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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. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: ARCTOS Technology Solutions, LLC            Topic: DLA18A001

    Universal Technology Corporation (UTC) has teamed with the University of Dayton Research Institute (UDRI), Stratonics, and Macy Consulting to demonstrate not only the transitionability into commercial systems, but also to develop the data analytics and monitoring and control requirements to extract the full value fromseveral sensors, including the Stratonics ThermaViz, acoustic and profilometry se ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  2. Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

    SBC: X-Wave Innovations, Inc.            Topic: DLA18A001

    Additive Manufacturing (AM) is a modern and increasingly popular manufacturing process for metallic components, but suffers from well known problems of inconsistent quality of the finished product. Process monitoring and feedback control are therefore crucial research areas with a goal of solving this problem. To address this concern, X-wave Innovations, Inc. (XII) and the University of Dayton Res ...

    STTR Phase I 2018 Department of DefenseDefense Logistics Agency
  3. Laser Additive Manufacturing of Seven Thousand Series Aluminum Aircraft Components (LAM-STAAC)

    SBC: MV Innovative Technologies LLC (DBA: Opt            Topic: N18AT005

    Alloys of aluminum in the 7000 series are known to have good weight, strength, and fatigue properties and are commonly used in Naval aircraft components. Recent manufacturing trends are increasingly focused on additive manufacturing (AM) methods as a way to reduce lead time, cost, and to improve part performance. Current additive manufacturing techniques are unable to fabricate parts in 7000 serie ...

    STTR Phase I 2018 Department of DefenseNavy
  4. Control & Optimization of Multiple Illumination Characteristics (COMIC) of A Pulsed Fiber Array Laser System For Active Imaging Through Fog

    SBC: MV Innovative Technologies LLC (DBA: Opt            Topic: N18AT021

    Degraded weather conditions particularly, dense maritime fog, reduces the US Fleet EO/IR systems ability to maintain situational awareness and detect/identify and track targets of interest. It is the Navys goal to develop an active EO/IR imaging system that jointly optimizes illumination source properties and implements advanced image processing to improve performance and operational range of curr ...

    STTR Phase I 2018 Department of DefenseNavy
  5. High Throughput Static and Dynamic Testing of AM Materials for Uncertainty Quantification and Qualification

    SBC: MRL MATERIALS RESOURCES LLC            Topic: N18AT028

    Qualification of additively manufactured parts is hampered by the inherent uncetainty in properties due to heterogeneity in processing, microstructure, and defects. The proposed effort combines high-throughput testing of static and dynamic properties using tailored sample geometry, fixture design, and load application method with microstructure quantification and analysis. This system will drastic ...

    STTR Phase I 2018 Department of DefenseNavy
  6. Wide-Area Laser Additive Manufacturing in Metals with Adaptive Beam Shaping (WALAM-ABS)

    SBC: MV Innovative Technologies LLC (DBA: Opt            Topic: N17AT030

    Optonicus proposes development of the Wide-Area Laser Additive Manufacturing in Metals with Adaptive Beam Shaping (WALAM-ABS) laser additive manufacturing (LAM) system. The WALAM-ABS metal additive manufacturing system will solve long-standing drawbacks imposed by current single-point selective laser melting LAM technology through the use of wide-area processing based on proprietary multi-beam fib ...

    STTR Phase II 2018 Department of DefenseNavy
  7. Situational Awareness for Mission Critical Ship Systems using Probabilistic Knowledge Graph

    SBC: INTELLIGENT FUSION TECHNOLOGY, INC.            Topic: N18AT009

    This effort proposes to develop situational awareness methodologies for mission critical ship system based on the state-of-the-art probabilistic knowledge graph (KG) and deep learning. The proposed KG approach can incorporate various data fusion technologies for analysis of unstructured data (text, images, etc.) and structured data (signal feeds, database items, etc.) for automated decision suppor ...

    STTR Phase I 2018 Department of DefenseNavy
  8. Nondestructive Evaluator for Polymer Ablatives (NEPAL)

    SBC: Intelligent Automation, Inc.            Topic: N18AT011

    Materials for thermal protection are required to protect structural components of space vehicles during the re-entry stage, missile launching systems, and solid rocket motors (SRMs). Polymer resins that have high char retention (e.g., phenolic resins) are the most common matrices in the composite materials for rigid thermal protection systems (TPSs) due to their tunable density, lower cost, and hi ...

    STTR Phase I 2018 Department of DefenseNavy
  9. 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
  10. Advanced Ship-handling Simulators

    SBC: D'Angelo Technologies, LLC            Topic: N18AT014

    There is a need to create an automated, adaptive, real time coaching module that can integrate the Conning Officer Virtual Environment (COVE) along with the associated Intelligent Tutor System (COVE-ITS) and the Conning-Officer Ship Handling Assessment (COSA) together. By automating the evaluation process, Surface Warfare Officers (SWOs) will have the opportunity to use the COVE simulations more f ...

    STTR Phase I 2018 Department of DefenseNavy
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