Quantum Sensor System using Rydberg Atoms

Project period
-

AOI: Quantum Sensing Technologies

Innovation: 

In this Ohio Federal Research Network proposal, Team GhostWave will demonstrate a quantum sensing system, based on the integration of Rydberg atom quantum RF electric field sensors with telecommunications band wavelength converters and RF noise radar systems. The team will quantitatively characterize system levels of quantum advantage from the integration of state-of-the-art quantum technology with state-of-the-art-classical technology. The team anticipates that the improved sensitivity of...

Structural Materials Joining in Space

The Ohio State University logo
Project period
-

AOI: Commercial Space in Low Earth Orbit

Innovation: 

The proposed work will focus on the understanding and quantification of the challenges associated with materials joining in space conditions. This work includes developing and using an autonomous welding system that reproduces the vacuum, temperature, and gravity conditions encountered during manufacturing, maintenance, and repair in space. 

This work will advance the technology readiness level (TRL) of laser beam welding (LBW) of metals...

High Bandwidth Light Weight Modular GaN Based Utility Interactive DC Emulator

UA logo
Project period
-

AOI: High Power Energy Conversion

Innovation: 

A Direct Current Emulator (DCE) that can operate as a programmable DC power supply (source) and a DC load (sink) is of particular interest to many electrical system Hardware-In-the-Loop (HIL) applications, such as avionics, automotive, and space power. To meet the requirements of a DCE for these HIL applications, we are proposing the development of a modular and scalable high bandwidth bidirectional DCE that...

Ocular and Physio-Temporal Indicators of Cognitive State (OPTICS)

Project period
-

AOI: Human Performance

Innovation: 

OPTICS will leverage Kairos’s advanced software prototyping capability to implement a dashboard tool for real-time physiological monitoring and visualization of cognitive state. This project will capitalize and expand upon Kairos’s existing DoD-funded technology by incorporating ocular and physiological signals predictive of suboptimal cognitive states such as fatigue and loss of vigilance. Additionally, the team will apply robust machine learning approaches to dynamically classify and predict an...

Gradient Alloy Processing in Laser Powder Bed Fusion for Hypersonic Applications

Project period
-

AOI: Hypersonics

Innovation: 

This project is designed to advance the state of the art in multi-material deposition for hypersonic applications and simultaneously drive expertise in multi-material solutions at Ohio universities. Arctos Technology Solutions expects to use this project to refine multi-material deposition developed within our R&D test beds – if successful this will help grow the Dayton-based OA group as experts in this rapidly growing AM focus area. 

Objective: 

The...

A Machine Learning Framework for Digital Engineering of Hypersonic Vehicles with Quantified Prediction Uncertainty (Hypersonic ML FW)

Project period
-

AOI: Digital Engineering Tools

Innovation: 

The key innovation of this is effort is development of a machine learning framework for creating digital engineering models of hypersonic vehicles with quantified prediction uncertainty. This capability will be provided in a form compatible with generic integrated digital environments (IDE) so that direct benefit to a broad range of digital engineering efforts within the DoD can be provided. The key capabilities added to digital...