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[Seminar] Multi-scale failure analysis of nuclear fuels
April 25 @ 4:00 pm - 5:00 pm
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. This talk will be focused on the development of novel fracture and damage modeling methods for both ceramic fuel pellets and tri-structural isotropic (TRISO) particle fuels. At engineering scale of a ceramic fuel pellet, the extended finite element method is developed to study random crack initiation and subsequent propagation of interacting thermally induced cracks. At mesoscale, a phase-field fracture model is developed to simulate 3D porosity dependent intergranular fracture as well as fine fragmentation of high burnup fuel during a loss-of-coolant accident. For TRISO particle fuels, the ability of the fuel to contain fission products is largely dictated by the quality of the manufacturing process, since most of the fission product release is expected to occur due to coating layer failure in a small number of particles at the locations of defects. To account for statistical variation in physical dimensions and material properties from particle to particle, a statistical failure analysis approach that considers multiple failure modes is developed to compute failure probability for a statistically sampled batch of particle. The failure determination is further coupled to the fission product diffusion at both a particle and fuel element scale. The coupled failure and diffusion analysis approach enables realistic calculation of fission product release from the many particles in a TRISO-fueled reactor.
Dr. Wen Jiang is a computational scientist in the Computational Mechanics and Materials Department at the Idaho National Laboratory. After receiving his Ph.D. in Mechanical Engineering and Materials Science from Duke University, he joined INL in 2015 to work on computational methods for nuclear material modeling and multi-physics simulation. Dr. Jiang is a main developer for the Bison nuclear fuel simulation code which won R&D 100 Award in 2022, and he is also actively contributing to the open-source MOOSE simulation framework, structural component aging simulation codes Grizzly and additive manufacturing simulation code in MOOSE Application Library for Advanced Manufacturing Utilities (MALAMUTE). Dr. Jiang currently leads the development of multi-scale TRISO particle fuels modeling for DOE’s Nuclear Energy Advanced Modeling and Simulation program (NEAMS).
Monday, April 25. 2022
4:00 pm seminar
Hybrid Option (Speaker is in person)
zoom (link upon request)
Room 1202 Burlington Labs