Award Data

Condition-based maintenance plus (CBM+), and cyber-physical systems (CPS) in general, depend on correct sensor data for analysis, decision making and control loops. If the sensor data that arrives at the point of processing is not correct, or more accurate, is outside its accepted error range, then any further processing will be incorrect as well. This could result in, in the case of CBM+, not det ...

High power generation at millimeter wave (mm-wave) frequencies is expensive and the concurrent need for wide bandwidths at these frequencies creates an extremely challenging problem. Currently the most stringent requirements for mm-wave power and bandwidth can only be practically met by vacuum electronics (VE) technology. At present, vacuum amplifiers with the required performance are prohibitivel ...

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 ...

The Navy desires a compact and highly efficient S-band magnetron source with stabilized output capable of modulation over a narrow bandwidth. In this Phase I STTR proposal, Physical Sciences Inc (PSI) outlines the development of an injection locked “cooker” magnetron which can be used for frequency shift keying (FSK) or phase shift keying (PSK) in a portable high power transmission device. In ...

There are currently no vaccines or therapeutics available for Marburg Virus Disease (MVD). Given the specter of weaponization and the terrible morbidity and high mortality rate of MVD, this represents a critical threat to the operational readiness of the Warfighter. While traditional vaccines have contributed greatly to public health, they have some limitations especially in the context of operati ...

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 ...

Effective mission planning is critical for military strategy and execution. This process is complex as human operators must consider many variables (e.g., resource limitations, threats, risks) when formulating a plan to accomplish mission goals. Although powerful tools, such as the Navy’s Joint Mission Planning System (JMPS), provide advanced functionality, mission planning remains a hybrid acti ...

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 ...

EMI resilient RF Photonic Links are critical for connecting remote antennas in the next generation Navy electronics warfare (EW) architecture. Current commercially available RF/photonic link technologies have deficiencies in dynamic range, noise figure, and SWaP performance. For a solution, this STTR project aims to develop a novel wide dynamic range, low noise RF photonic link, where the key comp ...