SC Solutions Engineers Presented at SMiRT 26

SC Solutions, together with other nuclear industry leaders and engineers from around the world joined together at the 26th SMiRT conference, held in Berlin/Potsdam, Germany from July 10 – 15, 2022.  There, SC Solutions engineers contributed to new ideas for...

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].