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The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.

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. 3D Acoustic Model for Geometrically Constrained Environments

    SBC: HEAT, LIGHT, AND SOUND RESEARCH, INC.            Topic: N16AT018

    Systems that operate in constrained environments depend on the acoustics in several ways. Harbor defense systems detect intruders (people and/or vessels) by either listening for their noises (passively) or by pinging on them and detecting their echoes (actively). Furthermore, such systems may also form the equivalent of an underwater cell phone network using sound to carry the information. The aco ...

    STTR Phase I 2016 Department of DefenseNavy
  2. 3D Acoustic Model for Geometrically Constrained Environments

    SBC: HEAT, LIGHT, AND SOUND RESEARCH, INC.            Topic: N16AT018

    Systems that operate in constrained environments depend on the acoustics in several ways. Harbor defense systems detect intruders (peopleand/or vessels) by either listening for their noises (passively) or by pinging on them and detecting their echoes (actively). Furthermore, suchsystems may also form the equivalent of an underwater cell phone network using sound to carry the information. The acous ...

    STTR Phase II 2017 Department of DefenseNavy
  3. Bonded Joint Analysis Method

    SBC: M4 ENGINEERING, INC.            Topic: N12AT004

    During Phase I and Phase II, M4 Engineering, Inc. and Sandia National Laboratories have created a unique bonded joint analysis methodology and associated software. During Phase II.5, the developed techniques will be further enhanced and a fully functional commercial analysis code (SIMULIA/Abaqus) plug-in will be created. The software plug-in will make the advanced technology accessible to all leve ...

    STTR Phase II 2016 Department of DefenseNavy
  4. Multi-Phase Flame Propagation Modeling for Present and Future Combustors and Augmentors

    SBC: Metacomp Technologies, Inc.            Topic: N17AT002

    The proposed project will develop advanced modeling capabilities for high-fidelity liquid-fuel spray calculations. State-of-the-art multiphase combustion models will be implemented in a volume-filtered Eulerian-Lagrangian framework that can easily be ported into existing CFD codes. Unlike traditional methods, the proposed strategy will ensure convergence under mesh refinement of the interphase exc ...

    STTR Phase I 2017 Department of DefenseNavy
  5. Improved High-Frequency Bottom Loss Characterization

    SBC: HEAT, LIGHT, AND SOUND RESEARCH, INC.            Topic: N17AT026

    We propose development of an improved bottom database suitable for use in the frequency range of 1-10 kHz. Measured transmission loss (TL) and reverberation level (RL) will be jointly processed in building the database. The influence of the rough sea surface, rough seafloor, as well as subbottom heterogeneity will be accounted for during database generation. The rough sea surface will be character ...

    STTR Phase I 2017 Department of DefenseNavy
  6. Additive Manufacturing for Microwave Vacuum Electron Device Cost Reduction

    SBC: Radiabeam Technologies, LLC            Topic: N16AT010

    The Department of the Navy has a need for the development of an additive manufacturing (AM) process for key vacuum electronic device components to meet on-demand, flexible, and affordable manufacturing requirements. The developed manufacturing method has a potential to reduce cost of vacuum electronics by as much as 70% as well as simplify and hence expedite production process of these devices by ...

    STTR Phase I 2016 Department of DefenseNavy
  7. Fast and Flexible Differential Equation Model Fitting with Application to Pharmacometrics

    SBC: Metrum Research Group LLC            Topic: N16AT016

    Differential equations are widely used to analyze and simulate the dynamics of complex systems in the physical, biological and social sciences. Inferences with such models are challenging due to both statistical and computational complexity. Stan is a widely used, open-source, probabilistic programming language and Bayesian inference engine. We propose to extend Stan by incorporating solvers for o ...

    STTR Phase I 2016 Department of DefenseNavy
  8. Large-scale Entity Linking and Disambiguation with DeepDive

    SBC: CLEARCUT ANALYTICS, INC            Topic: N16AT016

    DeepDive is a system for extracting relational databases from dark data: the mass of text, tables, and images that are widely collected and stored but which cannot be exploited by standard relational tools. If the information in dark data --- scientific papers, Web classified ads, customer service notes, and so on --- were instead in a relational database, it would give analysts access to a massiv ...

    STTR Phase I 2016 Department of DefenseNavy
  9. High Fidelity Rotorcraft Towing Modeling and Simulation with Towed Magnetic Anomaly Detection System

    SBC: ADVANCED ROTORCRAFT TECHNOLOGY, INC.            Topic: N15AT009

    Towing of a Magnetic Anomaly Detection (MAD) system is an important aspect of rotorcraftmaritime operation. The oscillatory rotorcraft combined with the long and flexible towingcable, the low mass ratio of the towed body to the towing aircraft, and the rotor wake effecton the towed body presents a challenge for integration of a modern MAD system withrotorcraft platform. The research objective is t ...

    STTR Phase II 2016 Department of DefenseNavy
  10. 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 Navyproviding 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 technologie ...

    STTR Phase I 2017 Department of DefenseNavy
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