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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. 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
  2. A Hierarchical and Extendable, Component-Based Simulation Tool for Aircraft Thermal Management Systems

    SBC: CFD RESEARCH CORPORATION            Topic: N19BT025

    The requirements for thermal management on tactical aircraft systems have reached a level at which integrated system design must be considered early in the aircraft design process. An integrated propulsion, power and thermal modeling and simulation design approach is necessary for reduced size, weight and power requirements. At the same time, there is an urgent need for capabilities that enable an ...

    STTR Phase I 2019 Department of DefenseNavy
  3. Conjugate heat transfer for LES of gas turbine engines

    SBC: CASCADE TECHNOLOGIES INC            Topic: N19BT027

    Current design tools for gas turbine engines invoke a variety of simplifying assumptions to estimate heat transfer to solid/metal engine components (e.g., isothermal boundary conditions). These approximations are often not valid, result in inaccurate predictions of heat transfer, and ultimately compromise the thermal integrity of propulsion and power systems. Wall-modeled large eddy simulation (WM ...

    STTR Phase I 2019 Department of DefenseNavy
  4. Large Eddy Simulation (LES) Flow Solver Suitable for Modeling Conjugate Heat Transfer

    SBC: Kord Technologies, Inc.            Topic: N19BT027

    Accurate prediction heat transfer in gas turbine components subject to cooling requires high fidelity modeling of heat transfer in the presence of high Reynolds number turbulent flow. The cooling internal to the blades results in sustained temperature gradients within the structural parts, from low temperature in the interior of the structure to increasingly higher temperature closer to the surfac ...

    STTR Phase I 2019 Department of DefenseNavy
  5. Data Science Techniques for Various Mission Planning Processes and Performance Validation

    SBC: Perceptronics Solutions, Inc.            Topic: N19BT029

    Mission and planning is a difficult and time-consuming process that places a heavy burden on manpower and critical thinking and is performed under significant pressure. Existing and emerging artificial intelligence (AI) and machine learning (ML) techniques are well-suited to assisting humans with these challenges. While the promise of AI/ML is great, there are significant obstacles to operationali ...

    STTR Phase I 2019 Department of DefenseNavy
  6. AI-Driven, Secure Navy Mission Planning via Deep Reinforcement Learning and Attribute-Based Multi-Level Security

    SBC: EH GROUP INC            Topic: N19BT029

    Current mission planning systems allow strike planners and operations centers to perform time-sensitive strike planning, execution monitoring, and validate mission effects using XML-based tools that visualize time critical attack plan and track plan status vs. execution. In this proposed STTR Phase I design for the Next Generation Navy Mission Planning (NGNMPS) system, we will identify expanded op ...

    STTR Phase I 2019 Department of DefenseNavy
  7. Tools for Implementing Speech Agents in Crew Resource Management Training Systems

    SBC: OPTIMAL SYNTHESIS INC.            Topic: N17AT010

    Crew resource management training systems are often constrained by the high cost and lack of flexibility in coordinating a large group of human role players for part-task training. Motivated by the recent maturation of the speech synthesis and recognition technologies, speech-enabled crew role-player agents are being introduced to address these limitations. However, difficulties remain in customiz ...

    STTR Phase II 2019 Department of DefenseNavy
  8. Electro-Optic Transmissive Scanner

    SBC: ULTIMARA INC            Topic: N17AT001

    The goal of this program is to develop and construct a thin, light weight, low power, large aperture, electro-optic (EO) transmissive scanner that utilizes electro-optically active nanomaterial structures, suitable for UAV’s platform. The nano-material beam-steering technology aperture system offers an ultra-thin Size, Weight, and Power (SWAP) to fit on UAV’s airframe and achieve ultrafast and ...

    STTR Phase II 2019 Department of DefenseNavy
  9. Visual Tools and Progressive Automation for Complex Knowledge Management and Decision Support

    SBC: Stottler Henke Associates, Inc.            Topic: N17AT004

    We propose to adapt and automate the processes and technologies associated with evidence-based decision support to the Navy—providing a tool that can synthesize current cognitive and learning science knowledge and inform decisions so as to maximize the value gained for each training expenditure. We will develop a plug-play architecture that will allow us to make the best use of emerging technolo ...

    STTR Phase II 2019 Department of DefenseNavy
  10. Physics-based Computationally Efficient Spray Combustion Models for LES of Multiphase Reacting Flows

    SBC: CFD RESEARCH CORPORATION            Topic: N17AT002

    One important challenge for the reliable prediction of liquid fuel effects on the combustion in aviation combustors and augmentors is the accurate modeling of underlying physical processes, involving the evaporation of fuels, preferential vaporization, scalar mixing and ignition. LES methodologies are required to accurately capture these transient and inherently unsteady combustion processes. In t ...

    STTR Phase II 2019 Department of DefenseNavy
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