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 ...

NP Photonics proposes to design and develop a compact and integrated radio frequency (RF) -to-optical transmitter at 1060 nm for balanced RF-over fiber photonic links by taking advantage of our mature single-frequency laser technology, multicore fiber fabrication technology, and substantial heterogeneous packaging experience and capability in fiber laser products. In this Phase I program, we will ...

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.

Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

In an effort to improve the design of radiation hardened electronic components, this proposal explores the feasibility of creating predictive modeling techniques for nanoscale material properties in advanced integrated electrical devices. This study encompasses the collaborative usage of high resolution Transmission Electron Microscope (HR-TEM) data, circuit design targeted electrical data, and ma ...

Radiation effects in microelectronic components are a significant concern for the reliability of DoD systems that operate at high altitudes or in outer space. Typical characterization efforts focus on macroscale degradation signatures from electrical measurements at device terminals. However, a comprehensive analysis of radiation-induced physical defects is not possible based solely on terminal me ...

Alphacore will evaluate and develop a new approach to multi-scale modeling of radiation effects in electronic device technologies based on novel material systems. Our approach aims to directly correlate nano-scale properties of novel materials systems with macro-scale electrical properties of devices constructed with those materials, and their radiation response. Radiation hardness assurance (RHA) ...

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 ...