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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. Blending Classical Model-Based Target Classification and Identification Approaches with Data-Driven Artificial Intelligence

    SBC: TOYON RESEARCH CORPORATION            Topic: N18BT033

    Toyon Research Corp. and the University of California propose to develop innovative algorithms to perform automatic target recognition (ATR), localization, and classification of maritime and land targets in EO/IR, LiDAR, and SAR imagery. The proposed algorithms are based on recent developments made at the University of California, which outline a strong mathematical framework for naturally blendin ...

    STTR Phase I 2019 Department of DefenseNavy
  2. Cervical Spine Health Improvement Products

    SBC: SWITCHBOX INC            Topic: DHA18B001

    Most standard-of-care tools and techniques for evaluating neck disorders are subjective, unreliable, and do not provide actionable information for providers, payers, and organizations to deliver efficient and effective care. This lack of objective neck he

    STTR Phase I 2019 Department of DefenseDefense Health Agency
  3. Advanced Command and Control Architectures for Autonomous Sensing

    SBC: TOYON RESEARCH CORPORATION            Topic: N18BT030

    We propose to develop an innovative open architecture for the semi-autonomous command and control (C2) of teaming Unmanned Aircraft Systems (UAS). The proposed architecture, based upon Toyon’s Decentralized Asset Management system, supports both centralized and decentralized fusion and control autonomy solutions as well as hybrids approaches. Leveraging STANAG-4586, TCP/IP, UPD, Google™ protob ...

    STTR Phase I 2019 Department of DefenseNavy
  4. Out-of-Oven Aerospace Composites

    SBC: CORNERSTONE RESEARCH GROUP INC            Topic: N18BT031

    Large aerospace composite structures currently require autoclaves and ovens to achieve desired performance which are expensive to purchase, costly to operate, and often limit part size and production rate. Ovens and autoclaves rely on convective heating which is inefficient, consumes large amounts of energy, and can be difficult to predict. Alternative cure processes using external heaters or hot ...

    STTR Phase I 2019 Department of DefenseNavy
  5. Carbon Nanotube-Based Heater Coatings for Processing of Thermosetting and Thermoplastic Composites

    SBC: MAINSTREAM ENGINEERING CORP            Topic: N18BT031

    For this research program, Mainstream will collaborate with Colorado State University (CSU) to develop a nanostructured heater capable of curing aerospace grade composites out-of-autoclave (OOA). The use of autoclaves is the primary cost driver in composite manufacturing due to size limitations, long processing times, and inefficient energy usage. Therefore, the Navy is looking to develop a nanost ...

    STTR Phase I 2019 Department of DefenseNavy
  6. Optimization of Fatigue Test Signal Compression Using the Wavelet Transform

    SBC: ATA ENGINEERING, INC.            Topic: N18BT029

    Traditional approaches to accelerated fatigue testing rely on heuristic methods with thresholds based mostly on experience and engineering judgment. These methods generally do not apply to the multiaxial dynamic loading situations characteristic of most aerospace applications and often result in uncharacteristic fatigue damage and failure modes during testing. To overcome the limitations of tradit ...

    STTR Phase I 2018 Department of DefenseNavy
  7. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: ARCTOS Technology Solutions, LLC            Topic: DLA18A001

    Universal Technology Corporation (UTC) has teamed with the University of Dayton Research Institute (UDRI), Stratonics, and Macy Consulting to demonstrate not only the transitionability into commercial systems, but also to develop the data analytics and monitoring and control requirements to extract the full value fromseveral sensors, including the Stratonics ThermaViz, acoustic and profilometry se ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  8. Power and Propulsion System Optimization

    SBC: CORNERSTONE RESEARCH GROUP INC            Topic: N18AT012

    Unmanned underwater vehicles (UUVs) are currently limited in the type of missions they can perform. Limited available power limits which sensors can be run or for how long, and also limits the duration and range of the mission. More efficient propulsion systems would increase the power available to the UUV payload. Improved power distribution systems and control systems would also increase the ava ...

    STTR Phase I 2018 Department of DefenseNavy
  9. An Integrated Materials Informatics/Sequential Learning Framework to Predict the Effects of Defects in Metals Additive Manufacturing

    SBC: Citrine Informatics, Inc.            Topic: N18AT013

    In this project, Citrine Informatics and the ADAPT Center at the Colorado School of Mines propose to build an informatics-driven system to understand the effects of defects in additive manufactured parts. The entire history of each sample will be captured on this system; from specific printing parameters and details of precursor materials through to part characterizations and performance measureme ...

    STTR Phase I 2018 Department of DefenseNavy
  10. New Integrated Total Design of Unmanned Underwater Vehicles (UUVs) Propulsion System Architecture for Higher Efficiency and Low Noise

    SBC: CONTINUOUS SOLUTIONS INC            Topic: N18AT012

    In this proposal, a meta model-based scaling law will be used to represent each system component. A components meta model-based scaling law describes the tradeoffs between performance metrics for that component or subsystem as a function of its ratings in relation to the system. This greatly reduces the number of degrees of freedom for each component, and at the same time, retains the information ...

    STTR Phase I 2018 Department of DefenseNavy
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