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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. New Paradigms in High Pressure Combustion Dynamics Prediction and Control

    SBC: HYPERCOMP INC            Topic: AF12BT15

    ABSTRACT: Stability phenomena that are of vital interest in liquid rocket motor development involve a confluence of diverse physics and interactions across many system components. Any comprehensive, self-consistent numerical model is burdened by a very large computational mesh, stiff unsteady processes which limit permissible time step, and the need to perform tedious, repeated calculations for a ...

    STTR Phase I 2013 Department of DefenseAir Force
  2. Semi-Analytic Fresnel Propagation Simulation

    SBC: MZA ASSOCIATES CORPORATION            Topic: AF18BT004

    Wave-optics simulations are critical tools for analysis of laser directed energy systems. The primary method for conducting these simulations is to evaluate the Fresnel diffraction integral using the angular spectrum method based on the fast Fourier transform (FFT). While FFTs are considered computationally efficient, their use in the Fresnel integral results in difficult grid constraints includin ...

    STTR Phase I 2019 Department of DefenseAir Force
  3. Characterization of the Aero-Structure Environment of a Transonic Scaled Fighter (CASE-TSF)

    SBC: NEXTGEN AERONAUTICS, INC.            Topic: AF12BT12

    ABSTRACT: NextGen Aeronautics Inc. proposes use of rapid prototyping (RP) technologies, design process improvements, and novel sensing technologies to significantly reduce time and cost of transonic aeroelastic wind tunnel model development and improve their direct correlation to CFD data. The use of modern RP technologies will allow for model design variations such as variable modulus (stiffness ...

    STTR Phase I 2013 Department of DefenseAir Force
  4. Toolset For Prediction of Carbon-Carbon Aeroshell Properties Based On Constituent Materials And Manufacturing Process Parameters

    SBC: ATA ENGINEERING, INC.            Topic: AF19AT021

    Carbon-carbon (C-C) composites are used in the fabrication of aeroshells and thermal protection systems (TPS) in hypersonic and atmospheric reentry applications because they maintain their strength at elevated temperatures and have desirable thermal conductivity properties. Although these materials have been used in mission-critical components for decades, the effects of variations in processing m ...

    STTR Phase I 2019 Department of DefenseAir Force
  5. A High Performance and Cost Effective Ultra High Performance Concrete

    SBC: i2C Solutions, LLC            Topic: AF12BT04

    ABSTRACT: Adversarial installations, such as those housing the means for nuclear weapons production, are increasingly being constructed in heavily fortified locations and often using ultra high performance concrete (UHPC) as the construction material. As such, the U.S. Air Force has considerable interest in further developments of ultra high performance concrete (UHPC) to maintain an advantage o ...

    STTR Phase I 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. Clearance of Aircraft Stores Carriage under Uncertainty

    SBC: CMSOFT, INC.            Topic: AF18BT008

    The main objective of this STTR effort is three-fold. First, to develop and demonstrate in Phase I a Bayesian methodology exploiting flight test data in order to identify critical store carriage tests and clear non-critical store carriage configurations by updated analysis. Second, to extend in Phase II the scope of this methodology to viscous flows with analysis enriched using analytical sensitiv ...

    STTR Phase I 2019 Department of DefenseAir Force
  8. Scaled Transonic Dynamic Aeroelasticity Through Wind Tunnel Testing (ST-DAWTT)

    SBC: CREATIVE AERO ENGINEERING SOLUTIONS INC.            Topic: AF12BT12

    ABSTRACT: Under this collaborative effort, Creative Aero Engineering Solutions (CAES) and its academic partner University of California Los Angeles (UCLA) are pleased to team on the research entitled"Scaled Transonic Dynamic Aeroelasticity through Wind Tunnel Testing (ST-DAWTT),"consisting of a novel approach for characterizing the transonic aeroelastic environment of a full-scale fighter in the ...

    STTR Phase I 2013 Department of DefenseAir Force
  9. Wave-Optic Propagation Computation Enabled by Machine Learning Algorithms (WOPA)

    SBC: Luminit LLC            Topic: AF18BT004

    To address the U.S. Air Force need for Developing innovative wave-optics Propagation methods to model laser systems that are faster, efficient and more accurate, Luminit, LLC, and University of Southern California (USC) propose to develop Wave-Optic Propagation Computation Enabled by Machine Learning Algorithms (WOPA). The proposed algorithms will be based on cutting off redundant frequencies upon ...

    STTR Phase I 2019 Department of DefenseAir Force
  10. Virtual Reality for Multi-INT Deep Learning (VR-MDL)

    SBC: INFORMATION SYSTEMS LABORATORIES INC            Topic: AF19AT010

    Recent advances and successes of deep learning neural networks (DLNN) techniques and architectures have been well publicized over the last several years. Voluminous, high-quality and annotated training data, or trial and error in a realistic environment, is required to achieve the promised performance potential of DLNNs. Unfortunately for DoD and/or Intelligence Community (IC) applications of mult ...

    STTR Phase I 2019 Department of DefenseAir Force
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