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The Award database is continually updated throughout the year. As a result, data for FY19 is not expected to be complete until April, 2020.

  1. Element Model Framework

    SBC: ARCHARITHMS, INC.            Topic: MDA18009

    Uniform interface saves money; reduced integration time; lifecycle improvement; increases integration speed; reduces schedule flux; saves times and schedule; reduces future improvement costs; reduces integration costs; reduces network bandwidth costs.Approved for Public Release | 18-MDA-9817 (23 Oct 18)

    SBIR Phase I 2019 Department of DefenseMissile Defense Agency
  2. Advanced Data Management and Mining for BMDS Digital Simulations

    SBC: ARCHARITHMS, INC.            Topic: MDA18011

    Minimizes integration, testing and training; saves time and money; high speed identification of runs; automated classification of nominal and off nominal behavior; high quality visualization to help with analysis; quick display of estimated and predicted metrics; rapid prediction of performance; enables reuse of components with no software changes; low size weight and power compute nodes.Approved ...

    SBIR Phase I 2019 Department of DefenseMissile Defense Agency
  3. RadHard Packaging for Small Satellite Microelectronics

    SBC: Triton Systems, Inc.            Topic: AF182066

    The purpose of this proposal is to develop a process capable of fabricating radiation hardened (RadHard) packages for commercial-off-the-shelf (COTS) microelectronics used in small satellites. The goal is to fabricate a package that mitigates single event effects and reduce total ionizing dose (TID) and dose rate from space radiation. During the Phase I, Triton Systems proposes to demonstrate the ...

    SBIR Phase I 2019 Department of DefenseAir Force
  4. Framework for Modeling Turbulent Flow with Conjugated Heat Transfer

    SBC: Advanced Cooling Technologies, Inc.            Topic: N19BT027

    With gas turbines becoming smaller and more powerful the need to accurately predict the temperature distribution of the turbine blades become crucial. The high Reynolds number (Re), poorly behave flow encountered in gas turbines makes Reynolds Averaged Navier Stokes (RANS) inaccurate and Direct Numerical Simulations (DNS) too expensive to be used as analysis tools. Large Eddy Simulation (LES) appr ...

    STTR Phase I 2019 Department of DefenseNavy
  5. 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
  6. 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
  7. Joint User-centered Planning artificial Intelligence Tools for Effective mission Reasoning (JUPITER)

    SBC: Charles River Analytics, Inc.            Topic: N19BT029

    Effective mission planning is critical for military strategy and execution. This process is complex as human operators must consider many variables (e.g., resource limitations, threats, risks) when formulating a plan to accomplish mission goals. Although powerful tools, such as the Navys Joint Mission Planning System (JMPS), provide advanced functionality, mission planning remains a hybrid activit ...

    STTR Phase I 2019 Department of DefenseNavy
  8. 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
  9. AI-Driven, Secure Navy Mission Planning via Deep Reinforcement Learning and Attribute-Based Multi-Level Security

    SBC: EH GROUP            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
  10. REVAMP: REcommendation, Verification, and Analysis for Mission Planning

    SBC: Intelligent Automation, Inc.            Topic: N19BT029

    Effective and efficient data-driven mission support is crucial for achieving readiness and superiority in warfighting enterprises. Leveraging machine learning (ML) and artificial intelligence (AI) in mission planning would not only minimize the human-error factors and increase accuracy, but also improve speed in planning, execution, and evaluation of a mission. REVAMP will improve the next generat ...

    STTR Phase I 2019 Department of DefenseNavy

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