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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

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. Rapid Identification of Effects of Defects within Metal Additive Manufacturing (RIED-AM)

    SBC: Intelligent Automation, Inc.            Topic: N18AT013

    Additive manufacturing (AM) systems, especially metal AM, bring revolutionary capabilities, but suffer from a lack of understanding of the defects that exist within the components. In this research, based on selective experimental study and numerical simulations, we will develop an empirical database of defects and their effects on mechanical properties using Laser Powder Bed Fusion (LPBF) technol ...

    STTR Phase I 2018 Department of DefenseNavy
  2. An Integrated Materials Informatics/Sequential Learning Framework to Predict the Effects of Defects in Metals Additive Manufacturing

    SBC: Citrine Informatics, Inc.            Topic: N18AT013

    In this project, Citrine Informatics and the ADAPT Center at the Colorado School of Mines propose to build an informatics-driven system to understand the effects of defects in additive manufactured parts. The entire history of each sample will be captured on this system; from specific printing parameters and details of precursor materials through to part characterizations and performance measureme ...

    STTR Phase I 2018 Department of DefenseNavy
  3. Analysis and Application of Treatments to Mitigate Exfoliation Corrosion (Delamination) of 5XXX Series Aluminum

    SBC: OCEANIT LABORATORIES INC            Topic: N18AT016

    Oceanit proposes to research and develop chemical or non-chemical methods and processes to impart surface morphology modifications to aluminum-magnesium (Al-Mg) alloys to mitigate and increase the exfoliation corrosion resistance.

    STTR Phase I 2018 Department of DefenseNavy
  4. Optimization of Fatigue Test Signal Compression Using the Wavelet Transform

    SBC: ATA ENGINEERING, INC.            Topic: N18BT029

    Traditional approaches to accelerated fatigue testing rely on heuristic methods with thresholds based mostly on experience and engineering judgment. These methods generally do not apply to the multiaxial dynamic loading situations characteristic of most aerospace applications and often result in uncharacteristic fatigue damage and failure modes during testing. To overcome the limitations of tradit ...

    STTR Phase I 2018 Department of DefenseNavy
  5. Evidence-Based, User-Centered Design Process for Improvement of the Utility of the Surface Electronic Warfare Display Suit

    SBC: PACIFIC SCIENCE & ENGINEERING GROUP, INC.            Topic: N11AT031

    In Naval, surface electronic warfare (EW), visual displays form critical bridges between warfighters and the complex operational radio-frequency (RF) spectrum they must monitor and interpret. Surface electronic warfare operators and supervisors must monitor and interact with multiple, stove-piped display systems in order to perform their work. Further, the visual displays they employ are not desig ...

    STTR Phase II 2018 Department of DefenseNavy
  6. Medium Voltage Direct Current (MVDC) Fault Detection, Localization, and Isolation

    SBC: ISSAC Corp            Topic: N16AT009

    During the Phase II effort, the ISSAC Team will investigate several objectives and questions posed in Phase I efforts, in order to best develop a draft specification for NGES MVDC DLI systems. This includes exploring notional and conceptual architectures and discerning thresholds for DLI parameters; exploring individual and hybrid protection plan technologies to drive performance requirements for ...

    STTR Phase II 2018 Department of DefenseNavy
  7. 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 goal of this Phase II effort is to develop and validate Electron Beam Melting (EBM) additive manufacturing (AM) technology for the production of vacuum electronic devices meeting t ...

    STTR Phase II 2018 Department of DefenseNavy
  8. Ignition Modeling for Present and Future Combustors and Augmentors

    SBC: COMBUSTION SCIENCE & ENGINEERING, INC.            Topic: N17AT003

    The ability to predict the ignitibility potential of a combustor at various operating conditions is not practical at this time due to the complexity of this process. Ignition within a gas turbine combustor is dependent on various parameters; including spark (or plasma) energy, flow conditions, fuel/air ratio, and fuel spray density. All these parameters must be properly predicted in order to effec ...

    STTR Phase II 2018 Department of DefenseNavy
  9. Reduced Cavitation, High Efficiency Outboard Propulsors for Small Planing Craft

    SBC: CANDENT TECHNOLOGIES INCORPORATED            Topic: N17AT019

    The Candent Technologies “Reduced Cavitation, High Efficiency Outboard Propulsor for Small Planing Craft” Phase II program is structured to develop an advanced waterjet propulsor for the Combat Rubber Raiding Craft (CRRC). This new axial flow waterjet propulsion system is designed as a “bolt on” assembly that replaces the lower unit of the existing MFE 55 outboard motor. This new propulsio ...

    STTR Phase II 2018 Department of DefenseNavy
  10. A Scalable Event Extractor for Multi-Level Event Data and Pattern Archiving: SEE

    SBC: Intelligent Automation, Inc.            Topic: N17AT022

    To address the need of auto-extracting data relevant to significant events and to archive patterns, Intelligent Automation, Inc. (IAI) team proposes to continue developing a Scalable Event Extractor for Multi-Level Event Data and Pattern Archiving: SEE. The key innovations of our proposed SEE system are (1) a large class of analytics that extract valuable and important information from raw data, a ...

    STTR Phase II 2018 Department of DefenseNavy
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