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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. Hybrid Energy Harvesting Systems

    SBC: Prime Photonics, LC            Topic: AF10BT22

    ABSTRACT: For this Phase II STTR effort, Prime Photonics and Virginia Tech propose to demonstrate a fully packaged hybrid photovoltaic/magneto-thermoelectric (PV/MTG) panel with improved energy conversion efficiency designed for solar powered air vehicles. In addition to acting as an active thermal backplane for the PV, the MTG is designed to maximize thermal to electrical conversion from the av ...

    STTR Phase II 2013 Department of DefenseAir Force
  2. Highly-Scalable Computational-Based Engineering Algorithms for Emerging Parallel Machine Architectures

    SBC: RNET TECHNOLOGIES INC            Topic: AF10BT13

    ABSTRACT: RNET and The Ohio State University propose to use algorithmic modifications and multi-level parallelization techniques and tools to improve the scalability of the aero-line/aero-elastic coupled CFD/CSD codes relevant to the DoD/AF (e.g., CREATE/Kestrel). The optimizations will address inter-node and intra-node parallelization to better target emerging compute architectures (e.g., multi ...

    STTR Phase II 2013 Department of DefenseAir Force
  3. Suppression of Wind Turbine Clutter from Radar Data

    SBC: MATRIX RESEARCH INC            Topic: AF12BT05

    ABSTRACT: It is well known that wind turbine clutter (WTC) presents a significant challenge to detecting targets in civilian and military applications. The large radar cross section (RCS) of wind turbines, combined with their significant range of Doppler spread, make traditional clutter mitigation techniques effectively useless. The objective of this Phase I effort is to develop a physically con ...

    STTR Phase I 2013 Department of DefenseAir Force
  4. Exploitable Physics for Recognition and Classification

    SBC: MATRIX RESEARCH INC            Topic: AF12BT06

    ABSTRACT: The objective of this effort is to develop innovative methods for deriving a sparse set of physical target features that can be used for exploitation of air to ground signature data collected from sensor systems including electro-optical, infrared, and laser radar. Current classification methods require near exact replication of the original imaging parameters, or extensive modeling in ...

    STTR Phase I 2013 Department of DefenseAir Force
  5. Autonomic Performance Assurance for Multi-Processor Supervisory Control

    SBC: COLORADO ENGINEERING INC.            Topic: OSD11T01

    Multi-processor computing systems are growing in capacity and usage. They encompass multiple, distributed implementations as well as heterogeneous, embedded computing architectures. The processing density enabled by such approaches holds promise for unmanned combat air vehicles (UCAVs) with their plethora of mission sensors and command and control processing requirements. However, the software ...

    STTR Phase II 2013 Department of DefenseAir Force
  6. Development of a Rapidly Deployable Scaled Fighter for Aeroelastic Research

    SBC: MAINSTREAM ENGINEERING CORP            Topic: AF12BT12

    ABSTRACT: Experimental testing of dynamic models has been performed for more than 50 years and a wealth of data exists for individual models. However, this data is often either restricted as proprietary or is not suitable for CSE tool validation as a result of incomplete model or test information. Mainstream Engineering proposes to design, fabricate, and test a scaled fighter for aeroelastic ...

    STTR Phase I 2013 Department of DefenseAir Force
  7. Spatiotemporal Nonlinear Data Analysis Tools and Reduced Order Models for Prediction of High-Pressure Reacting Flow Dynamics and Control

    SBC: SPECTRAL ENERGIES LLC            Topic: AF12BT15

    ABSTRACT: This Phase-I research effort is designed to forward the engineering investigation of the dynamics and control of turbulent combustion in high-pressure combustion systems by developing a set of game-changing nonlinear analysis tools that can significantly improve the post-processing speed and intelligent data mining of large numerical or experimental data sets. Moreover, a system based o ...

    STTR Phase I 2013 Department of DefenseAir Force
  8. Time series prediction for satellite ballistic coefficients

    SBC: OMITRON INC            Topic: AF10BT36

    ABSTRACT: The leading errors in computing future positions of satellites in Low Earth Orbit are generally due to inaccuracies in the thermospheric density and the prediction thereof. The use of Dynamic Calibration Atmosphere has reduced these traditional sources of error and variations seen in ballistic coefficients can now be attributed to unmodeled satellite frontal area changes. When the orb ...

    STTR Phase II 2013 Department of DefenseAir Force
  9. Adaptive multi-sensor wide area situational awareness system- MP 85-12

    SBC: METRON INCORPORATED            Topic: AF12BT14

    ABSTRACT: Existing machine learning algorithms have difficulty using all available data about a problem. This STTR will develop a new algorithm that can make full use of all available data, whether that data is labeled or not, and even when some data types or data resolutions are not available during operation. BENEFIT: This STTR will develop a novel machine learning algorithm for reasoning abo ...

    STTR Phase I 2013 Department of DefenseAir Force
  10. Operating System Mechanisms for Many-Core Systems

    SBC: SECURBORATION, INC.            Topic: OSD11T04

    In the Phase I portion of this STTR, Securboration and renowned multicore expert Dr. Frank Mueller from North Carolina State University designed, developed, and benchmarked the proof-of-concept Pico-kernel Adaptive and Scalable Operating-system (PICASO) for many-core architectures. The Securboration Team took a scientific, experimentation-based approach to identifying and resolving shortcomings wi ...

    STTR Phase II 2013 Department of DefenseAir Force
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