Award Data

Under this STTR solicitation N20B-T028, the goal is to build on the strengths of HyPerComp’s development in the HDphysics suite of tools to meet NAVAIR’s requirements in solving large-scale problems in electromagnetics.  One area that will receive a major attention in this effort is the development of high order curved meshes for arbitrary geometries with small- and large-scale features that ...

Performing accurate simulations of large- and multi-scale electromagnetics problems has far-reaching implications in a variety of engineering and scientific disciplines. The same physics governs a diversity of applications including problems of importance for NAVAIR such as complex radome-antenna and antenna-platform interactions.  Such simulation problems involve complex materials, multiple feed ...

In this program, we propose to adapt a new, high-performance integration platform for RF photonics to operation at 1um, and to realize integrated optical transmitters that meet the requirements of the program.

There is a critical need for electrification of transportation systems. The proposed technology enables the development of very high-power density permanent magnet motors, which when coupled to an integrated SiC drive allows for an overall specific power beyond 12 kW/kg. The proposed concept relies on the tight integration of a high-power density dual-rotor permanent magnet motor, high power densi ...

There is a critical need for electrification of transportation systems. The proposed technology enables the development of very high-power density permanent magnet motors, which when coupled to an integrated SiC drive allows for an overall specific power beyond 12 kW/kg. The proposed concept relies on the tight integration of a high-power density dual-rotor permanent magnet motor, high power densi ...

There is a critical need for electrification of transportation systems. The proposed technology enables the development of very high-power density permanent magnet motors, which when coupled to an integrated SiC drive allows for an overall specific power beyond 12 kW/kg. The proposed concept relies on the tight integration of a high-power density dual-rotor permanent magnet motor, high power densi ...

We propose a suite of video processing algorithms utilizing the machine learning (ML) techniques of artificial intelligence (AI) reinforcement learning, deep learning, and transfer learning to process submarine imagery obtained by means of periscope cameras. Machine learning (ML) can help in addressing the challenge of human failure of assessing the data of periscope imagery. Though pre-tuned blac ...

Areté and the Machine Learning for Artificial Intelligence (MLAI) Lab at the University of Arizona (UofA) will develop and demonstrate new approaches that improve the performance of in situ machine learning (ML) algorithms as they evolve over time, adapt to new environments, and are capable of transferring their learned experiences across platforms.  Technological advances that will be brought t ...

Areté and the Machine Learning for Artificial Intelligence (MLAI) Lab at the University of Arizona (UofA) will develop an interactive scenario building tool capable of generating realistic synthetic 360° videos in real-time for use in training simulators for periscope operators .  We refer to this solution as RealSynth360.  This novel capability will be created by combining the latest advances ...

Current design tools for gas turbine engines invoke a variety of simplifying assumptions to estimate heat transfer to solid/metal engine components (e.g., isothermal boundary conditions). These approximations are often not valid, result in inaccurate predictions of heat transfer, and ultimately compromise the thermal integrity of propulsion and power systems. Wall-modeled large eddy simulation (WM ...