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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 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.

  1. Novel Fiber Optic Methods for Sensing Shape, Orientation and/or Heading of Undersea Arrays and Tethers

    SBC: 3 Phoenix, Inc.            Topic: N08T029

    In the Phase I STTR, N08-T029 “Novel Fiber Optic Methods for Sensing Shape, Orientation and/or Heading of Undersea Arrays and Tethers” a concept was developed for a fiber optic sensing array and shape reconstruction algorithm to be used for situation awareness of flexible undersea cable structures. Undersea cable structures are deployed in environments unsuitable for direct in-situ observation ...

    STTR Phase II 2010 Department of DefenseNavy
  2. Development of Magnetostrictive Energy Harvesting of Mechanical Vibration Energy

    SBC: Applied Physical Sciences Corp.            Topic: N10AT020

    Applied Physical Sciences and the University of Maryland propose to develop a magnetostrictive transducer that harvests electrical energy from shipboard machinery while simultaneously suppressing vibration to improve the ship’s stealth characteristics and thereby improving the performance of hull mounted sonar systems. Analysis performed during the Base Effort will provide an initial design spec ...

    STTR Phase I 2010 Department of DefenseNavy
  3. External Pipe Sound Pressure Level Sensor

    SBC: Applied Physical Sciences Corp.            Topic: N10AT016

    Applied Physical Sciences (APS) and the Pennsylvania State University Applied Research Laboratory (ARL/PSU) will collaborate in the development of a novel sensor system to measure the low frequency acoustic pressures within a fluid-filled pipe. The proposed concept improves upon the Navy’s current Array Based Acoustic Measurement (ABAM) system for laboratory characterization of full-scale piping ...

    STTR Phase I 2010 Department of DefenseNavy
  4. Integration of PALACE and Touchdown Planning Methods for Landing CUAS at Unprepared Sites

    SBC: AURORA FLIGHT SCIENCES CORPORATION            Topic: N10AT039

    Aurora Flight Sciences and MIT have been developing tools and techniques that, together with existing 3D environment decision-making and navigation tools developed by AMRDEC in the PALACE program, are well-suited to the problem of autonomous vertical landing on unprepared landing sites. In this program, Aurora will team with MIT researchers and UC Santa Cruz (UCSC licenses PALACE technologies for ...

    STTR Phase I 2010 Department of DefenseNavy
  5. Adaptive Turbine Engine Control for Stall Threat Identification and Avoidance

    SBC: AURORA FLIGHT SCIENCES CORPORATION            Topic: N10AT008

    Aurora Flight Sciences and MIT propose to develop a model-based adaptive health estimation and real-time proactive control to identify gas turbine engine stability risks and avoid them through control action. In this concept, the engine control system actively monitors sensors and actuators, compares them against physical models, and infers which components may be performing poorly and may need to ...

    STTR Phase I 2010 Department of DefenseNavy
  6. Demonstrated Environment/Harware Cooperation for Expanded Riverine Coverage

    SBC: BARRON ASSOCIATES, INC.            Topic: N10AT024

    The Barron Associates/Virginia Tech team believes that intelligent use of ambient riverine environmental factors together with novel drifter design and low-energy articulation is the key to enabling large non-overlapping river coverage. The proposed phase I research program focuses on (1) identifying key river characteristics which may be leveraged by riverine drifters, (2) fabricating a novel riv ...

    STTR Phase I 2010 Department of DefenseNavy
  7. Development of Surface Reaction Mechanism for C-SiC-SiO2-Rubber Composite Oxidation in Extreme Oxidizing Condition

    SBC: CFD Research Corporation            Topic: N10AT005

    The purpose of this STTR is to develop comprehensive detailed kinetics for oxidation of C-SiC-SiO2-rubber in extreme oxidizing environment. This material is used as a coating on the outer surface of Navy weapon systems. In order to predict the fate of this material under extreme conditions and mitigate the degradation of the coating, a comprehensive oxidation mechanism is required. In Phase I, CFD ...

    STTR Phase I 2010 Department of DefenseNavy
  8. Lightweight Layered Protection Systems for Missile Launchers and Canisters

    SBC: Corvid Technologies LLC            Topic: N10AT018

    The objective of this proposed effort is to leverage state-of-the-art modeling and simulation tools to predict and assess the performance of a novel layered material system as protection for high-value missiles when deployed in launchers and canisters. The physics-based computational tools developed and used by Corvid allow for complex material interactions to be captured to provide an understandi ...

    STTR Phase I 2010 Department of DefenseNavy
  9. Prediction of the Full-Scale Cook-off Response Based on Small-Scale Testing

    SBC: Corvid Technologies LLC            Topic: N10AT011

    The objective of this proposed effort is to continue the development of Corvid’s existing modeling and simulation framework to provide an innovative methodology used to predict the response of full-scale weapons systems to fast cook-off (FCO) and slow cook-off (SCO). Ammunition presents a special problem where no reliable and inexpensive sub or small scale testing capability has been identified. ...

    STTR Phase I 2010 Department of DefenseNavy
  10. Multi-Modal Knowledge Acquisition from Documents

    SBC: ObjectVideo            Topic: N10AT019

    Images with associated text are now available in vast quantities, and provide a rich resource for mining for the relationship between visual information and semantics encoded in language. In particular, the quantity of such data means that sophisticated machine learning approaches can be applied to determine effective models for objects, backgrounds, and scenes. Such understanding can then be used ...

    STTR Phase I 2010 Department of DefenseNavy
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