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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.
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SBC: CLEAR SCIENCE CORP Topic: N13AT001
Clear Science Corp. and the University of Texas at Austin will develop and demonstrate technology that accurately quantifies aero-optical distortion associated with high-energy laser (HEL) weapons on rotorcraft and will utilize the information in designing adaptive optics (AO) systems to maximize HEL system performance over the full range of flight conditions. Aero-optical distortion arises from v ...STTR Phase I 2013 Department of DefenseNavy
SBC: MZA ASSOCIATES CORP Topic: N13AT001
MZA partnered with the University of Notre Dame proposes to conduct high-fidelity computational fluid dynamics (CFD) simulations providing volumetric time-resolved aero-optical disturbance modeling for rotary-wing aircraft flow dominated by wing-tip vortices. We will develop detailed wave-optics models of a baseline Navy helicopter beam director including engineering-level simulations of the beam ...STTR Phase I 2013 Department of DefenseNavy
SBC: TAI-YANG RESEARCH COMPANY Topic: N19AT016
Energy to Power Solutions (e2P) has teamed with quench detection (QD) expert Dr. Yuri Lvovsky (retired GE), Dr. Sastry Pamidi of the Center for Advanced Power Systems (FSU-CAPS), and American Superconductor Corporation (AMSC) to design, fabricate, and test a robust, reliable, and low cost QD system. e2P’s proposed system is a vastly different quench avoidance system that will provide multiple le ...STTR Phase I 2019 Department of DefenseNavy
SBC: NOVATEUR RESEARCH SOLUTIONS LLC Topic: N13AT016
This STTR Phase I project will demonstrate the feasibility and effectiveness of novel biologically-inspired computational memory models for on-board exploitation of long-duration sensor data streams to enable autonomous missions in unknown environments. The key innovation in this effort is a computationally and space-efficient computational memory model that is able to: i) handle long-duration dat ...STTR Phase I 2013 Department of DefenseNavy
SBC: XL SCIENTIFIC LLC Topic: N19AT001
Verus Research and the University of New Mexico (UNM) are pleased to respond to the Navy Phase I STTR solicitation N19A-T001 titled “Optimized Higher Power Microwave Sources.” Verus Research, in collaboration with UNM, propose to develop a GW-class, S-band, high power microwave (HPM) source to integrate in vehicle and vessel stopping systems. Our integrated approach ensures the objectives for ...STTR Phase I 2019 Department of DefenseNavy
SBC: CORNERSTONE RESEARCH GROUP INC Topic: N18BT031
Large aerospace composite structures currently require autoclaves and ovens to achieve desired performance which are expensive to purchase, costly to operate, and often limit part size and production rate. Ovens and autoclaves rely on convective heating which is inefficient, consumes large amounts of energy, and can be difficult to predict. Alternative cure processes using external heaters or hot ...STTR Phase I 2019 Department of DefenseNavy
SBC: CONTINUOUS SOLUTIONS LLC Topic: N19AT007
The primary objective is to develop electric machine/drive topologies and power architectures that achieve the power densities required for 50% more power without the increase in weight or space requirements. In addition to PMSM-based designs, two new machine topologies will be considered. The first is a trapped flux coreless (TFC) machine that utilizes superconducting pucks made of YBCO to produc ...STTR Phase I 2019 Department of DefenseNavy
SBC: MANTEL TECHNOLOGIES, INC. Topic: N19AT013
The U.S. Navy seeks methods to improve the fuel economy of marine diesel engines through utilization of waste heat. Low temperature engine jacket water, lubrication oil, and aftercooler air are largely untapped streams of thermal energy on these ships, but their utilization circumvents many operation challenges associated with exhaust gases. For example, variable and high exhaust gas temperatures ...STTR Phase I 2019 Department of DefenseNavy
SBC: METRON INCORPORATED Topic: N19AT017
Metron and Northeastern University propose to design, develop, and validate a proof-of-concept predictive Graph Convolutional Network (GCN) capability using open source Reddit and GDELT data. We propose: (1) to extract and preprocess open-source Reddit and GDELT data, (2) to design a predictive graph convolutional neural network model, (3) to implement and train that model, and (4) to validate the ...STTR Phase I 2019 Department of DefenseNavy
SBC: SCIENTIFIC FORMING TECHNOLOGIES CORPORATION Topic: N10AT028
While there are established methods available in determining the fatigue life of critical rotating components, there is still room for improvement for better understanding and prediction of life limiting factors. Improved risk assessment of jet engine disk components would require probabilistic modeling capability of the evolution of microstructural features, residual stresses and material anomali ...STTR Phase I 2010 Department of DefenseNavy