Modeling the Seismic Response of Spent Nuclear Fuel in Dry Storage

The US Department of Energy’s Spent Fuel and Waste Science and Technology (SFWST) program is investigating the mechanical loading of spent nuclear fuel (SNF) to close knowledge gaps and inform the range of relevant loads for mechanical testing of irradiated SNF.  The...

Physics-informed Machine Learning for Control – DNN in a Dynamic Feedback Loop

This Case Study describes an approach to combining physical principles with Machine Learning (ML) for modeling and control of complex systems. Our approach was developed as part of a DARPA-funded research project. It was applied to oil reservoir management. While this Case Study provides an overview, technical details may be found in a separate publication [1].