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Award Data
The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.
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Development of powder bed printing (3DP) for rapid and flexible fabrication of energetic material payloads and munitions
SBC: MAKEL ENGINEERING, INC. Topic: DTRA16A001This program will demonstrate how additive manufacturing technologies can be used with reactive and high energy materials to create rapid and flexible fabrication of payload and munitions. Our primary approach to this problem will be to use powder bed binder printing techniques to print reactive structures. The anticipated feedstock will consist of composite particles containing all reactant spe ...
STTR Phase I 2016 Department of DefenseDefense Threat Reduction Agency -
Production of Chemical Reagents for Prompt-Agent-Defeat Weapons
SBC: NALAS ENGINEERING SERVICES INC Topic: DTRA14B001The US DoD requires robust ways of neutralizing threats posed by hostile powers and terrorist organizations that may be in possession of dangerous weapons of mass destruction (WMDs). Unfortunately, the weapons currently available to the DoD do not offer a way for the WMD to be destroyed without risking the spread of that material throughout the area. The strategy for the defeat of biological weapo ...
STTR Phase I 2015 Department of DefenseDefense Threat Reduction Agency -
Modular Pulse Charger and Laser Triggering System for Large-Scale EMP and HPM Applications
SBC: SCIENTIFIC APPLICATIONS & RESEARCH ASSOCIATES Topic: DTRA16A004For effective protection against EMP and HPM threats, it is important to understand the physics of the threats, and also to quantify the effects they have on electrical systems. EMP and HPM vulnerability testing requires delivery of high peak power and electric fields to distant targets. The most practical solution to simulate such environments is to develop a modular, optically-isolated MV-antenn ...
STTR Phase I 2016 Department of DefenseDefense Threat Reduction Agency -
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