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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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SBC: COMBUSTION RESEARCH & FLOW TECHNOLOGY INC Topic: N/AN/A
STTR Phase I 2000 Department of DefenseAir Force -
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SBC: COMBUSTION RESEARCH & FLOW TECHNOLOGY INC Topic: N/AN/A
STTR Phase II 2000 Department of DefenseAir Force -
Physical Sub-Model Development for Turbulence Combustion Closure
SBC: COMBUSTION RESEARCH & FLOW TECHNOLOGY INC Topic: AF13AT12ABSTRACT: The innovation proposed is a computationally-tractable, physics-based, portable turbulent combustion modeling strategy for application to a wide range of Air Force aero-propulsive systems, including augmentors, liquid rockets and scramjets. This modeling strategy will be implemented within an Application Programming Interface (API) library suitable for easy integration within Air Force ...
STTR Phase I 2014 Department of DefenseAir Force -
Decision Making under Uncertainty for Dynamic Spectrum Access
SBC: INFOBEYOND TECHNOLOGY LLC Topic: AF13AT02ABSTRACT: Due to scarcity of spectrum, Dynamic Spectrum Access (DSA) becomes a needed technology to improve the utilization of electromagnetic spectrum for DoD satellite communication. However, current DSA approaches are developed for terrestrial communications without addressing the unique challenges for SATCOM environments such as error-prone spectrum sensing, high mobility, and large coverage. ...
STTR Phase I 2014 Department of DefenseAir Force -
Secure Efficient Cross-domain Protocols
SBC: INFOBEYOND TECHNOLOGY LLC Topic: AF13AT08ABSTRACT: Coordinating and sharing information across multi-level security (MLS) networks are of great interest in many military applications. However, it is very challenging to accomplish those goals due to the heterogeneous security classifications of different network domains. The recent proposed cross-domain solutions (CDS) provide initial steps to make such applications possible. However, th ...
STTR Phase I 2014 Department of DefenseAir Force -
High Speed High Accuracy Artificial Neural Networks for UAV based Target Identification
SBC: UHV TECHNOLOGIES, INC. Topic: AF18BT007The machine learning and artificial intelligence community has recently garnered much attention for ground breaking performance of novel neural network architectures for self-driving cars. One of the machine learning methods used in self-driving cars is semantic segmentation. In this fashion each pixel in an image is label with a class, allowing for contour-based image segmentation which is differ ...
STTR Phase I 2019 Department of DefenseAir Force -
Contour Based Image Segmentation
SBC: VY CORP Topic: AF18BT007We propose to detect and identify moving objects in airborne imagery and full-motion video in unconstrained environments. Conventional techniques result in too many false positives; a new topology is needed to automatically detect and identify moving targets from a moving platform in airborne imagery. Our software is designed to analyze video imagery and deliver curve metadata that can be organize ...
STTR Phase I 2019 Department of DefenseAir Force -
Multiphysics Modeling of Dynamic Combustion Processes
SBC: COMBUSTION RESEARCH & FLOW TECHNOLOGY INC Topic: AF18BT010The objective of this effort is to develop a zonal, multi-physics modeling framework for dynamic combustion processes that can capture relevant local physics and simulate system behavior. The primary focus will be on liquid rocket combustors with secondary application to gas turbines. The goal is to obtain an order of magnitude reduction in current simulation time within acceptable error limits. T ...
STTR Phase I 2019 Department of DefenseAir Force -
Technical training software platform using machine learning and AR for Air Force maintenance and service operation
SBC: DISTAT CO Topic: AF19BT001A comprehensive technical training software platform combining computer vision and Augmented Reality (AR) technologies can transform the human learning process and experience. Computer vision is leveraged to understand the physical environment, while AR is used to superimpose contextual information onto the physical world. We aim to provide software solution using AR tools and systems to address s ...
STTR Phase I 2019 Department of DefenseAir Force -
Open Call for Science and Technology Created by Early-Stage (e.g. University) Teams
SBC: ESTAT ACTUATION INC Topic: AF19BT001Designing actuation hardware for autonomous systems is challenging due to the high weight and power consumption of conventional actuators and clutches. Compared to existing clutch technologies, the electroadhesive clutches produced by ESTAT have exceptional holding force as a ratio of both mass and power consumption. They weigh 10x less and consumes 1000x less power than other clutching technologi ...
STTR Phase I 2019 Department of DefenseAir Force