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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. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  2. Properties Investigation of High-MON Oxidizers for Use in Deep Space Exploration

    SBC: Frontier Aerospace Corporation            Topic: T9

    Rocket propulsion for deep space applications typically use liquid propellants for axial stage and attitude control systems. The most common propellants are hydrazine (N2H4) and monomethylhydrazine (MMH) (CH3N2H3) for the fuels, and nitrogen tetroxide (NTO) (N2O4) for the oxidizer. The freezing points of both hydrazine and NTO approach room temperature and require on-board electrical heaters for t ...

    STTR Phase I 2018 National Aeronautics and Space Administration
  3. System for Nighttime and Low-Light Face Recognition

    SBC: Systems & Technology Research LLC            Topic: SOCOM18A001

    Face recognition performance using deep learning has seen dramatic improvements in recent years. This improvement has been fueled in part by the curation of large labeled training datasets with millions of images of hundreds of thousands of subjects.This results in effective generalization for matching over pose, illumination, expression and age variation, however these datasets have traditionally ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  4. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  5. Human Performance Optimization

    SBC: REJUVENATE BIO INC            Topic: SOCOM17C001

    Special Operations Forces (SOF) are an integral aspect of the US military. SOF operators are among the most elite and highly qualified individuals in the U.S. military. As such, extraordinary physical and mental demands are placed upon them to excel in extreme environments for extended periods of time. This unrelenting cycle of combat deployments and intense pre-deployment training shortens the fu ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  6. Bantam Rocket Affordable SLV Stage (BRASS)

    SBC: EXQUADRUM INC            Topic: T101

    During the proposed Phase I research and development effort, the project team will integrate previously demonstrated technologies into a stage 4 propulsion system for an existing Small Launch Vehicle (SLV). The resulting fourth stage will meet launch vehicle requirements for Mass Fraction and Specific Impulse. Key stage component will be fabricated and demonstrated. The propulsion system will be ...

    STTR Phase I 2017 National Aeronautics and Space Administration
  7. A Massively Parallel Framework for Low-Dissipation, Multiphysics Simulations of Rocket Engines

    SBC: CASCADE TECHNOLOGIES INC            Topic: T102

    In this proposal, researchers from Cascade Technologies and Stanford University outline a multi-year research plan to develop large-eddy simulation (LES) tools to predict and understand combustion instabilities in liquid-propellant rocket engines. Rocket instabilities are a notoriously complicated, multiscale problem involving nonlinear interactions between transcritical multiphase flows, turbulen ...

    STTR Phase I 2017 National Aeronautics and Space Administration
  8. Multiphysics Framework for Prediction of Dynamic Instability in Liquid Rocket Engines

    SBC: ATA ENGINEERING, INC.            Topic: T102

    Mitigation of dynamic combustion instability is one of the most difficult engineering challenges facing NASA and industry in the development of new continuous-flow combustion systems such as the combustion chambers in liquid-fueled rocket engines (LREs). Combustion instabilities are spontaneous, self-sustaining oscillations that tie the combustor acoustics to the combustion reaction itself. These ...

    STTR Phase I 2017 National Aeronautics and Space Administration
  9. Through Wall Wireless Intelligent Sensor and Health Monitoring (TWall-ISHM) System

    SBC: AMERICAN GNC CORPORATION            Topic: T1301

    NASA's strategic needs include those related to flexible instrumentation capable of monitoring remote or inaccessible measurement locations within Stennis Space Center (SSC) testing facilities. Looking to support the advancement of NASA SSC's infrastructure, American GNC Corporation (AGNC) and the Rensselaer Polytechnic Institute (RPI) are proposing the Through Wall Wireless Intelligent Sensor and ...

    STTR Phase I 2017 National Aeronautics and Space Administration
  10. Methodology for Distributed Electric Propulsion Aircraft Control Development with Simulation and Flight Demonstration

    SBC: EMPIRICAL SYSTEMS AEROSPACE INC            Topic: T1501

    In the proposed STTR study, Empirical Systems Aerospace, Inc. (ESAero) and the University of Illinois at Urbana-Champaign (UIUC) will create a methodology for the development of a flight control algorithm featuring differential thrust provided by a distributed electric propulsion (DEP) system. The focal piece of the study is a dynamically scaled Cirrus SR22T UAV at UIUC, which will be modified to ...

    STTR Phase I 2017 National Aeronautics and Space Administration
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