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Award Data

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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. 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
  2. Power-Dense Electrical Rotating Machines for Propulsion and Power Generation

    SBC: CONTINUOUS SOLUTIONS LLC            Topic: N19AT007

    The primary objective is to develop electric machine/drive topologies and power architectures that achieve the power densities required for 50% more power without the increase in weight or space requirements. In addition to PMSM-based designs, two new machine topologies will be considered. The first is a trapped flux coreless (TFC) machine that utilizes superconducting pucks made of YBCO to produc ...

    STTR Phase I 2019 Department of DefenseNavy
  3. Probabilistic Prediction of Location-Specific Microstructure in Turbine Disks

    SBC: SCIENTIFIC FORMING TECHNOLOGIES CORPORATION            Topic: N10AT028

    While there are established methods available in determining the fatigue life of critical rotating components, there is still room for improvement for better understanding and prediction of life limiting factors. Improved risk assessment of jet engine disk components would require probabilistic modeling capability of the evolution of microstructural features, residual stresses and material anomali ...

    STTR Phase I 2010 Department of DefenseNavy
  4. Probabilistic Prediction of Location-Specific Microstructure in Turbine Disks

    SBC: UES INC            Topic: N10AT028

    Thermo-mechanical processes of turbine disks have been progressively improved to meet microstructural requirements tailored for advanced, sustainable high temperature performances. However, the chemistry of typical Ni-base turbine disk alloys is very complex, and yields a variety of phases and microstructural anomalies under different thermo-mechanical heat treatments. These microstructural hetero ...

    STTR Phase I 2010 Department of DefenseNavy
  5. Process to Mitigate Catastrophic Optical Damage to Quantum Cascade Lasers

    SBC: IRGLARE LLC            Topic: N19AT004

    The development of a catastrophic optical damage model for quantum cascade lasers describing instantaneous laser damage at high optical power levels is proposed. The model will be validated by comparison to experimental data. Based on obtained results, changes to laser design and laser fabrication resulting in an increased damage threshold will be implemented. The work will ultimately result into ...

    STTR Phase I 2019 Department of DefenseNavy
  6. Progressive Model Generation for Adaptive Resilient System Software

    SBC: SECURBORATION, INC.            Topic: N13AT014

    Complex software systems are typically developed by disparate engineering teams working concurrently. At the same time, software requirements are frequently dynamic, evolving even during active development cycles. Discrepancies between how software is defined and how it is implemented at the modular level can cascade into critical system errors when modules are integrated. More troubling is that i ...

    STTR Phase I 2013 Department of DefenseNavy
  7. Seamless Wireless Charging of Micro and Small Unmanned Aerial System Through Local Power Transmission Infrastructure

    SBC: EH GROUP INC            Topic: N19AT019

    Wireless charging of unmanned aerial system (UAS) platforms from the environment has the potential to greatly increase flight and mission times. A promising option is to use electromagnetic fields from the power transmission infrastructure as an energy source. EH Group and the University of Alabama propose a design for UAS wireless charging in the near-field environment of the commercial power tra ...

    STTR Phase I 2019 Department of DefenseNavy
  8. Situational Awareness as a Man-Machine Map Reduce Job

    SBC: SOAR TECHNOLOGY, LLC            Topic: N13AT024

    Improving situational awareness and accuracy of decisions in complex missions relying on streaming open-source data requires scalable information extraction and fusion in collaboration between Man and Machine reasoning. SoarTech, with its proven track-record of basic and applied research and transition into actual deployment, will bring forward advanced imagery and text processing technology integ ...

    STTR Phase I 2013 Department of DefenseNavy
  9. Situational Awareness for Mission Critical Ship Systems

    SBC: IERUS TECHNOLOGIES INC            Topic: N18AT009

    The US Navy operates a vast fleet of combat and support vessels with complex power control systems under the control and decision authority of human operators. Several current resources such as SPY-1D radar and Vertical Launch System (VLS) and future resources such as railgun, AMDR, and high energy laser (HEL) are energy hungry, exceeding current and planned power generation capability when deploy ...

    STTR Phase I 2018 Department of DefenseNavy
  10. System for Nighttime and Low-Light Face Recognition

    SBC: POLARIS SENSOR TECHNOLOGIES INC            Topic: SOCOM18A001

    The objective of this proposal is to develop instrumentation and algorithms for acquiring facial features for facial recognition in low- and no-light conditions.We will use cross-spectrum matching by exploiting infrared polarimetric imagery which tends to show features that match more closely visible imagery than conventional infrared.In addition to thermal infrared, we will also test subjects in ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
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