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Award Data

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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. Novel Development of an Intelligent Quench Detection (QD) Method for HTS Coils

    SBC: TAI-YANG RESEARCH CO            Topic: N19AT016

    Energy to Power Solutions (e2P) has teamed with quench detection (QD) expert Dr. Yuri Lvovsky (retired GE), Dr. Sastry Pamidi of the Center for Advanced Power Systems (FSU-CAPS), and American Superconductor Corporation (AMSC) to design, fabricate, and test a robust, reliable, and low cost QD system. e2P’s proposed system is a vastly different quench avoidance system that will provide multiple le ...

    STTR Phase I 2019 Department of DefenseNavy
  2. Real-Time Validation of Machine Intelligence Controlling Unmanned Vehicle Autonomous Operations

    SBC: XL SCIENTIFIC LLC            Topic: N18BT032

    To realize the full potential of autonomous systems, it is imperative that they behave safely, correctly, ethically, and legally. Providing these assurances through offline verification alone is insufficient, due to the complex and changing nature of autonomous systems. Online monitoring and corrective actions are necessary to account for uncertainties, and to increase trust between a human superv ...

    STTR Phase I 2019 Department of DefenseNavy
  3. Optimized Higher Power Microwave Sources

    SBC: XL SCIENTIFIC LLC            Topic: N19AT001

    Verus Research and the University of New Mexico (UNM) are pleased to respond to the Navy Phase I STTR solicitation N19A-T001 titled “Optimized Higher Power Microwave Sources.” Verus Research, in collaboration with UNM, propose to develop a GW-class, S-band, high power microwave (HPM) source to integrate in vehicle and vessel stopping systems. Our integrated approach ensures the objectives for ...

    STTR Phase I 2019 Department of DefenseNavy
  4. Power-Dense Electrical Rotating Machines for Propulsion and Power Generation

    SBC: CONTINUOUS SOLUTIONS Inc            Topic: N19AT007

    The primary objective is to develop electric machine/drive topologies and power architectures that achieve the power densities required for 50% more power without the increase in weight or space requirements. In addition to PMSM-based designs, two new machine topologies will be considered. The first is a trapped flux coreless (TFC) machine that utilizes superconducting pucks made of YBCO to produc ...

    STTR Phase I 2019 Department of DefenseNavy
  5. Power Dense Turbo-Compression Cooling Driven by Waste Heat

    SBC: MANTEL TECHNOLOGIES INC            Topic: N19AT013

    The U.S. Navy seeks methods to improve the fuel economy of marine diesel engines through utilization of waste heat. Low temperature engine jacket water, lubrication oil, and aftercooler air are largely untapped streams of thermal energy on these ships, but their utilization circumvents many operation challenges associated with exhaust gases. For example, variable and high exhaust gas temperatures ...

    STTR Phase I 2019 Department of DefenseNavy
  6. GECCO: Gecko-gripper for EOD with Cavitation Cleaning Operation

    SBC: VALOR ROBOTICS, LLC            Topic: N19AT011

    The objective of the Phase I proposal is to investigate the application of controlled cavitation cleaning technology in conjunction with gecko-inspired mechanical adhesion and soft elastomeric applicators for use in non-intrusive EOD operations. This investigation requires the proof-of-concept testing and validation of a controlled cavitation cleaning mechanism, and a soft robotic gecko-inspired m ...

    STTR Phase I 2019 Department of DefenseNavy
  7. Predictive Graph Convolutional Networks- 19-008

    SBC: METRON INCORPORATED            Topic: N19AT017

    Metron and Northeastern University propose to design, develop, and validate a proof-of-concept predictive Graph Convolutional Network (GCN) capability using open source Reddit and GDELT data. We propose: (1) to extract and preprocess open-source Reddit and GDELT data, (2) to design a predictive graph convolutional neural network model, (3) to implement and train that model, and (4) to validate the ...

    STTR Phase I 2019 Department of DefenseNavy
  8. Reduced Order Modeling (ROM) for UUV/USV Environmental Awareness-- 19-013

    SBC: METRON INCORPORATED            Topic: N19AT022

    In Phase I, Metron and the University of Miami (UM) propose to develop a theoretic reduction of dynamics framework applicable to the prediction of oceanographic fields in geophysical fluid dynamic models for use onboard unmanned platforms. Our approach leverages, extends and combines modern advances in the renormalization group and Bayesian probability combined with fluid dynamics modeling and for ...

    STTR Phase I 2019 Department of DefenseNavy
  9. Local Stochastic Prediction for UUV/USV Environmental Awareness

    SBC: APPLIED OCEAN SCIENCES, LLC            Topic: N19AT022

    This project delivers a system to assess local uncertainties and track the evolution of the maritime environment around unmanned platforms at sea. The system uses Navy ocean forecasts for initial environmental guesses and outlooks and implements a Reduced Order Model (ROM) derived from Dynamically Orthogonal (DO) solutions to deliver a local uncertainty picture (for the next 24-48 hours). The ROM- ...

    STTR Phase I 2019 Department of DefenseNavy
  10. Unified Logging Architecture for Performance and Cybersecurity Monitoring

    SBC: INNOVATIVE DEFENSE TECHNOLOGIES, LLC            Topic: N19AT012

    In order to achieve real-time monitoring, analysis, and alerting for complex systems, a unified logging architecture must exist that can support the collection and analysis of big data. Our technical objective is to develop a unified logging architecture that supports collection, aggregation, storage, and analysis of system performance and cybersecurity logs, events, and alerts produced by Naval C ...

    STTR Phase I 2019 Department of DefenseNavy
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