You are here
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.
-
Autonomous Airborne Chemical/Biological Cloud Detection Sensor
SBC: UES INC Topic: DTRA082011Detection of chemical and biological warfare agents in a real-world setting is an increasingly urgent problem. Many of the current state-of-the-art sensors are aqueous based and require large biomolecules, such as antibodies, to achieve binding of the target molecule and subsequent reporting of the binding event. These technical hurdles are a drawback when considering deployment of these technol ...
SBIR Phase I 2009 Department of DefenseDefense Threat Reduction Agency -
SUBMARINE SHOCK LETHALITY STUDIES: AN OBJECTIVE APPROACH FOR LARGE STRAIN CALCULATIONS
SBC: Thornton Tomasetti, Inc. Topic: N/AADVANCED STRUCTURAL MATERIALS USED IN THE FABRICATION OF SUBMARINES CAN SUSTAIN LARGE STRAINS DURING THE FORMATION PROCESS CAUSED BY EXPLOSIVE LOADINGS. THE COMPUTATIONAL SOLID MECHANICS COMMUNITY HAS RECENTRLY RECOGNIZED SERIOUS SHORTCOMINGS IN CALCULATIONS USING MATERIAL MODELS IN THIS LARGE STRAIN REGION. BECAUSE OF THE IMPORTANCE OF CALCULATIONS IN UNDERSTANDING THE SHOCK RESPONSE OF SUBMARINE ...
SBIR Phase I 1989 Department of DefenseDefense Threat Reduction Agency -
Engineering Models for Damage to Structural Components Subjected to Internal Blast Loading
SBC: Thornton Tomasetti, Inc. Topic: DTRA08006Weidlinger Associates Inc. proposes to develop effective technology for simulating explosive detonations within civil buildings where the propagation of airblast and failure of weak internal walls are strongly coupled. We will conduct a field test program designed to complement other internal detonation testing efforts such as DTRA''s Distinct Cobra, expanding the available database. We will perfo ...
SBIR Phase II 2009 Department of DefenseDefense Threat Reduction Agency -
High Fidelity Modeling of Building Collapse with Realistic Visualization of Resulting Damage and Debris
SBC: Thornton Tomasetti, Inc. Topic: DTRA082005An approach for performing high fidelity modeling for blast and progressive collapse simulations of buildings will be developed. The modeling approach will allow complete simulations of building response to be performed within several days of computing time on desktop PCs. An 'easy to use' modeling interface will also be demonstrated in this effort. All response regimes will be addressed includi ...
SBIR Phase I 2009 Department of DefenseDefense Threat Reduction Agency -
SWaP-C Efficient High-Resolution High-Speed Digitizer and Processor
SBC: PRIXARC LLC Topic: NGA192001We propose to develop an efficient, fast, and low size, weight, power, and cost (SWaP-C) digitizer for use with fast photodetectors. High-speed data converters are critical in building a fast-reliable photon detector in a small form factor. We propose to combine i) ultra-low power analog design techniques, ii) well-known adaptive ADC topologies, iii) signal coherence Digital Signal Processing ( ...
SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency -
TrailBlazer: A GAN-Trained, High-Fidelity Track Simulator
SBC: KITWARE INC Topic: NGA192004Persistent wide area sensor coverage enables unique intelligence analytic capabilities such as pattern-of-life detection, unsupervised pattern discovery, and anomaly detection. As these capabilities incorporate machine learning and artificial intelligence techniques, large datasets are necessary for training and validation. However, the lack of datasets with high fidelity dynamic targets and acto ...
SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency -
ALURD: Automated Learning from Unsupervised Repositories of Data
SBC: ETEGENT TECHNOLOGIES, LTD. Topic: NGA201003Etegent proposes Automated Learning from Unsupervised Repositories of Data (ALURD). ALURD incorporates a trained detector to feed a semi-supervised discrimination apparatus that leverages state-of-the-art approaches.in semi-supervised learning (SSL). The need for automated labelling of overhead data is obvious, less obvious is that these unlabelled images provide an opportunity to improve auton ...
SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency -
MIPS
SBC: ATC-NY INC Topic: DTRA172003Next-generation high-performance computing (HPC) hardware, such as the Intel Xeon Phi Knights Landing Many-Integrated-Core processor, provide new deep memory architectures that offer the promise of increased performance. The challenge in taking full advantage of this architecture is selecting which data structures will be placed in the high-bandwidth memory. Optimizing data structure placement in ...
SBIR Phase II 2020 Department of DefenseDefense Threat Reduction Agency -
High-Fidelity Diagnostics of Aerosols and Vapors at High Temperatures and Pressures
SBC: SPECTRAL ENERGIES LLC Topic: DTRA182003There is a need to improve the understanding of physical and chemical processes involved in the evolution of chemical warfare agent (CWA) simulant aerosols and vapors that are interacting with combustion, deflagration, and detonation products. However, the measurement of aerosols and vapors is very challenging because of limited knowledge of the photophysics at varying temperatures and pressures, ...
SBIR Phase II 2020 Department of DefenseDefense Threat Reduction Agency -
Sporadic long-Term and Transferable Patterns of life (SPOTTER)
SBC: KITWARE INC Topic: NGA192005Aerial or spaced-based imaging assets cannot continuously monitor a single location or site of interest for prolonged periods of time such as weeks, months, or years without significantly sacrificing surveillance of other locations. Current approaches for modeling patterns of life (PoL) at a location are not capable of incorporating sporadic data and do not gracefully model daily to monthly or ye ...
SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency