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...
Abstract We present a robust control system and methodology for physics-informed artificial intelligence (PAI) used to optimize and improve oil recovery, demonstrated in the Yates Field operated by the Kinder Morgan CO2 company. The system consists of a robust control...
Inclusion of incoherency effects in soil-structure interaction (SSI) analysis provides a more realistic determination of earthquake induced building structural responses than those obtained considering coherent ground motion. Separately, industry demand for...
This presentation summarizes the methodology and results from a recent seismic evaluation of a safety-class fire water storage tank. Tanks such as this are common at both DOE and NRC regulated nuclear facilities and their safety function following earthquake is relied...
Motivation The last 3 years have seen an increased demand for analog, MEMS and RF chips, which has led to a shortage in both 200mm fab capacity as well as equipment. This has sparked a new interest among equipment makers to refurbish used 200mm tools, develop entirely...
