Dr. Wen Jiang
Assistant Professor of Nuclear Engineering
Department of Nuclear Engineering
North Carolina State University

Abstract

The first part of this talk will be focused on the development of novel numerical methods for nuclear fuels performance modeling. Nuclear fuel is subject to severe thermal-mechanical and irradiation environments. Its thermal-mechanical behavior is strongly affected by underlying microstructure as well as the temperature and stress conditions. Cracking of nuclear fuel has a direct impact on the fission product release and thermal transport at both normal and off-normal operation conditions. A physics-based multi-scale fracture modeling capability is essential for safety and performance evaluation.

The performance of nuclear fuels is closely related to their material properties and manufacturing techniques. There is significant interest in applying additive manufacturing (AM) techniques to manufacture nuclear fuel systems. Compared to traditional fuel production techniques, AM technique greatly simplifies the fabrication procedure, reduces the production time and cost, and provides additional flexibility to nuclear fuel design for better thermal and mechanical performance. Modeling and simulation can provide the insight for a rational design by addressing the basic science and engineering needs for AM process, leading to a mechanistic understanding of processing-structure-property relationships, which are fundamental to design and develop innovative fabrication techniques for nuclear fuels. In the second part of this talk, recent progress on the multiscale additive manufacturing process modeling will be reviewed.

Biography

Dr. Wen Jiang received a Ph.D. in mechanical engineering and materials science from the Duke University. Prior to joining the NC State faculty, he was a computational scientist in the Computational Mechanics and Materials Department at the Idaho National Laboratory. Jiang works on computational method development for nuclear material modeling and multi-physics simulation. He is a key developer for the BISON nuclear fuel simulation code which won R&D 100 Award in 2022, and he leads the development of open-source multiscale additive manufacturing simulation code in MOOSE Application Library for Advanced Manufacturing Utilities (MALAMUTE). In addition, he is actively contributing to the open-source MOOSE simulation framework. Dr. Jiang has published more than 50 peer-reviewed journal papers within the above-mentioned topics.

Thursday, September 14. 2023
4:00 pm seminar

zoom link upon request

Room 1202 Burlington Labs