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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY21 is not expected to be complete until September, 2022.

Download all 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.

  1. Techniques to Adjust Computational Trends Involving Changing Data (TACTIC-D)

    SBC: Oasys, Inc.            Topic: N17BT032

    The Navy seeks technology based on statistical or computational methods to assist in the continued tracking of training performance and proficiency trends as underlying tactical data changes. OASYS, INC. and the ITCS at UAH proposes to exploit the benefits of modeling the underlying cause-effect structure of Navy data, rather than the data itself. This approach makes the model and analytical metho ...

    STTR Phase I 2017 Department of DefenseNavy
  2. Risk-Aware Navigation and Guidance for Resilience (RANGR)

    SBC: BIHRLE APPLIED RESEARCH INC.            Topic: N17BT034

    Because traditional methods for assessing risk in UAS operations with the National Airspace (NAS) are unavailable, alternatives must be sought. As such, the work detailed within this proposal can be split into two significant parts. The first part is the identification of information sources, both open and commercial, from which databases of inferred population-based risk can be generated. The sec ...

    STTR Phase I 2017 Department of DefenseNavy
  3. Risk-Based Unmanned Air System (UAS) Mission Path Planning Capability

    SBC: ACTA, LLC            Topic: N17BT034

    In this Phase I Project ACTA and its partners will demonstrate the feasibility of developing a risk-based mission path planning (RB MPP) approach. Areas of interest to the Navy where a RB MPP address critical needs include enabling less restrictive UAS operations within the US National and Foreign Airspaces. The Phase I will demonstrate feasibility with a two-step approach. The first step will dem ...

    STTR Phase I 2017 Department of DefenseNavy
  4. Minimum-Risk Planning and On-Board Replanning for UAS Operations

    SBC: BARRON ASSOCIATES, INC.            Topic: N17BT034

    Current aircraft operations within the National Airspace System (NAS) rely heavily on the presence of an on-board pilot to safely manage the flight. Integration of Unmanned Aircraft Systems (UAS) into the NAS requires a high confidence that these unmanned aircraft operations can meet or exceed the safety afforded through manned operations. Specifically, these UAS operations must not pose an undue ...

    STTR Phase I 2017 Department of DefenseNavy
  5. Cognitive Risk Management for UAS Missions

    SBC: Stottler Henke Associates, Inc.            Topic: N17BT035

    Enabling operators to command and control multiple UAVs will require higher levels of supervisory control, enabling vehicles to operate autonomously during larger portions of each mission. For the foreseeable future, however, critical portions of each mission will require operators to apply their superior knowledge, judgment, and skills to assess the situation, monitor execution more closely and, ...

    STTR Phase I 2017 Department of DefenseNavy
  6. Dynamically Reconfigurable Mission Control and Performance (DREAM CAPER)

    SBC: DZYNE Technologies Incorporated            Topic: N17BT035

    The Navys Common Control System (CCS) plan for managing multiple Unmanned Aerial System (UAS) and manned aircraft requires mechanisms to focus the operators attention as quickly as possible to changes in the environment that will affect mission success. The planned evolution of the CCS to fully autonomous operation further requires that these changes and their effects on the mission be identified ...

    STTR Phase I 2017 Department of DefenseNavy
  7. Cognitive Adaptation and Mission Optimization (CAMO) for Autonomous Teams of UAS Platforms

    SBC: Opto-knowledge Systems, Inc.            Topic: N17BT035

    OKSI and Professor Matthew Taylor will develop the Cognitive Adaptation and Mission Optimization (CAMO) command and control tool for teams of UAS platforms. CAMO will incorporate existing databases (e.g., NASA population maps, FAA airspace maps, etc.) as well as real-time data from UAS into a learning-based cognitive control solution that maximizes mission performance while minimizing risk for a t ...

    STTR Phase I 2017 Department of DefenseNavy
  8. Materials Modeling Tool for Alloy Design to Streamline the Development of High Temperature, High-Entropy Alloys for Advanced Propulsion Systems

    SBC: TECHNICAL DATA ANALYSIS, INC.            Topic: N17BT031

    The recent alloy developments involving high entropy alloys (HEAs) are paving the way for the development of high temperature refractory metal alloys with stable single phase microstructures at ambient conditions. Development of HEAs is an emerging field and our understanding of these new materials is still very limited and preliminary. During past decades, much attention has been given to MoSiB a ...

    STTR Phase I 2017 Department of DefenseNavy
  9. Materials Modeling Tool for Alloy Design to Streamline the Development of High Temperature, High-Entropy Alloys for Advanced Propulsion Systems

    SBC: Directed Vapor Technologies International, Inc.            Topic: N17BT031

    The performance of gas turbine engines is greatly improved as engine operation temperatures are increased. This has dictated that the hot structural components made of nickel based superalloys often operate at temperatures approaching their melting point. Alternate materials with higher temperature performance are desired for use in the hot section of gas turbine engines. Higher temperature capabl ...

    STTR Phase I 2017 Department of DefenseNavy
  10. Optimized Build Plate Design Tool for Metal Laser Powder Bed Additive Manufacturing

    SBC: TECHNICAL DATA ANALYSIS, INC.            Topic: N17BT033

    TDAs proposed work addresses the target STTR topic objectives of developing an intelligent decision support system to (a) mitigate the evolution of AM process-induced residual stresses and distortions, (b) include advanced optimization features and (c) help the user in selecting the best part orientation & support on the AM platformBased on our teams expertise in topology optimization, modeling an ...

    STTR Phase I 2017 Department of DefenseNavy
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