Nuclear Forensics
UQ and ML for Nuclear Forensics
We are part of the United States Department of Energy (US DOE) National Nuclear Security Administration (NNSA) Consortium for Nuclear Forensics (CNF). The CNF is a $25 million consortium over 5 years (2023-2028) led by the University of Florida. The CNF comprises 16 Universities and 7 National Laboratories that contribute to important research fields within nuclear forensics. This will be achieved by focusing on five main research areas: Rapid Turnaround Forensics, Advanced Analytical Methods, Ultrasensitive Measurement, Signature Discovery and Prompt Effects which will be achieved by using the combined expertise in radiochemistry, geochemistry, analytical chemistry, nuclear material science, shock physics, quantum-enabling sensing, high performance computing (HPC)/data science and training and education. Our goal is to develop inverse UQ methods for improving the quality of nuclear data for radiation transport simulations in nuclear forensics applications, as well as to combine scientific machine learning and UQ to improve the predictive modeling of fallout formation.