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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

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. Operational Sand and Particulate Sensor System for Aircraft Gas Turbine Engines

    SBC: HAL Technology, LLC            Topic: N18AT023

    Gas turbine engines with prolonged exposure to sand and dust are susceptible to component and performance degradation and ultimately engine failure. Hal Technology’s proprietary, compact, rugged, flush-mounted, fiber-optic sensor platform measures particulate size, size distributions, and concentration for real-time engine health monitoring. Our proposed sensor will use an innovative hybrid disc ...

    STTR Phase I 2018 Department of DefenseNavy
  2. Hypersonic Experimental Aerothermoelastic Test (HEAT)

    SBC: GLOBAL AEROSPACE CORPORATION            Topic: AF16AT24

    The U.S. Air Force is interested in developing hypersonic vehicles including reusable transport aircraft, cruise missiles, and unmanned systems. Hypersonic flight regimes result in multifaceted and very difficult design challenges that can be encapsulated into an aerothermoelastic problem, which is a complex interaction of structural, thermal, and aerodynamic mechanisms. When a flexible structural ...

    STTR Phase II 2018 Department of DefenseAir Force
  3. Enhanced Sensor Resource Management Utilizing Bayesian Inference

    SBC: GCAS, Inc.            Topic: N19AT002

    This proposal describes the use of machine learning, data mining and Bayesian inference algorithms for incorporation into a surveillance aircraft cognitive radar system. The need for incorporation of higher-order uncertainty distributions will also be assessed. This will result in enhanced sensor resource management capability for surveillance aircraft radar.

    STTR Phase I 2019 Department of DefenseNavy
  4. Predictive Graph Convolutional Networks

    SBC: Arete Associates            Topic: N19AT017

    The US Navy’s mission to maintain, train and equip combat-ready Naval forces requires that decision makers have situational awareness of the capabilities, limitations, vulnerabilities/opportunities for adversarial and allied forces. An incomplete or inaccurate understanding of the current landscape and associated trends could lead to suboptimal mission readiness and outcomes. Analysts need tools ...

    STTR Phase I 2019 Department of DefenseNavy
  5. 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
  6. Data Analytics and Machine Learning Toolkit to Accelerate Materials Design and Processing Development

    SBC: CFD RESEARCH CORPORATION            Topic: N19AT020

    Navy has identified refractory high entropy alloy (RHEA) and metal additive manufacturing as two potential areas of interest. This includes designing new RHEA and optimizing metal additive manufacturing with specific material property requirements. Developing materials and processes via applying traditional experimentation and process optimization techniques is painfully slow due to the large numb ...

    STTR Phase I 2019 Department of DefenseNavy
  7. Integrated photonic Raman sensor on a chip

    SBC: PARTOW TECHNOLOGIES LLC            Topic: N19AT023

    A photonic integrated spectrometer based on high-index contrast thin film platform is proposed for Raman signal processing. Raman signal generation on the chip via waveguide collection integrated with a spectrometer is proposed to increase the efficiency and signal to noise ratio and significantly reduce cost and the size of Raman sensor systems. All components of the proposed Raman detection syst ...

    STTR Phase I 2019 Department of DefenseNavy
  8. Compact and Low-cost High Performance Spectrometer Sensor based on Integrated Photonics Technology

    SBC: ULTRA-LOW LOSS TECHNOLOGIES LLC            Topic: N19AT023

    Ultra-Low Loss Technologies (ULL Technologies) is proposing in collaboration with Prof. Arka Majumdar from University of Washington (UW), to develop a compact, low-cost spectrometer module to be used for chemical sensing applications and to be fabricated using the process design kit (PDK) available through AIM Photonics multi-project wafer run (MPW). The team will combine ULL Technologies expertis ...

    STTR Phase I 2019 Department of DefenseNavy
  9. Multi-lingual Social-media Crowd Manipulation Detector (MSCMD)

    SBC: BCL Technologies            Topic: N19AT024

    In this SBIR, BCL proposes developing a Multi-lingual Social-media Crowd Manipulation Detector (MSCMD). The MSCMD will use natural language processing techniques to detect terms that arouse emotion using information out of context to trigger reaction from the audience and move them to act.The MSCMD will operate in Asian languages using a Natural Language Processor for each language. The MSCMD will ...

    STTR Phase I 2019 Department of DefenseNavy
  10. 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
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