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

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

Project period
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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...

Digital Engineering for Hypersonics

Event Recap: Expanding New Horizons with Ohio Federal Research Network and NASA Glenn Research Center

OFRN/NASA GRC Meeting
Gradient Alloy Processing
Quantum Sensor System
OPTICS
GaN Based DC
LAWN
Digital Engineering for Hypersonics
Brook Park, Ohio – On December 5, 2023, key stakeholders in aerospace and defense joined to expand collaborative research and innovation between NASA Glenn Research Center (NASA GRC) and the Ohio Federal Research Network (OFRN). The aim of the event...

The Ohio Federal Research Network awards $6.85 million to six Ohio organizations to advance aerospace innovation in Ohio

OFRN Round 6
Gradient Alloy Processing
Quantum Sensor System
OPTICS
Space Materials Joining
Digital Engineering for Hypersonics
Dayton, Ohio – The Ohio Federal Research Network (OFRN) program awarded a total of $6.85 million to six Ohio-based organizations representing industry and academia and their collaborators to advance science and technology innovation for U.S. national...