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Award Data
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.
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Protocol Feature Identification and Removal
SBC: P & J ROBINSON CORP Topic: N18AT018Protocols used for communication suffer bloat from a variety of sources, such as support for legacy features or rarely used (and unnecessary) functionality. Traditionally, the Navy subscribes to a blanket adoption of a standard protocol "as is". Unnecessary features are active and can be accessed by both internal and external systems creating security vulnerabilities. PJR Corporation's (PJR's) Pha ...
STTR Phase I 2018 Department of DefenseNavy -
Optimization of Fatigue Test Signal Compression Using the Wavelet Transform
SBC: ATA ENGINEERING, INC. Topic: N18BT029Traditional 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 -
Operational Sand and Particulate Sensor System for Aircraft Gas Turbine Engines
SBC: HAL Technology, LLC Topic: N18AT023Gas turbine engines with prolonged exposure to sand and dust are susceptible to component and performance degradation and ultimately engine failure. Hal Technology’s proprietary, compact, rugged, flush-mounted, fiber-optic sensor platform measures particulate size, size distributions, and concentration for real-time engine health monitoring. Our proposed sensor will use an innovative hybrid disc ...
STTR Phase I 2018 Department of DefenseNavy -
Non-Destructive Concrete Interrogator and Strength of Materials Correlator
SBC: KARAGOZIAN & CASE, INC. Topic: N18AT006Karagozian & Case Inc. and the University of Nebraska-Lincoln Department of Civil Engineering are proposing a Phase I STTR to develop a non-invasive and non-destructive methodology capable of measuring concrete material properties, including relevant spatial and statistical information associated with them, for input to hydrocode models. The solution will be both laboratory and field deployable, w ...
STTR Phase I 2018 Department of DefenseNavy -
Additive Manufacturing for Naval Aviation Battery Applications
SBC: STORAGENERGY TECHNOLOGIES INC Topic: N18AT008Storagenergy Technologies Inc. proposes to develop an all solid-state battery (ASSB) which can be made by a high-speed AMtechnology.
STTR Phase I 2018 Department of DefenseNavy -
Twiner
SBC: SOAR TECHNOLOGY INC Topic: N18AT019We currently lack the ability to holistically and autonomously look across all three layers of cyberspace (persona, logical and physical) and identify interesting patterns, which would give us an edge in understanding complex activities in and through cyberspace. To address this challenge, Soar Technology (SoarTech) and the GeorgiaTech Research Institute (GTRI) propose Twiner, an intelligent syste ...
STTR Phase I 2018 Department of DefenseNavy -
Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery
SBC: TOYON RESEARCH CORPORATION Topic: 1On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...
STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
Algorithms for Look-down Infrared Target Exploitation
SBC: SIGNATURE RESEARCH, INC. Topic: 1Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...
STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
An Integrated Materials Informatics/Sequential Learning Framework to Predict the Effects of Defects in Metals Additive Manufacturing
SBC: Citrine Informatics, Inc. Topic: N18AT013In 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 -
Full Featured Low-Cost HMS for Combatant Craft
SBC: QUALTECH SYSTEMS, INC. Topic: N18AT015Qualtech Systems, Inc. (QSI), in collaboration with VU proposes to develop a state-of-the art HMS system featuring: (1) Low Hardware cost by leveraging industrial-grade computers ruggedized to military specifications (2) Low Software cost by leveraging QSI’s COTS TEAMS software with real-time monitoring and diagnosis capabilities (3) Vibration and Shock Analysis and its impact on vehicle and cre ...
STTR Phase I 2018 Department of DefenseNavy