Date/Time
Date(s) - 10/12/2023
1:55 pm - 2:55 pm
Location
Rhines Hall 125
Categories
Abstract
Advanced reactor design and analysis encounters many new and unique challenges with more stringent operation conditions and safety requirements. Reactor physics, the backbone area in nuclear engineering that deals with the neutronics aspect of a nuclear reactor and its associated components, plays a vital role in reactor design and analysis.
The principle task of the reactor physicist is to predict a detailed yet macroscopic-level neutron behavior in a reactor core at various conditions. Currently, this task can be accomplished via many state-of-the-art numerical modeling and simulation techniques that rely heavily on advanced computational hardware and computational methodologies.
Though great strides have been achieved over the decades in developing computational tools for modeling realistic reactor physics problems, the current methodologies will most likely lack the higher efficiency and fidelity requirements needed to address the new design and operational challenges. Future reactor designs will thus favor new modeling and simulation paradigms.
The purpose of this talk is to provide an overview of the challenges faced by reactor physics modeling and simulations, and summarize the speaker’s recent research activities that are pertaining to innovative solutions based on advanced data science analytics and machine learning approaches in reactor physics applications and beyond.
Bio
Zeyun Wu, Ph.D.
Associate Professor
Virginia Commonwealth University
Dr. Zeyun Wu is an Associate Professor in the Department of Mechanical and Nuclear Engineering at the Virginia Commonwealth University (VCU) and directs the computational reactor physics research group at VCU. Dr. Wu earned his B.S. and M.S.E. degrees in Engineering Physics from Tsinghua University in China, and Ph.D. degree in Nuclear Engineering from Texas A&M University.
Dr. Wu’s research interests encompass reactor physics, advanced reactor design and analysis, computational methods on neutron transport, uncertainty and sensitivity analysis, inverse transport problems, advanced data analytics and machine learning. Dr. Wu has published over 90 technical journal articles, conference papers and summaries based on his research work. Since he joined VCU as a faculty member in the nuclear engineering program in August 2017, Dr. Wu has been leading and co-leading multiple US DOE-sponsored R&D projects in a variety of advanced reactor analysis, including sodium fast reactor (SFR), molten salt reactor (MSR), and pebble bed type high temperate gas-cooled reactor (PB-HTGR).