1002/(SICI)1097-0126(199610)41:2%3C193::AID-PI623%3E3.0.CO;2-6/full; 2. De Bonis, D. and La Scala, J. “Advanced Fast Curing Adhesives for Adverse Conditions.” Proc. SAMPE 2007 Conference, Baltimore, MD, 3-7 June (2007). https://www.arl.army.mil/www/default.cfm?technical_report=1450; 3. Evans, L. V. “Marine Algae and Fouling: A Review, with Particular Reference to Ship- Fouling.” Botanica Marina 24, 167-172 (1981). https://www.degruyter.com/view/j/botm.1981.24.issue-4/botm.19220.127.116.11/botm.1918.104.22.168.xml; 4. Walte, J. H. “Nature’s underwater adhesive specialist.” Intl. Journal of Adhesion and Adhesives, 7, 9-14 (1987). https://www.sciencedirect.com/science/article/pii/0143749687900480; 5. Tai, R. C. L. and Szklarska-Smialowska, Z. “Effect of fillers on the degradation of automotive epoxy adhesives in aqueous solutions.” Journal of Materials Science, 22, 6205-6210 (1993). https://link.springer.com/article/10.1007/BF00365044
KEYWORDS: Underwater Adhesives; Non-intrusive Attachment; Explosive Ordnance Disposal; EOD; Remotely Operated Vehicle; ROV; Naval Mine Neutralization; Teledyne SeaBotix VLBV300
TECHNOLOGY AREA(S): Info Systems
OBJECTIVE: Develop a unified logging architecture that supports collection, aggregation, storage, and analysis of system performance and cybersecurity logs, events, and alerts produced by Naval Control Systems (NCS).
PHASE I: Define and develop a concept for the architecture and software that enable the unified collection, production and consumption of log, event, and alert data streams for all components of the NCS. Ensure that the concept will feasibly address the requirements discussed in the Description for meeting centralized performance and cybersecurity monitoring within the NCS. Develop a Phase II plan. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a prototype solution in Phase II, as well as determining an appropriate unclassified NCS.
PHASE II: Develop and deliver a prototype of the architecture and software for unified logging of performance and cybersecurity related data streams based on the results of Phase I and the Phase II Statement of Work (SOW). Create a unified logging architecture model for any Navy-specified NCS that incorporates the key attributes defined in the Description. Demonstrate that it can meet the parameters described in the Description to utilize existing Navy-specified system and sub-system components to provide performance- and cybersecurity-related data streams to a centralized aggregation and storage framework for consumption by analytic and monitoring systems to support visibility of full NCS status. Provide a facility for the initial demonstration with final testing and certification occurring at a Government-provided facility. Prepare a Phase III development plan to transition the technology for Navy use.
PHASE III: Assist the Navy in transitioning the demonstrated technologies to the Navy. The architecture should be suitable for Navy specified NCSs and the awardee must support associated system engineering activities of NCS Program offices, with Integrated Warfare Systems (IWS) 5.0 serving as the initial planned transition target. The architecture developed can easily be adapted to non-Navy systems that require centralized visibility of system of systems performance and cybersecurity status in complex, critical environments. Centralized logging for performance and cybersecurity monitoring is of high interest to both the DoD and private industry in understanding and protecting their networks. Any industry that uses a complicated network or system of systems architecture such as healthcare systems (e.g., hospitals, clinics, nursing homes, rehabilitation units, and patient homes) could use this technology.
REFERENCES:1. "Risk Management Framework (RMF) Overview.” National Institute of Standards and Technology (NIST), 30 Jan. 2017. http://csrc.nist.gov/groups/SMA/fisma/framework.html; 2. “Guide to Computer Security Log Management.” National Institute of Standards and Technology (NIST), Sep. 2006. http://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-92.pdf; 3. "Fluentd | Open Source Data Collector.” Fluentd 2018, 12 January 2018. https://www.fluentd.org/; 4. “Apache Kafka.” Apache Project, 2018. 12 January 2018. https://kafka.apache.org/; 5. Mahmood, T. and Afzal, U. "Security Analytics: Big Data Analytics for cybersecurity: A review of trends, techniques and tools." 2013 2nd National Conference on Information Assurance (NCIA), Rawalpindi, 2013, pp. 129-134. https://ieeexplore.ieee.org/document/6725337/
KEYWORDS: Cybersecurity; Computer Network Traffic Analysis; Centralized Logging; Network Intrusion Detection; Naval Control Systems; System Of Systems
TECHNOLOGY AREA(S): Ground Sea
OBJECTIVE: Develop innovative technology improvements to propulsion and power generation prime movers through increased power density and improved fuel efficiency.
DESCRIPTION: Some current commercial applications perform waste heat recovery primarily from the exhaust gases of the prime movers. Typical gas turbine exhaust temperatures are 800° F and higher. Diesel engine exhaust temperatures can be 700° F and higher. Industrial gas turbines have achieved efficiencies up to 60% when waste heat from the gas turbine is recovered in a combined cycle configuration. Although waste heat recovery systems are commonly used in industrial power generation, the highly transient operation of U.S. Navy engines and the stringent requirements applied to the gas exhaust introduce significant technical challenges to heat exchanger durability, caused by the resultant high thermo-mechanical stresses (fatigue and material failure). As such, this STTR topic seeks methods to recover energy from sources as low as 200° F and below (e.g., jacket water) so that heat exchangers do not experience thermal cycling challenges. The Navy seeks to develop innovative technology improvements to propulsion and power generation prime movers (which convert fuel to rotational energy) through increased power density and improved fuel efficiency. Typical gas turbine engines are less than 35% thermally efficient at full power, and significantly less efficient at partial power. Diesel engines have better partial power efficiency, but thermal efficiency generally does not exceed 45%, and power density and longevity are lower. Currently these engines are very inefficient when operating at reduced power levels. Research and development is needed to determine if there is a feasible concept that is power dense and can achieve an overall 10% gain in thermal efficiency. By utilizing technology that will increase the power density and generation efficiency as well as enabling an Integrated Power and Energy System (IPES) on smaller surface combatants, these smaller ship classes will be better able to implement high power/energy weapons and sensors, such as larger directed energy weapons, sensors with further range and fidelity, and higher speed operations. Recovering useful energy in the form of electrical power or alternative heating and cooling applications from these engines over varied operational demands would directly reduce system fuel consumption, increase available electric power, and improve overall system efficiency. Energy recovery will also help to meet the Navy’s need for reliable redundant power. Using recovered energy to augment the power produced by the prime mover will enable system operation at a lower net power with lower net fuel consumption. Other examples of uses for recovered energy may include, but are not limited to, powering small unique loads, supplementing refrigeration systems, precooling chilled water, or charging energy storage systems. As an example, the Navy Landing Platform/Dock (LPD) class amphibious ships each have five Ship Service Diesel Generator Sets (SSDGs) rated at 2,500 KW of electrical output power. Proposals should incorporate technologies that will increase the efficiency of an electric plant like what is on the LPD class by providing at least 150KW of additional power output and an overall system thermal efficiency of greater than 55%. The proposer will develop and test a reduced scale technology demonstrator in the 50-100 KW range that can provide the target performance metrics, scalable to 2500 KW. Solutions should be able to meet future higher power demands of directed energy weapons by incorporating Supercritical carbon-dioxide (sCO2) as the working medium or an alternative working medium that can achieve similar results. All proposed solutions will be analyzed for their impact on engine design and energy heat recovery capability. The technologies must not impose limitations on engine operations and must not impede the airflow of the intakes or uptakes. In addition, the installation of the new technology should not increase the combined generator weight and volume by more than 6% (threshold) or 4% (objective). Emphasis will be placed on modularity and scalability to higher power applications. The proposer must also address shock and vibration requirements covered under MIL-S-901 [Ref 6] and MIL-STD-167 [Ref 7].
PHASE I: Develop a conceptual design for a power dense waste heat recovery system for application to naval ships. Discuss the salient features of the performance as well as the physical and functional characteristics of the proposed system(s). Using best practices, develop thermodynamic models to predict system performance and provide justification for the model assumptions. Use the results from the modeling study to assess the ability of the proposed solution to meet the performance goals and metrics. Develop a Phase II plan. The Phase I Option, if exercised, will outline the specifications and capabilities to build the prototype in Phase II.
PHASE II: Develop, fabricate, deliver, and demonstrate a reduced scale prototype of the module as identified in the Description with a power level of at least 10 kW. Demonstrate the same technology that can support full-scale operation for shipboard power generation. In a laboratory environment, demonstrate through test and validation that the prototype meets the performance goals established in Phase I. Perform all analyses and effort required to refine the prototype into a useful technology for the Navy. Provide detailed drawings and specifications, document the final product in a drawing package, and develop a Phase III installation plan.
PHASE III: Working with the Government, conduct detailed design and fabrication of a shipboard module to provide to the Navy for qualification and other testing as required by the fleet technical authorities in preparation for a shipboard installation. Transition opportunities for this technology include commercial ship and offshore systems that could benefit from reduced volume of mechanical equipment and increased system efficiencies.
REFERENCES:1. “The 2015 Naval Power and Energy Systems Technology Development Roadmap.” http://www.navsea.navy.mil/Portals/103/Documents/Naval_Power_and_Energy_Systems_Technology_Development_Roadmap.pdf; 2. Markle, Stephen P., PE “Surface Navy Electrical Leap Forward.” Sea-Air-Space Exposition Presentation 1.1. 03 April 2017. http://www.navsea.navy.mil/Portals/103/Documents/Exhibits/SAS2017/Markle-ElectricShips.pdf?ver=2017-04-03-155727-897; 3. “Waste Heat Recovery: Technology and Opportunities in U. S. Industry.” BCS, Incorporated, U.S. Department of Energy, Industrial Technologies Program, March 2008. https://www1.eere.energy.gov/manufacturing/intensiveprocesses/pdfs/waste_heat_recovery.pdf; 4. Gibson, S., Young, D., and Bandhauer, T. M. “Technoeconomic Optimization of Turbocompression Cooling Systems.” Paper IMECE2017-70934, ASME International Mechanical Engineering Congress and Exposition, Tampa, FL, 2017. http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=2669116; 5. Yuksek, Errol L. and Mirmobin, Parsa. “Waste Heat Utilization Of Main Propulsion Engine Jacket Water In Marine Application.” ASME 2015, 3rd International Seminar on ORC Power Systems, Brussels, Belgium, October 2015. https://www.researchgate.net/publication/301301713_WASTE_HEAT_UTILIZATION_OF_MAIN_PROPULSION_ENGINE_JACKET_WATER_IN_MARINE_APPLICATION; 6. MIL-DTL-901E, Detail Specification, Shock Tests, H.I. (High-Impact) Shipboard Machinery, Equipment, and Systems, Requirements for. http://quicksearch.dla.mil/qsDocDetails.aspx?ident_number=2640; 7. MIL-STD-167, Fiber Optic Cabling Systems Requirements and Measurements. http://quicksearch.dla.mil/qsDocDetails.aspx?ident_number=277227
KEYWORDS: Supercritical CO2; Heat Exchanger; Energy Recovery In Electrical Generators; Waste Heat Recovery; Thermal Efficiency; Jacket Water
TECHNOLOGY AREA(S): Sensors, Electronics, Battlespace
OBJECTIVE: Develop an innovative low-cost miniature electrical connector for towed arrays that has high-density connections and can withstand high-pressure marine environments.
DESCRIPTION: Currently for its towed arrays, the Navy uses high-density miniature electrical connectors that contain 7-12 pins and meet the harsh environmental requirements inherent in the use of towed arrays and other marine sensors. Existing Navy miniature electrical connectors do not provide effective electrical and mechanical isolation between individual pins over the lifecycle (~5 years) and range of conditions experienced by towed arrays during Navy operations. While these connectors provide adequate isolation as new assemblies, their effectiveness quickly deteriorates due to the environmental, chemical, and mechanical forces experienced by the connectors during their lives. Additionally, these connectors do not provide sufficient protection against electrical contact fretting caused by the relative motion of the mated connectors and insufficient plating (i.e., thickness, material selection or both). The current connectors, while relatively inexpensive to procure (~$100 per pair), are expensive to install due to the density of connections and means afforded to affix wires to each connector. Combined, these shortcomings lead to lower system reliability and availability, which results in significant costs to the Navy both in terms of forcing Navy platforms to leave their missions to replace failed towed arrays as well as the costs associated with troubleshooting, repairing and maintenance, and shipping costs for the failed array. Currently available commercial technologies fail to meet the Navy’s needs on one or more of these factors (i.e., size, cost, environmental ratings). The Navy is seeking an innovative connector that provides a solution to the problems of (1) degradation of mechanical isolation between pins, (2) contact fretting from motion and insufficient plating, (3) wire density, and (4) expensive methods of connecting wires in the connectors. The solution will reduce total ownership cost through low up-front costs (lower than $100 per pair); low assembly, repair, and maintenance costs; and improved reliability. The solution will provide improved electrical isolation (greater than 1 MOhm at 500V) between individual pins (even in the event of a failed pressure seal); improved mechanical sealing (no leakage at 2500 psi) against pressure (e.g., hermetic seal); improved resistance to fretting via better plating, better prevention of relative motion, or both; and reduced cost of manufacturing processes by at least 25%. Cost reduction will result from improved fixtures, tooling or procedures that lower the time, skill or costs to assemble the current connector. Separate fixtures or tools that allow for improved connector manufacturing are acceptable solutions to the issues of ease-of-use and affixing wires during array assembly/repair. While individual single conductor pins are acceptable, it is desirable to have at least one or more pins that maintain coaxial conductors through the connector with a characteristic impedance of 50+/-2 Ohms. If such a coaxial pin can be achieved, it would be counted as 2 conductors (2 pins) for the total count in the connector. For example, while 7-12 coaxial pins are not desired or required, a 1 coaxial and 5 single pins solution would be superior to the currently available solution. The current Navy miniature electrical connector only offers single conductor pins. Fitting a coaxial pin in this form factor, that is also affordable to manufacture, will require innovative solutions not currently available in the commercial or military market. This is a goal, not a threshold requirement. The proposed solution must meet at least the following set of conditions: (1) The connector will be exposed to vibrations up to those described in MIL-STD-167-1A (with requirements extended up to 50Hz) and MIL-STD-810G. (2) The connector will be exposed to temperatures of -40.0C up to 65.0C, and must survive without any damage or performance degradation; however, it is only expected to properly operate over the range of -2.0C to 50.0C. (3) The connector will be exposed to hydrostatic pressures up to 1200 psi, and must survive without damage or allowing fluid into the interface between the connected halves. The connector is housed in the vicinity of other wires as well as components that are vulnerable to damage due to abrasion and cutting. As such the proposed connector must not have any sharp edges on the mated body (no features smaller than 0.005”). Due to the limitations of available space in current Navy towed arrays, the connector must fit within a maximum diameter of 0.635 inches and not exceed 1.25 inches long when mated. Note that the proposed connector need not have a circular cross-section as long as all other requirements are met. The mated connector will be exposed to bending loads of 10 pounds when simply supported (with 5 pounds applied at each end). The connector must not suffer any damage or degradation due to repeated (up to 10,000 cycles) bending loads. The wires will attach to the connector with solder cups that will support up to 20-gage wire. The connector must allow for the use of potting, such as urethane, to seal the back end of the wires as they enter the connector. The proposed connector must have both male and female connector types that provide a feature to prevent misalignment when mating. Each half (male and female) of the un-mated connector must provide an external indication of the alignment feature such that the connector can be visually aligned by an operator prior to attempting to mate the halves. The pins must be capable of handling 500V at a maximum current of 3.0 amps (goal). If desired, a separate connector design could be proposed with few pins (minimum 3) to handle high voltage and current. In that case, the 7-12 pin connector would be required to handle 200V and 2.0 amps (threshold). The insulation resistance between any two pins and between the pins and case must be a minimum of 1.0 giga-ohms when measured with a megohmmeter at 500V. Critical design aspects of the STTR effort are: (1) development of an innovative method to seal the mating pins against external pressures, (2) development of a low-cost manufacturing method (at least 25% improvement), and (3) minimization of the relative motion of the mated pieces during towed array operations. The connector must be easy to use, have solder-ability, meet Navy environmental performance standards described earlier in this description and electrical properties. The environmental compatibility test of the unit will be in accordance with MIL-STD-810G [Ref 4] and MIL-STD-167A [Ref 5]. The Government will assess the electrical properties of the connectors using standard processes (where available) or will develop test procedures with the company where standard processes are not available. The Government will assess the suitability of the connector prototype using the criteria described in the previous paragraphs. The technology will provide innovative solutions to the issues present in the current Navy connector (e.g., electrical isolation, procurement cost, manufacturing cost, mechanical sealing, fretting), while also meeting the environmental and electrical requirements of Navy towed arrays.
PHASE I: Develop a concept for a low-cost, high-density, harsh environment, high-pressure miniature electrical connector. Address the critical performance factors, laid out in the Description, related to electrical isolation, procurement cost, manufacturing cost, mechanical sealing, and fretting. Demonstrate feasibility through analysis and modeling of the key elements (e.g., mechanical packaging model, current carrying capacity calculations, finite element analysis, manufacturing cost model). Develop a Phase II plan. The Phase I Option, if exercised, will include the initial design specifications and capabilities description to build a prototype in Phase II.
PHASE II: Deliver a prototype for testing. Demonstrate its ability to meet the requirements described in the Description. Deliver test results to the Government, which the Government will verify by conducting independent functionality and environmental testing of the connector. Prepare a Phase III development plan to transition the technology for Navy production and potential commercial use.
PHASE III: Assist the Government in transitioning the final connector design to allow for Navy acquisition. Support installation of the connectors into a Government prototype towed array, which will be subjected to standard array performance and reliability testing to verify the suitability of the connector for towed array applications. After successful verification, produce connectors for insertion into prototype and future production towed array systems such as TB-29X. This connector would prove useful in oceanographic research vehicles (manned, unmanned or remotely operated), downhole oil drilling, oil and gas exploration, harsh environment industries (e.g., chemical manufacturing), and oil/gas refineries.
REFERENCES:1. Lemon, S. G. "Towed-Array History, 1917-2003." IEEE Journal of Oceanic Engineering, Vol. 29, No. 2, April 2004, pages 365-373. http://ieeexplore.ieee.org/abstract/document/1315726/; 2. Antler, Morton. “Contact Fretting of Electronic Connectors.” Special Issue of Electromechanical Devices and Their Materials, Vol. E82-C, No.1, January 1999. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.29.8048&rep=rep1&type=pdf; 3. Barnes, Howard E. and Gennari, Jervis J. “A Review of Pressure-Tolerant Electronics (PTE).” Naval Research Lab, Washington DC, June 1976. http://www.dtic.mil/dtic/tr/fulltext/u2/a027967.pdf; 4. MIL-STD-810G, Department of Defense Test Method Standard: Environmental Engineering Considerations and Laboratory Tests. http://everyspec.com/MIL-STD/MIL-STD-0800-0899/MIL-STD-810G_12306/; 5. MIL-STD-167-1A, Department of Defense Test Method Standard: Mechanical Vibrations of Shipboard Equipment. http://everyspec.com/MIL-STD/MIL-STD-0100-0299/MIL-STD-167-1A_22418/
KEYWORDS: High Density; Low Cost Electrical Connector; Towed Array; Miniature Electrical Connector; Coaxial Conductors; Electrical Contact Fretting; Degradation Of Mechanical Isolation Between Pins
Marine Atmospheric Modeling, Data Collection, Visualization & Metrological Toolset for Submarine Electromagnetic (EM) Maneuverability
TECHNOLOGY AREA(S): Sensors, Electronics, Battlespace
OBJECTIVE: Develop an electromagnetic (EM) beam propagation prediction toolset that combines the metrological Marine Wave Boundary Layer (MWBL) atmospheric model, the short pulse multi-band metrological toolset, and visualization software/hardware and uses compact single-aperture Light i detection and ranging (LIDAR) technology for estimating beam performance in the MWBL.
DESCRIPTION: Atmospheric metrological data are used to augment EM beam performance prediction models for estimating effects of atmospheric turbulence on EM beam propagation for a given set of environmental conditions. Estimating atmospheric parameters and their impact on EM beam propagation performance in proximity of the ocean surface is particularly challenging. Close to the surface, complex fluid mechanics and particle motion drive mass transport and turbulence in a region of the atmosphere from 0 to approximately 60 ft (18.2 m) above the sea-air interface defining a MWBL. Height dependent factors contributing to mass transport and turbulence in the MWBL include: gradients of temperature and pressure; wind speed and wave slap; aerosol content and dispersion; and evaporation and condensation of water vapor including humidity, rain, fog, and mist. Moreover, unlike higher altitudes in the atmosphere above the MWBL (at distances on the order of kilometers) where simplified approximations of isotropy and homogeneity hold up and are conventionally used for modeling effects of turbulence on beam propagation at these higher altitudes, near the marine surface where mass transport is prevalent, the assumptions of homogeneity and isotropy no longer apply. Current atmospheric modeling algorithms, such as the Coupled Ocean-Atmosphere Response Experiment (COARE), Navy Atmospheric Vertical Surface Layer Model (NAVSLaM), Navy Surface Layer Optical Turbulence (NSLOT), and Laser Environmental Effects Definition and Reference (LEEDR), either do not predict the atmosphere accurately at the sea-air marine wave boundary layer or were not developed to predict an atmospheric profile given local meteorological measurements at the sea-air interface. To date, sufficient 24/7 data measurement procedures and modeling techniques are lacking for making valid estimates of EM beam propagation performance predictions in the MWBL. Hence, the objective requirements of this topic are to: (a) gain an improved understanding of the underlying physics and mathematics of mass transport and turbulent effects on EM propagation in the MWBL; (b) develop new analytical techniques, modeling, data collection and visualization tools, and procedures for maximizing EM systems signal exploitation in the MWBL for submarine offensive, defensive, and stealth operational performance; and (c) develop a submarine-based single aperture measurement and performance modeling apparatus in which to estimate a priori EM beam propagation performance in the MWBL. Toward this end, a multi-wavelength short pulsed (pico-second) Lidar-based laser system is required. Estimating ‘in situ’ system electromagnetic beam propagation performance from a submarine is not practical for a submarine today. However, with rapid advances in laser and high-performance computing technology, the feasibility of employing a laser-based data collection apparatus on a submarine coupled with a high-performance computer data processing and modeling capability makes the prospect for fielding a prototype in the near-future quite possible. Accurate marine wave boundary atmospheric models and data collection at and below 60 feet are needed for performing high fidelity range estimation, ranging accuracy, target detection, identification and classification at range and power distribution along a horizontal or angular path between source and target-of-interest within the confines of the MWBL. Models and data extractions are useful not only as a tactical decision aid, but also for mission planning of EM system performance for hypothesized scenarios pertaining to offensive, defensive and stealth capabilities. Extrapolation of forecasted data in conjunction with ‘in situ’ measurement profiles also may be used to increase predicted performance accuracy. Forecasted and/or in situ measurement data may include, as examples: air temperature, pressure, and humidity; sea temperature; wind speed, evaporation layer, mist condition, sea particulate size, and wind direction. Visualization tools are required for providing temporally- and spatially-formatted data displays and performance information in a user-friendly format that augments visual interpretation of data and performance results as a tactical decision aid and performance.
PHASE I: Develop a concept to solve the Navy’s problem as described in the Description, and demonstrate the feasibility of that concept through simulation, modeling, and verification via data collection and development of short pulse multiband Lidar metrological system development over marine wave boundary layer. Model key elements of the concept to provide a high degree of confidence and data collection. Model the compact short pulse multi-band Lidar-based metrological tools that will be used for data collection over MWBL and determine their feasibility. Document the MWBL model and provide modeling, data supporting the approach and metrological system architecture based on multiband short pulse Lidar to monitor marine wave boundary layer particle size distribution, temperature, and pressure. Propose to the Government the expected level of accuracy. Develop a Phase II plan. The Phase I Option, if exercised, will lay out the model and characteristics for development into a prototype in Phase II.
PHASE II: Develop and deliver a prototype metrological system based on short-pulse multiband Lidar (single-aperture transmitter/receiver) for testing and evaluation based on the results of Phase I and the Phase II Statement of Work (SOW). Describe how the prototype will be evaluated to determine if the technology has the potential to meet Navy performance goals described in the Phase II SOW. Use the data collected using the prototype metrological system at marine atmospheric for the validation of the MWBL model and visualization software. Deliver the toolset to the Navy to determine its capability in meeting Phase II performance goals through additional testing and refinement with atmospheric data captured using existing commercial meteorological tools and developed under a LIDAR tool set.
PHASE III: Support the Navy in transitioning the technology, including the marine visualization data, to Navy use. Transition of algorithms to the submarine combat system occurs through the PMS 435 Advanced Processor Build/Technical Insertion (TI-APB) process. Test data collected by the awardee during Phase II and data provided by the Government during Phase III. Provide technical support to the Navy over the course of transition. This technology will have applications in atmospheric modeling for any worldwide scenarios where access to weather information is limited.
REFERENCES:1. Fairall, C. W., et al. "Bulk Parameterization of Air-Sea Fluxes: Updates and Verification for the COARE Algorithm." Journal of Climate 16.4 (2003): 571-591. https://www.researchgate.net/publication/215721706_Bulk_Parameterization_of_Air--Sea_Fluxes_Updates_and_Verification_for_the_COARE_Algorithm; 2. Frederickson, P. A., Davidson, K. L., Zeisse, C. R., and Bendall, C. S. “Estimating the Refractive Index Structure parameter (Cn2) over the Ocean Using Bulk Methods.” Journal of Applied Meteorology 39, 1770-1783 (2000). https://www.researchgate.net/publication/249607025_Estimating_the_Refractive_Index_Structure_Parameter_over_the_Ocean_Using_Bulk_Methods; 3. Kemp, E., Felton, B., and Alliss, R. “Estimating the Refractive Index Structure-Function and Related Optical Seeing Parameters with the WRF–ARW.” Northrop Grumman Information Technology/TASC, Chantilly, Virginia. National Center for Atmospheric Research WRF User Workshop, P9.30 (2008). http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.525.3762&rep=rep1&type=pdf; 4. Cagigal, M. and Canales, V. “Generalized Fried parameter after adaptive optics partial wave-front compensation.” J. Opt. Soc. Am. A 17, 903-910 (2000). https://www.researchgate.net/publication/12521033_Generalized_Fried_parameter_after_adaptive_optics_partial_wave-front_compensation
KEYWORDS: Light Detection And Ranging; Lida R; Navy Atmospheric Vertical Surface Layer Model; NAVSLaM; High Energy Laser; HEL; Electronic Warfare; EW; Coupled Ocean Atmosphere Response Experiment; CORE
TECHNOLOGY AREA(S): Sensors, Electronics, Battlespace
OBJECTIVE: Develop and demonstrate an innovative method to detect, prevent, and protect high-inductance, High Temperature Superconducting (HTS) coils from damage that would normally occur in a quench event.
DESCRIPTION: The Navy has been developing high-temperature superconducting (HTS) systems, such as large-scale motors or large-scale magnets, over the past few decades using HTS coils. Superconducting magnets utilizing alternating current (AC) modulation do not have any quench detection capabilities, putting the system at risk for damage due to uncertain superconducting-state health. HTS wire has the ability to pass large electrical currents with essentially no voltage drop due to its zero resistance when below the transition temperature. Therefore, there is tremendous advantage to use HTS technology in applications generating large magnetic fields such as, high-field magnets, motors, generators, and superconducting magnetic energy storage (SMES) systems. However, when high-temperature superconductors are used in these aforementioned applications, there is significant operational risk to an HTS coil in the event of a quench. For superconducting power cables, a quench event is not as critical as that of a magnet-based system which inherently stores large amount of inductive energy. In the field of HTS technology, a “quench” is when an HTS conductor transitions from its superconducting state to its normal-conducting resistive state. Typically, the transition initiates in a local region referred to as “normal zones”. Depending on the design of an HTS magnet, individual coils may be replaced, or repaired; however, this is very costly, and time consuming, and does not guarantee that the HTS magnet will be operational upon completion of an attempted repair. Methods to detect the onset of a quench, prevent a quench from occurring, and/or protect the HTS coil from damage must be employed to safeguard HTS coils. High-field HTS magnets have large electrical inductances that store mega-joules of energy. When a quench occurs, this energy converts to heat in the normal zone of the conductor and has the potential to cause a burnout in the HTS coil. The current method of quench monitoring and protection system technology measures the voltage drop across the HTS coils. When the voltage exceeds a set threshold, the energy in the coils is “dumped” to a resistive load to protect the coil from quenching. The limitation with this type of system is a delay between 500ms to 1000ms to detect the onset of quench, and rate of energy extraction to protect the coils. Furthermore, since voltage measurements are typically taken over long conductor lengths, indicators of a localized quench may be masked causing a delayed response. In addition, when an HTS magnet is used as an AC magnetic source or as a pulsed current source, the differential voltage across a coil could reach kilovolt levels that are difficult for simple quench detection data acquisition hardware to manage. The proposed solution technology is expected to be applicable to superconducting magnet payloads, HTS motor and generator field and stator coils, and pulsed current SMES systems subject to alternating currents. The quench monitoring and control system must provide adequate quench detection, prevention, and protection to both direct current (DC) and AC HTS coils. The system must also provide a safe shutdown sequence in the event a quench occurs. The solution must have the ability to be integrated with HTS coils and their sub-systems, operate with HTS magnet controls, and be fully operational in a naval environment. Since initial target application is for integration into an HTS system as a payload on an Unmanned Surface Vehicle (USV), compact and lightweight solutions (i.e., standard 19” rack mount, on the order of 50-70lbs) are favorable. The quench monitoring and control system should be able to detect a quench within 80ms. It should be able to operate in magnetic applications with voltages ranging from 0V to ±12kV and AC frequencies ranging up to 60Hz. Any hardware or sensors mounted to the HTS coils should be able to operate at magnetic fields up to 5T, and any hardware or data acquisition systems should be shielded from magnetic fields up to 1T. The proposed solution should be effective with coils wound from tens of meters to tens of kilometers of wire or more. In addition, any proposed hardware or sensor solutions mounted to the HTS coils should be able to operate in temperatures from 20K to 100K (-253°C to -173°C), and must be able to be integrated into a cryogenic cryostat containing the magnet coil. Any auxiliary hardware or data acquisition systems external to the cryostat must operate in atmospheric air temperatures from -20°C to 46°C, cooling water from 4°C to 40°C, humidity levels from 0% to 100%, and salt fog conditions as listed in MIL-STD-810G (Section 509.5) [Ref 4]. Finally, all proposed solutions must be capable of withstanding military shock specifications as listed in MIL-S-901D Grade A [Ref 5] and military vibration standards listed in MIL-STD-167-1A [Ref 6].
PHASE I: Define and develop a quench detection, prevention, and protection concept that meets the objectives stated in the Description. Demonstrate the feasibility of the proposed concept through modeling and analysis. Quantify the clear benefits in terms of speed to detect, prevent, and protect an HTS coil as compared to existing voltage measurement solutions [Ref 2]. Develop size and weight objectives of proposed concepts including sensors and control electronics. Develop a Phase II plan. The Phase I Option, if exercised, will include the initial layout and capabilities description to build the prototype in Phase II.
PHASE II: Develop and fabricate a prototype for demonstration and characterization of key parameters of the quench control system as described in the Description. Conduct a prototype demonstration capable of full-scale operation according to the design. Complete relevant testing to prove the full-scale metrics. Based on lessons learned through the prototype demonstration, develop a substantially complete design of a quench control system to allow for Navy integration. Ensure that this design includes all ancillary equipment required to operate components such as the quench control system, integration hardware, and control software when applicable to the proposed concept.
PHASE III: Support the Navy in transitioning the technology for Navy use. Although a fully operational quench control system is initially targeted for use in an HTS system as a payload aboard a USV, the quench control system should have the ability to transition to any naval acquisition program utilizing HTS coils as either a major system or as a sub-system to a larger program. The desired quench control system has applications in commercial large-bore superconducting magnets used in the medical field, large-particle accelerators, and superconducting motor applications. A simpler design of the quench control system could also be applied to superconducting power distribution, superconducting electric grids and alternative energy technologies using superconducting systems.
REFERENCES:1. Scurti, F., Ishmael, S., Flanagan, G., and Schwartz, J. “Quench Detection for High Temperature Superconductor Magnets: a Novel Technique Based on Rayleigh-backscattering Interrogated Optical Fibers.” Superconductor Science and Technology, Volume 29, Number 3, March 2016. http://iopscience.iop.org/article/10.1088/0953-2048/29/3/03LT01; 2. Marchevsky, M. “Protection of Superconducting Magnet Circuits.” U.S. Particle Accelerator School (USPAS) Course Material, UC Davis, January 2017. http://uspas.fnal.gov/materials/17UCDavis/MachineProtection/uspas_mm.pdf; 3. Wakuda, T., Ichiki, Y., and Park, M. “A Novel Quench Protection Technique for HTS Coils.” IEEE Transactions on Applied Superconductivity, Volume 22, Issue 3, June 2012. http://ieeexplore.ieee.org/document/6111204/; 4. MIL-STD-810G (sect 509.5), Department of Defense Test Method Standard: Environmental Engineering Considerations and Laboratory Tests. http://everyspec.com/MIL-STD/MIL-STD-0800-0899/MIL-STD-810G_12306/; 5. MIL-S-901D Grade A, Military Specifications: Shock Tests H.I. (High-Impact) Shipboard Machinery Equipment, and Systems, Requirements for. http://everyspec.com/MIL-SPECS/MIL-SPECS-MIL-S/MIL-S-901D_14581/; 6. MIL-STD-167-1A, Department of Defense Test Method Standard: Mechanical Vibrations of Shipboard Equipment. http://everyspec.com/MIL-STD/MIL-STD-0100-0299/MIL-STD-167-1A_22418/
KEYWORDS: High Temperature Superconductor; High-field Magnets; SMES; Quench Detection; Quench Prevention; Quench Protection; Superconducting Magnetic Energy Storage
TECHNOLOGY AREA(S): Info Systems, Human Systems
OBJECTIVE: Mature algorithms/software to enable assessments and predictive capabilities from graph data relevant to Naval use cases.
DESCRIPTION: Convolutional neural networks (CNNs) in recent years have revolutionized computer vision. Recurrent neural networks have enabled meaningful progress in natural language processing. Naval data, however, is to a significant extent graph based. For example, information about an opposing force (e.g., a platform or unit having some set of attributes/capabilities present at a specific location) is most effectively captured in a graph form. In the last couple of years, graphical convolutional networks have been developed with the goal of enabling CNN-based performance on images to translate to graph data. Under this STTR topic, during Phase I awardees will tackle the problem of training a machine to make decisions from graph sequences [Ref 5] using open source data. Researchers will mature and code graphical convolutional neural networks to make predictions from dynamic text-derived graph data. Of particular interest is a capability that can predict future risk assessments and global trends in Global Database of Events, Language, and Tone (GDELT) from activity / content in Reddit. During Phase II, awardees will train graph CNNs to make decisions on the capabilities and limitations and vulnerabilities/opportunities for units/forces from graphical data with the help of Government-furnished data. Awardees will be expected to mature their Phase I algorithms and train machines to assess units/forces based on their attributes/capabilities/conditions/locations. Specific technical challenges include algorithm development, feature selection, the design of a machine learning training plan, and results in good performance against test data. Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. owned and operated with no foreign influence as defined by DoD 5220.22-M, National Industrial Security Program Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Security Service (DSS). The selected contractor and/or subcontractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances, in order to perform on advanced phases of this project as set forth by DSS and ONR in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material IAW DoD 5220.22-M during the advanced phases of this contract.
PHASE I: Determine feasibility and complete a proof of concept study of the use of a graphical convolutional neural network for risk assessment and global trends. Conduct a detailed analysis of literature and commercial capabilities. For a bounded number of Reddit sub-groups and GDELT metrics, train a model that predicts one from the other. Carefully design a validation plan to verify performance of the resulting model. Develop a Phase II plan with a technology roadmap and milestones for generalizing the use of their algorithm.
PHASE II: Produce a prototype system based on the preliminary design from Phase I. Ensure that the capability of the prototype extends to a machine learning service that can predict the capabilities/limitations of a platform/force and suggest opportunities/vulnerabilities from graph-based data. Note: The system will need to ingest military graphical data at the secret level and provide explanatory evidence for unit/force assessments; and simulations may be needed to generate labeled data. During Phase II, the small business may be given specific mission scenarios by the Government to validate capabilities. An awardee should assume that the prototype system will need to run as a distributed application with a mature design for the human computer interface. Deliver a working prototype of the system (source code and executable) and software documentation including a user’s manual, and provide a demonstration using a Naval operational scenario of interest. It is probable that the work under this effort will be classified under Phase II (see Description section for details).
PHASE III: Produce a final prototype capable of deployment to training centers, operational command and control centers and as a virtual application. Adapt the system to transition as a component to a larger system or as a standalone commercial product. Provide a means for performance evaluation with metrics for analysis (e.g., accuracy of assessments) and a method for operator assessment of product interactions (e.g., display visualizations). The Phase III system should have an intuitive human computer interface. The software and hardware should be modified and documented in accordance with guidelines provided by the engaged Programs of Record and any commercial partners. Researchers are encouraged to publish S&T contributions. Technology development should be applicable to any domain that requires assessments/predictions to be made from graph-based data including but not limited to common tactical picture assessment, readiness assessment, event detection, or video summarization.
REFERENCES:1. Kipf, Thomas N. “Graph Convolutional Networks.” 30 September 2016. https://tkipf.github.io/graph-convolutional-networks/; 2. Ganssle, Graham. “Node Classification by Graph Convolutional Network.” January 20, 2018. https://www.experoinc.com/post/node-classification-by-graph-convolutional-network; 3. Kipf, Thomas N. and Willing, Max. “Semi-Supervised Classification with Graph Convolutional Networks.” ICLR 2017. https://arxiv.org/abs/1609.02907; 4. Henaff, Mikael, Bruna, Joan, LeCun, Yann. “Deep Convolutional Networks on Graph Structured Data.” Submitted 16 June 2015. https://arxiv.org/abs/1506.05163; 5. Li, Yujia, et. Al, “Gated Graph Sequence Neural Networks” ICLR 2016 https://arxiv.org/abs/1511.05493v4
KEYWORDS: Graph Analysis; Fusion; Convolutional Neural Networks; Predictive Science; Natural Language Processing; Classifications
TECHNOLOGY AREA(S): Air Platform, Ground Sea, Electronics
OBJECTIVE: Produce algorithms that can identify vulnerabilities in software for Field-programmable Gate Arrays (FPGAs). The focus is the analysis of software at the various stages of synthesis and not the actual hardware (i.e., Altera or Xilinx) on which the code is implemented.
DESCRIPTION: FPGAs are becoming more prominent in technology. They have become just as favorable as Application Specific Integrated Circuits (ASICs) in some applications and are even showing up in some computer server technology for the enterprise. FPGAs also play a vital role in Naval systems for their real-time processing and ability to be upgraded with new software. As opposed to standard Internet connected computing hardware, FPGAs have received minimal research and development (R&D) for cyber protection. Most of the work t for FPGA security thus far has been in the vein of protecting the intellectual property (IP) aspect from theft and physical reverse engineering efforts. This does not address operational vulnerabilities due to how the code is structured and executes based on inputs and state conditions. Due to the acceleration of cyber-warfare and hacking, this is problematic. The development and deployment of code for FPGAs goes through a different set of synthesis tools than what typical computing users are familiar with for application development. This presents a lack of familiarity from the mainstream cybersecurity community. Another issue is the potential source of vulnerabilities that comes from purchased 3rd party IP cores. There are little to no tools available for evaluating FPGA code for cyber vulnerabilities. From an ideal perspective, the Navy would like vulnerability analysis conducted on the bitstream as it resides on the physical device; however, the Navy realizes that there may be complications due to encryption and access. With that in mind, the Navy is requesting proposals that present approaches for analyzing the FPGA code as close to in situ (or on device) as possible. The Navy will be open to opportunities to analyze the code throughout the synthesis process chain. Preference will be closer to the deployed application on the board but awardees must convince the Navy that their approaches has a reasonable likelihood of success. There will be no Government-furnished equipment (GFE) provided for this effort. Awardees must provide their own hardware and code for experimentation. Proposers must have experience in the FPGA domain to be competitive.
PHASE I: Develop a concept and methodology to automatically identify potential cyber vulnerabilities in the FPGA code at the level(s) under study. Ensure that the algorithm can locate and identify the portion of the code that is vulnerable and also provide a brief explanation as to why it is vulnerable and a proposed remediation description. Provide a limited proof-of-concept application to demonstrate the viability of the approach. Develop a Phase II prototype plan.
PHASE II: Develop the prototype into a fully functioning software toolset for identifying and tagging cyber vulnerabilities within the FPGA code. Provide a graphical user interface (GUI) that allows the user easy identification of the vulnerability, its significance, and a description for remediation. Demonstrate and evaluate the efficacy of the tools on FPGA codes of varying complexity as selected by the awardee.
PHASE III: Work with the Navy to integrate the tool into current cyber assessment processes. Many test and evaluation teams require more automated and more frequent assessment of the cybersecurity posture of weapons systems and hull, mechanical, and electrical (HM&E) systems. The Office of Naval Research (ONR) will facilitate interactions with Naval Sea Systems Command (NAVSEA), Naval Air Systems Command (NAVAIR), and Space and Naval Warfare Systems Command (SPAWAR) to apply the tool to Navy's cyber-physical systems. The R&D conducted here would be equally useful in the commercial sector in any application where FGPAs are implemented.
REFERENCES:1. Kastner, R. and Huffmire, T. “Threats and challenges in reconfigurable hardware security.” California University San Diego La Jolla, Department of Computer Science and Engineering, 2008 Jul. http://www.dtic.mil/docs/citations/ADA511928; 2. Trimberger, Stephen M., and Moore, Jason J. "FPGA security: Motivations, features, and applications." Proceedings of the IEEE 102.8 (2014): 1248-1265. https://ieeexplore.ieee.org/document/6849432/
KEYWORDS: FPGA; Synthesis; Vulnerability; Cybersecurity; Scanning; 3rd Party IP Cores; Intellectual Property; IP
TECHNOLOGY AREA(S): Air Platform, Electronics
OBJECTIVE: Develop the means to recharge battery-operated micro and small unmanned aerial systems by harvesting energy from the battlefield, eliminating the need for the systems to return to base.
DESCRIPTION: The employment of micro (µ-) and small unmanned aerial systems (sUAS) is expected to dramatically increase over the next decade. These µ- and sUAS are anticipated to be battery-operated and capable of short-duration missions, for example up to 25 km distance and 30 minutes of flight, with operational capabilities increasing as battery technology improves. The infrastructure to manage a future fleet of sUAS in the field under austere conditions may be daunting considering the magnitude of battery recharging needs. It is also desirable to simultaneously increase mission duration and persistence; therefore, the ability to scavenge power directly from the battlefield would be an important military technology with other dual-use civilian applications. To that end, harvesting energy that would otherwise be wasted from the environment to power µ- and sUAS is an attractive option because much of the fuel that is required for batteries, supercapacitors, and fuel-cells need not be always stored on the device. The types of energy harvesting that fall into this category are broad, and include vibrational energy, simple mechanical energy, and electromagnetic energy. Sources of electromagnetic energy that is abundant and available for harvesting and conversion include high-voltage substations, transformers, and alternating current transmission line (i.e., power lines). High-voltage (500 kV) substations generate AC electric field strengths that approach 18 kV m–1, and magnetic flux densities that can approach 10µTrms, which could produce a power density >100µW cm–3, which is comparable to solar panels operating on a cloudy day. Alternatively, allowing an unmanned aerial vehicle (UAV) to “dock” on a power line in an urban environment, scavenging magnetic energy as a means to trickle-charge its onboard batteries prior to mission continuation, could provide significant tactical benefits. If the energy scavenging source is collocated at the mission area, full mission persistence might be achieved and the µ- and sUAS may never need to return to base. In addition to battery recharging is the increased demand of distributed sensing and communication. The same technological examples described above can be extended to the strategic placement and powering of wireless sensor nodes on the battlefield. Further, other energy modes are ripe for harvesting in the environment of, for example, an electrical transformer, including vibrational, thermal, and acoustic energy. Piezoelectric nanogenerators are one such technology that has been shown to convert small mechanical fluctuations and vibrations into electric energy, and can generate the magnitude of power (10–100s µW) required for these wireless sensor nodes [Refs 2, 4, 5].
PHASE I: Define and develop a concept/approach to recharge a µ- or sUAS in the field without having to return to base. Conduct modeling and simulation and/or calculations to justify the feasibility of this energy harvesting concept in both pass and active mode. Preliminary environmental conditions to be considered include altitude, wind speed, humidity, and weather. Describe in detail the energy harvesting system design and proposed energy output and feasible battery size and recharge time, targeting a total recharge time =12 h. Develop a Phase II plan. The Phase I Option, if exercised, could include a sub-scale, lower fidelity, laboratory demonstration.
PHASE II: Develop, demonstrate, and validate the energy harvesting concepts in a laboratory or outdoor environment. The prototype should be delivered with a down-selected dimension and associated battery size; the prototype will be paired with an appropriately sized existing µ- and/or sUAS for testing. The prototype should be delivered at the end of Phase II, ready to be flown by the Government once paired with a target µ- and/or sUAS. Document final prototype design and vendor test results.
PHASE III: Produce full-scale prototypes consistent with Program of Record needs and private sector transition of the technology. Successful demonstration of harvesting technology extends to the commercial sector in the fields of adaptable, wireless battery recharge and wireless sensor nodes.
REFERENCES:1. Marshall, P. T. “Power Line Sentry Charging.” U.S. Patent 7,318,564 B1 (Issued 15 Jan 2008) https://patentimages.storage.googleapis.com/79/bc/ad/0029f206b3c875/US7318564.pdf; 2. Hu, Youfan and Wang, Z. L. “Recent progress in piezoelectric nanogenerators as a sustainable power source in self-powered systems and active sensors.” Nano Energy, 14, 2015, 3–14. http://www.nanoscience.gatech.edu/paper/2014/14_NE_14.pdf; 3. Roundy, S., Wright, P. K., and Rabaey, J. “A study of low level vibrations as a power source for wireless sensor nodes.” Computer Communications, 26, 2003, 1131–1144. https://www.sciencedirect.com/science/article/pii/S0140366402002487; 4. Green, C., Moss, K. M., and Bryant, R. G. “Scavenging Energy From Piezoelectric Materials for Wireless Sensor Applications.” Proc. Of the IMECE2005, 2005, Orlando, Florida, USA. https://www.researchgate.net/profile/Christopher_Green7/publication/236274075_Scavenging_Energy_From_Piezoelectric_Materials_for_Wireless_Sensor_Applications/links/00b7d51788434d1b4f000000/Scavenging-Energy-From-Piezoelectric-Materials-for-Wireless-Sensor-Applications.pdf?origin=publication_detail; 5. Yuan, S., Huang, Y., Xu, Q., Song, C., and Thompson, P. “Magnetic Field Energy Harvesting Under Overhead Powerlines.” IEEE Transactions on Power Electronics, November 2015.
KEYWORDS: Energy Harvesting; Energy Scavenging; UAS; Unmanned Aerial Systems; Battery Recharging
TECHNOLOGY AREA(S): Materials
OBJECTIVE: Develop (1) algorithms to transform various raw data formats into information-rich features for machine learning (ML), and (2) software and modeling tools for ML that will automatically detect patterns in data; and learn and improve from experience the ability to predict new materials/optimal materials processes.
DESCRIPTION: Machine learning is a powerful subset of artificial intelligence for systems to learn from data, pattern identification, and decision making. Application of machine learning tools can enable accelerated new materials discovery by leveraging existing data for potential alloy composition and processing. A key challenge in applying ML algorithms to materials science data is that data comes in many formats. Determining how to featurize and utilize different materials data formats so that prior data can be used as training data for ML algorithms can be difficult. Feature engineering, including extraction, transformation, and selection, is critical for improved ML accuracy. High entropy alloys (HEAs) or multi-principal element alloys (MPEAs) utilize a broad composition space through control of material entropy. This growing material set can allow for enhanced material properties compared to conventional materials. Basic research of HEAs requires development of a powerful computational infrastructure, which, when coupled with multiple database formats and ML approaches, can accelerate discovery of new viable HEAs. Additionally, additive manufacturing (AM) materials and processes would also be able to feature engineering tool sets to accelerate process development for new AM materials. Applying these tools to new materials and processes can be impactful to accelerate materials development. To fully realize data analytics and machine learning tools for materials development, it is necessary to focus on developing algorithms to transform various raw data inputs into information-rich features suitable to model. The concept/approach/framework created by developing algorithms to classify and unify disparate data sets into a consistent format can be utilized and augmented by subsequent researchers. Feature transformation and selection would enable accuracy improvements to ML models applied to HEAs and AM.
PHASE I: Define and develop a concept/approach/framework for feature engineering tools to extract critical information from multiple formats. Key features may include material properties, chemistry, and processing variables. Include, in the concept/approach/framework, development of an alloy-related materials database with appropriate identification classifiers and interactions. Develop a Phase II plan. In a Phase I option, if exercised, the STTR team will demonstrate the feasibility of the proposed concept/approach to provide labeled data output for HEAs/AM.
PHASE II: Develop, demonstrate, and validate a materials database for supervised (e.g., support vector, neural networks) and unsupervised learning algorithms (e.g., cluster analysis) use for HEA/AM. Ensure that the database is able to identify prioritization of features whether it be structural, chemical, and physical properties or AM-related processing-microstructure-property phenomena.
PHASE III: Transition optimized computational/informatics handling engineering tools for commercialization in ML utilization through original equipment manufacturers (OEMs) or other partnering agreements. Commercialization of this technology may be through new material discovery or rapid process development. The STTR team will demonstrate the technology to DoD warfare centers/production facilities. Dual use applications could include aircraft, land vehicles, materials processing entities.
REFERENCES:1. Miracle, D. B. and Senkov, O. N. “A critical review of high entropy alloys and related concepts.” Acta Materialia. Vol. 122, 1 January 2017, p. 448-511. https://www.sciencedirect.com/science/article/pii/S1359645416306759; 2. Witten, Ian and Frank, Eibe. “Data Mining: Practical Machine Learning Tools and Techniques.” ftp://ftp.ingv.it/pub/manuela.sbarra/Data%20Mining%20Practical%20Machine%20Learning%20Tools%20and%20Techniques%20-%20WEKA.pdf; 3. Ling, Julia, et al. “Machine Learning for Alloy Composition and Process Optimization”. (Proceedings of ASME Turbo Expo 2018 Turbomachinery Technical Conference and Exposition.) https://arxiv.org/abs/1704.07423
KEYWORDS: Machine Learning; Feature Engineering; Additive Manufacturing; High Entropy Alloys; Data Analytics; Feature Extraction
TECHNOLOGY AREA(S): Info Systems, Human Systems
OBJECTIVE: Develop an intelligent modeling framework for cyberspace threat actor behaviors that traces their genealogy and supports predicting their future evolution.
DESCRIPTION: Cyberspace threat actors develop tactics, techniques, and procedures (TTP) that evolve over time in response to environmental stimuli. This evolution may be triggered by the actors’ growing expertise or changing goals, or by changes in their targets such as discovery of threat actor tactics or improved defenses. In the absence of such stimuli, however, these behaviors tend to remain fairly constant with regard to any given goal. Longitudinal studies of threat actors could identify inflection points in their behavior patterns, which in turn would provide valuable intelligence for defensive cyberspace operations (DCO). For example, the deployment of a new security control that lessens the effectiveness of an adversarial tactic would reasonably cause the threat actor to change behaviors if they still want to accomplish a similar goal. This change would confirm the effectiveness of the new control similarly to how one uses battle damage assessment (BDA) techniques. On the other hand, an unexpected change in TTP would tell the defenders that something of interest happened to the threat actor. If DCO personnel can find no known events that correlate to such changes, they would likely want to investigate further. There are few techniques that support forensic analyses of cyberspace behaviors and many of these are focused on external attacks involving malware. To the extent that such studies are being performed, they are manually done by highly skilled analysts. This approach requires significant investments of staff, time, and money. It seems plausible to leverage machine learning (ML) techniques to identify, classify and track discrete cyberspace events and to infer the behaviors, and ultimately the goals, to which they are related. Such use of ML, coupled with large sensor networks, would yield an unprecedented ability to monitor what our adversaries are doing, how they are adapting to changing conditions, and their likely goals. This STTR topic seeks novel approaches to building scalable models of cyberspace threat actor behaviors that lend themselves to analysis by both humans and machines. The models should be autonomously fitted to data from existing sensors in order to detect and classify adversarial behaviors and infer their goals. Furthermore, the models should automatically detect changes in behaviors, such as the introduction of new tools or procedures. Scalability of the proposed solution is an important consideration since the data sets are known to be very large.
PHASE I: Determine the feasibility of analyzing cyberspace observables, comparing them to behavior models, detecting the incorporation of new tools and procedures, and inferring adversaries’ goals. Identify classes of adversarial behavior that lend themselves to this analysis. Develop a detailed design for an intelligent system that collaborates with a human operator to identify the likeliest goals for an adversarial operation. Develop a Phase II plan.
PHASE II: Develop a prototype system that can classify adversarial behaviors, detect changes over time, and correlate those changes to known events. Demonstrate the prototype in a realistic information technology (IT) environment. Study and describe how this capability may be augmented with autonomous responses such as defensive countermeasures or deception.
PHASE III: Commercialize the technology. The solution developed in Phase II will be productized for general use across Government, commercial, and research organizations. Examples of such applications may include verification and validation of network security protocols, the development of objective criteria for assessing behavioral changes following TTPs, or the development of experimentation testbeds for cyber operations training.
REFERENCES:1. Maymí, F., Bixler, R., Jones, R., & Lathrop, S. "Towards a definition of cyberspace tactics, techniques and procedures." Big Data (Big Data), 2017 IEEE International Conference .; 2. Stillions, R. “On TTPs.” Blogspot, 22 Apr. 2014, ryanstillions.blogspot.com/2014/04/on-ttps.html; 3. Santarcangelo, M. “Exploit Attacker Playbooks to Improve Security.” CSO from IDG, 12 July 2017. www.csoonline.com/article/3207692/leadership-management/exploit-attacker-playbooks-to-improve-security.html
KEYWORDS: Cyberspace Operations; Machine Learning; TTP; Tactics, Techniques, And Procedures
TECHNOLOGY AREA(S): Info Systems, Battlespace
OBJECTIVE: Develop reduced order modeling (ROM) techniques for geophysical fluid dynamics models that will enable their use aboard unmanned platforms, including the ability to assimilate local environmental data into the model state. Computational efficiency (low power/memory) and the ability to provide estimates of the flow field to the local platform control system are required.
DESCRIPTION: The Navy operates high-resolution (O(km)) environmental models to provide forecasts of the operational environment to ensure safe and efficient maritime operations. These prediction systems assimilate observations from both in situ and space-based sensors and are run on High Performance Computing platforms. The resulting data sets are large, and the relevant weather and ocean forecast products must be transmitted to naval platforms for use. ROM methods are sought that can predict the evolution of the maritime environment around a platform at sea, incorporating in situ environmental observations to forecast the four-dimensional ocean fields (i.e., temperature, salinity, and velocity vectors) with sufficient fidelity to allow the platform to exploit the information (e.g., optimal path planning or positioning within the water column). The capability would enable unmanned platforms to sense the local environment and use that information to estimate the ocean conditions for use in autonomous command and control algorithms. Given limited power and computational capability on these systems, ROM techniques are likely to be useful for this application if they are able to provide a useful characterization with limited observational data. The ROM capability must be capable of operating in real time over iridium data rates, incorporating in situ observations, and returning a solution for the predicted ocean environmental information in time to enable exploitation by the platform. The Phase II effort will require implementation of the developed techniques aboard an unmanned platform. For this purpose, commercial systems of similar capabilities to existing platforms are sufficient – prototyping aboard actual naval unmanned systems is not required. Coordination and testing of software and techniques using existing GFE platforms will be possible but not required. The desired size and power constraints would be aimed for a light weight Unmanned Underwater Vehicle (UUV) class vehicle.
PHASE I: Design and develop ROM method(s) for prediction or reconstruction of oceanographic fields appropriate for use by an in situ unmanned platform. Estimate the capabilities of the proposed method(s). Determine the feasibility of the proposed method(s). Develop a Phase II plan.
PHASE II: Develop tools that incorporate the output of the ROM solution into the autonomous control system of the vehicle. Demonstrate the usage of the predicted environmental information to inform the control algorithm. Integrate and test prototype ROM tools onboard surrogate unmanned systems, which may include platforms operating on or below the ocean surface.
PHASE III: Finalize and transition the ROM tool to platform developers to test on U.S. Navy unmanned systems. This technology has the potential to provide better situational awareness for unmanned platforms deployed at sea. Other federal agencies and the ocean technology industry operate unmanned systems that could make use of this capability.
REFERENCES:1. Majda, A.J. and Qi, D. “New Strategies for Reduced-Order Models for Predicting the Statistical Responses and Uncertainty Quantification in Complex Turbulent Dynamical Systems.” SIAM Rev., 2017a. http://www.ipam.ucla.edu/abstract/?tid=14237; 2. Subramani, D.N., Wei, Q.J., and Lermusiaux, P.F.J. “Stochastic Time-Optimal Path-Planning in Uncertain, Strong, and Dynamic Flows.” Computer Methods in Applied Mechanics and Engineering, 333, 218–237, 2018. http://mseas.mit.edu/publications/PDF/Subramani_et_al_stochastic_timeoptimal_planning_CMAME2017.pdf; 3. Feppon, F. and Lermusiaux, P.F.J. “A Geometric Approach to Dynamical Model-Order Reduction.” SIAM Journal on Matrix Analysis and Applications, 2017. https://arxiv.org/pdf/1705.08521.pdf
KEYWORDS: Reduced Order Modeling; ROM; Ocean Modeling; Data Assimilation; Dynamical Systems; Unmanned Underwater Vehicle; UUV; Unmanned Surface Vehicle; USV; Autonomy
TECHNOLOGY AREA(S): Chem Bio_defense, Sensors
OBJECTIVE: Develop a fully-packaged short-wave infrared (SWIR, 900-1600 nm) spectrometer that uses photonic integrated circuit (PIC) technology and meets these requirements: compact (handheld, < 0.5 kg), compatible with a single-mode optical source, broadband (>200 nm, >128 channels), precise (<1 nm resol.), efficient, and fabricated using a PIC foundry.
DESCRIPTION: PICs are emerging as low-cost replacements for fiber-optic systems that use many individual fiber components, as well as a number of bulk optical systems. The DoD is developing sensors based on Raman, fluorescence, and absorption spectroscopies for areas such as chemical warfare agent detection, in situ warfighter health analysis, and environmental monitoring. However, the critical part of PIC spectroscopy, the spectrometer, does not currently meet the needs of DoD spectroscopic sensors. Successful demonstrations of critical PIC components, such as arrayed waveguide gratings (AWGs), detectors, or edge couplers have not been integrated into a single fully-packaged SWIR spectrometer using a PIC foundry. A suitable PIC will have: total package size (target: < 100 cm3); PIC area (target: < 4 cm2); and efficiency (target: > 10% quantum efficiency). Such a PIC spectrometer could then be integrated with PIC transducers and on-chip sources for a fully integrated biological or chemical detector.
PHASE I: Design and analyze a proposed approach for a PIC-based SWIR spectrometer based on a center wavelength between 1150 nm and 1250 nm. Important design criteria are optical bandwidth (target: > 200nm); channels (target: >128); channel-to-channel extinction ratio (target: >30 dB); operation temperature (target: -10 deg C); resolution (target: < 1nm full width at half maximum or FWHM). Demonstrate feasibility of the concept with S-parameter circuit (or equivalent) analysis based on Process Design Kit (PDK) component and/or custom component specifications for a specific PIC foundry. Ensure that the proposed device uses single-mode waveguide as optical input. Electronic detection can be done either with on-chip photodetectors (“active” PIC) with appropriate complementary metal-oxide-semiconductor (CMOS) backplane for readout, or with off-chip detection (“passive” PIC) with detector array optically coupled to PIC. Develop a Phase II plan.
PHASE II: Fabricate, assemble, package, and test the proposed approach described in Phase I. Final packaging should be clearly described and should include fiber-coupling to input waveguide for optical testing. Test the prototype first with a polarized white light source coupled to a single-mode optical fiber; and second with a polarized pump at 1064 nm co-propagating with simulated (or real) Raman signal approximately 10^8 times weaker, also in a single-mode optical fiber. Evaluate the prototype against the criteria listed in the Phase I description. If the prototype fails to meet the targets listed above, perform a root cause analysis, and describe/report design trade-offs necessary to reach all of the performance targets. Analyze the prototype design and packaging to determine additional engineering steps required to achieve (i) lower temperature operation (dual-stage thermoelectric cooler (TEC) down to -40 deg C); (ii) wider wavelength range (target 400 nm) and/or a center wavelength near 950 nm (instead of ~1200 nm); (iii) more output channels (512 channels); (iv) and lower resolution (< 0.25 nm). Describe a realistic path for the integration of this component into the component library PDK for a PIC foundry, and provide realistic estimates of the total cost to manufacture this component.
PHASE III: Integrate a PIC spectrometer with a PIC laser source and a PIC transducer for chemical or biological agent detection to create a chip-scale detection system that can be deployed to virtually every warfighter or unmanned detection platform in the DoD. This deployment can be done with the assistance of the contractor via the design of the full PIC system, the submission of the design to the PIC foundry, and the test and evaluation of the manufactured system. A PIC spectrometer is an essential component of a PIC-based sensor. While small Size, Weight, and Power (SWaP) sensors for trace concentrations of chemical warfare agents or dilute bioagents have important applications for the DoD, the technology has many commercial applications as well. Many health science sensors, such as breath analysis or illicit drug screening can benefit from the same sensing technology. Also, environmental applications such as methane leak detection or air quality monitoring could also benefit from this low SWaP sensing platform.
REFERENCES:1. Subramanian, A.Z. et al. “Silicon and silicon nitride photonic circuits for spectroscopic sensing on-a-chip.” Photonics Research 3, October 2015, B47-59. doi: 10.1364/PRJ.3.000B47; 2. Wang, R. et al. “III-V-on-silicon photonic integrated circuits for spectroscopic sensing in the 2-4 um wavelength range.” Sensors 17, 1788 (2017). doi: 10.3390/s17081788; 3. Stievater, T.H. et al. “Chemical sensors fabricated by a photonic integrated circuit foundry.” SPIE 10510, 1051001 (2018). doi: 10.1117/12.2294059
KEYWORDS: Photonic Integrated Circuit; Spectrometer; Spectroscopy; Infrared; Foundry; Detector
TECHNOLOGY AREA(S): Info Systems
OBJECTIVE: Develop information stream analysis models and analytic tools to detect, characterize, and visualize computational propaganda to detect influence campaigns and propaganda that target the emotions of anger, hate, fear, and disgust. Ensure that the proposed capability is able to indicate and analyze influence campaigns in progress and evaluate their potential impacts on target audiences.
DESCRIPTION: Operating in the information environment today is highly challenging for Navy, Marine Corps, and other military warfighters. The information environment includes multiple platforms, social communities, and topic areas that are polluted with disinformation and attempts to manipulate crowds, spread rumor, and instigate social hysteria. Polarization of crowds is a significant problem with nation-state actors conducting malicious campaigns to spread and amplify civil discontent and chaotic social dynamics—usually by manipulating the emotional mood of crowds. Hate, anger, disgust, fear, and social anxiety are heightened using computational propaganda. Current “sentiment” models are poorly suited to measuring emotional content in online media. These measures are not currently well synchronized with measurements of manipulation by information actors who are intent on subverting civil discourse and discrediting the messages of civil authorities. The current state-of-the-art in botnet detection merely identifies automated features such as identical content, identical targets, coordination of message dispersal, and similar measurable indicators. Hybrid or “cyborg” content distributors and distributors who use different types of artificial intelligence enhanced capabilities (“smart” botnets) make detecting manipulated discourses more difficult. Crowds of inflamed audiences can result from a relatively small “signal” of inflammatory texts, pictures, messages, and videos, amplified just enough to “catch hold” in an already unstable environment. This occurred in Sudan when messages about Benghazi in Libya caused mobs to attack embassies—with the British embassy set on fire, only hours after the first messaging began. Current state-of-the-art approaches rely on older algorithms (such as Lingusitc Inquiry and Word Count, LIWC) to evaluate messaging; more sophisticated models such as Ekman’s model of emotions or Russell’s circumplex model and Scherer’s update of the model [Refs 1, 2] have been used for measuring and evaluating emotions in blog posts. Natural Language Processing (NLP) models have also been used meaningfully in research settings [Ref 3]. “Feeling offended,” a complex emotional state, has also been studied by E’Errico and Poggi [Ref 4]. Typically, bot-detection methods today indicate the presence or absence of bots, with some degree of accuracy [Ref 5]. Sentiment analysis capabilities are very limited to at best a three-state scale (positive, negative, neutral). In crisis situations and emergencies, sentiment analysis is of little value. It cannot tell the operator what kinds of negativity are in play or what types of emotional issues are being expressed. Anger, fear, hate, disgust, and propaganda-fueled discourses require further unpacking. Communicators need to identify the gists, the stories, and ultimately, the narratives that are in play as well as have available effective models of complex emotions in order to develop an appropriate understanding of an influence campaign. The scope of the topic is to develop tools that can find the existence of an attempt to influence/mislead people through social networks or other IT means, assess the emotions it’s triggering, and the level of the reaction in real-time and provide this info to multiple network users in a cloud environment Technologies proposed under this topic might include models and analytic tools for measuring the emotional content and logical fallacies such as ad hominem arguments, ground shifts, and other rhetorical devices [Ref 6] commonly used in propaganda techniques online. Capabilities to identify propaganda may be separate or synchronized with capabilities to identify, evaluate, and describe emotional content. Methods and techniques for creating baselines of emotional responses of audiences to civil authority messaging would be helpful. Initial algorithms, models, and tools are expected to use simulated data, though real-world cases can be used in development. Capabilities that include cultural aspects of crowd manipulation in non-English speaking contexts would be considered particularly responsive to this topic.
PHASE I: Develop prototype algorithms, models, and tools that use Government supplied synthetic data supplemented by case studies to demonstrate a proof of concept to identify computational propaganda content and emotional valences of messages in Twitter, including indicators of manipulation and the capability to segment actor communities (i.e., botnet, bot-enhanced, human). Integrate simple models of emotions (such as Ekman’s model) and consider using more sophisticated, finer grained models (such as Russell’s model with Scherer’s updates). Note: These models are considered to be illustrative; developers are free to use other models of emotions. Ensure that the prototype successfully identify sets of messages, gists, and stories; determine their emotional content in a general sense; estimate whether these sets are likely to represent manipulated discourse; and visualize the discourse by gist (topics) and story (such as URL). Develop a Phase II plan.
PHASE II: Develop the models of emotion and propaganda so as to be able to identify computational propaganda, its emotional valences and arousal state. Estimate the degree of artificial manipulation present in gists and stories present in live information streams from Twitter, websites, and blogs. Ensure that model results are exportable to other tools (such as social network tools, visualization tools, databases and dashboards). Make available to the Navy a user-friendly, working prototype with built-in help capabilities for testing and evaluation in a cloud-based environment by multiple users in the context of an online military virtual tabletop as the final technical demonstration of this project. Conduct and complete model development and validation prior to Phase III.
PHASE III: Apply the knowledge gained in Phase II to further develop the interface, capabilities, and training components needed to make the technologies able to transition to military customers. Make the technologies available on an existing cloud platform of the customer’s choosing (e.g., SUNNET, Navy Tactical Cloud, Amazon Cloud) working with cloud owners to deliver a subscription-based tool interoperable with other tools in enclave settings. Expand and develop the model to cope with real-time information flows and evolving information tactics. The problem of detecting influence campaigns designed to disrupt the credibility of organizations is highly needed, world-wide. Western humanitarian organizations, international brands, and civil society organizations are continually under assault in the information environment by “trolls” and other malign actors for political and apolitical purposes. Currently there is little available on the market for this capability; scientific models of emotional modeling applied to social media are relatively new.
REFERENCES:1. Langroudi, George, Jourdanous, Anna, and Li, Ling. “Music Emotion Capture: sonifying emotions in EEG data.” Symposium on Emotion Modeling and Detection in Social Media and Online Interaction. 5 April 2018, University of Liverpool. https://www.emotiv.com/independent-studies/music-emotion-capture-sonifying-emotions-in-eeg-data/; 2. Harvey, Robert, Muncey, Andrew, and Vaughan, Neil. “Associating Colors with Emotions Detected in Social Media Tweets.” Symposium on Emotion Modeling and Detection in Social Media and Online Interaction. 5 April 2018, University of Liverpool. https://docplayer.net/82902361-Symposium-on-emotion-modelling-and-detection-in-social-media-and-online-interaction.html; 3. D’Errico, Francesca and Poggi, Isabella. “The lexicon of being offended.” Symposium on Emotion Modeling and Detection in Social Media and Online Interaction. 5 April 2018, University of Liverpool. https://www.researchgate.net/publication/326096901_The_lexicon_of_feeling_offended; 4. Badugu, Srinivasu and Suhasini, Matla. “Emotion Detection on Twitter Data Using Knowledge Base Approach.” International Journal of Computer Application, Volumbe 162, No 10. March 2017. https://pdfs.semanticscholar.org/6698/5a996eab1e680ffdd88a4e92964ac4e7dd56.pdf; 5. Agarwal, Nitin, Al-Khateeb, Saamer, et. Al. “Examining the Use of Botnets and Their Evolution in Propaganda Dissemination.” Defense Strategic Communications. Vol 2, Spring 2017. https://www.stratcomcoe.org/nitin-agarwal-etal-examining-use-botnets-and-their-evolution-propaganda-dissemination; 6. Dijck, Jose and Poell, Thomas. “Understanding Social Media Logic.” Media and Communication, August 2013, Vol 1, Issue 1,pp. 2-4. https://www.cogitatiopress.com/mediaandcommunication/article/view/70/60
KEYWORDS: Social Media, Computational Propaganda, Crowd Manipulation, Cocial Hysteria, Rumor
TECHNOLOGY AREA(S): Electronics
OBJECTIVE: The objective of this topic is to develop innovative alternatives to legacy radio frequency (RF) transmit and receive antenna designs to reduce the visual signature in both land mobile and fixed site applications.
DESCRIPTION: Legacy antenna designs currently employed with tactical radio equipment present an easily identified visual signature, limit mounting options, and reduce operational flexibility when employed in land mobile and fixed site applications. This topic seeks innovative research and development to provide a feasible alternative design solutions. Design considerations include: 1. Minimize form factor (size, weight, and power) to allow ease of transportation and flexible installation criteria. 2. Maximize compatibility with commonly used military radio frequencies. 3. Minimize external power requirements or use of common battery types. 4. Maximize all-weather operations. 5. Maximize the capability of utilizing non-traditional forms for antenna manipulation. 6. Maximize decibel gain.
PHASE I: Conduct a feasibility study to assess what is in the art of the possible that addresses the design considerations included in the above paragraph entitled “Description.” As a part of this feasibility study, the proposers shall evaluate system concepts that provide a compact form factor “resonator” to transform existing structures and materials commonly available on motor vehicles and building constructions into a radio transmit and receive antenna compatible with commonly used RF bands. Analysis shall address the effect of interaction with different structural materials (steel, aluminum, copper tape, etc.) Analysis shall also address performance attributes including: 1. Notional RF Resonator directivity 2. Notional RF Resonator efficiency 3. Notional RF Resonator frequency response bandwidth 4. Notional RF Resonator compatibility with existing communication architectures (GSM, LTE, etc.) 5. Notional RF Resonator frequency range compatibility (Very High Frequency, Ultra High Frequency, L-Band, S-Band, etc.) 6. Notional RF Resonator data throughput potential. The objective of this USSOCOM Phase I STTR effort is to conduct and document the results of a thorough feasibility study to investigate what is in the art of the possible within the given trade space that will deliver the described technology. The feasibility study should investigate all known options that meet or exceed the performance parameters specified in this write up. It should also address the risks and potential payoffs of the innovative technology options that are investigated and recommend the option that best achieves the objective of this technology pursuit. The funds obligated on the resulting Phase I SBIR contracts are to be used for the sole purpose of conducting a thorough feasibility study using scientific experiments, academic analysis, and laboratory studies as necessary. Operational prototypes will not be developed with USSOCOM SBIR funds during Phase I feasibility studies. Operational prototypes developed with other than SBIR funds that are provided at the end of Phase I feasibility studies will not be considered in deciding what firm(s) will be selected for Phase II.
PHASE II: Develop, install, and demonstrate a prototype system determined to be the most feasible solution during the Phase I feasibility study of a Low Visibility RF Resonator.
PHASE III: This system could be used in a broad range of military applications. Additional applications include U.S. law enforcement, U.S. border patrol, and search and rescue of persons by U.S. first responders in local / state / or federal capacity.
1: Full listing of Army Field Manuals: http://www.enlistment.us/field-manuals.
2: Headquarters Department of the Army Field Manual 6-02.43 titled "Signal Soldier’s Guide", dated March, 2009: https://usacac.army.mil/sites/default/files/misc/doctrine/CDG/cdg_resources/manuals/fm/fm6_02x43.pdf.
3: "Field Antenna Handbook", Department of Defense Electromagnetic Compatibility Analysis Center, dated June 1984: http://www.dtic.mil/dtic/tr/fulltext/u2/a155204.pdf.
4: "Tactical Radios - Multiservice Communications Procedures for Tactical Radios in a Joint Environment"
5: FM 6-02.72 (FM 11-1) dated June 2002: https://usacac.army.mil/sites/default/files/misc/doctrine/CDG/cdg_resources/manuals/fm/fm6_02x72.pdf.
KEYWORDS: Antenna, Radio Frequency, Resonator, Radio Communications, Satellite Communications Lasers, Pointers