About this Abstract |
| Meeting |
Materials in Nuclear Energy Systems (MiNES) 2025
|
| Symposium
|
Materials in Nuclear Energy Systems (MiNES) 2025
|
| Presentation Title |
Preliminary Results of a Computationally Generated Dataset for use in a Constitutive Semi-Empirical Buffer Densification Model for BISON |
| Author(s) |
Caitlyn Parsons, Wen Jiang, Brian Wirth |
| On-Site Speaker (Planned) |
Caitlyn Parsons |
| Abstract Scope |
The performance of TRistructural ISOtropic (TRISO) fuel particles is a significant interest to the nuclear industry for use in advanced reactors such as high-temperature gas reactors (HTGRs), fluoride salt-cooled reactors (FHRs), and microreactors. Qualification of this fuel form includes determining fuel failure mechanisms and the corresponding probability of fuel failure. For high temperature microreactor conditions, current empirically based models predict that TRISO fuel failure will occur by palladium (Pd) attack on the silicon carbide (SiC) layer that is accelerated by cracks within the inner pyrolytic carbon (IPyC) layer caused by nonuniform buffer-IPyC debonding behavior. This scope of this work consists of performing high fidelity finite element simulations of the porous buffer layer densification processes to generate a large computational dataset to inform an improved engineering scale model for use in the fuel performance code BISON. The mesh explicitly includes pore shape and density representative of the as-fabricated buffer layer microstructure informed by microscopy. Boundary conditions representative of the stresses induced by kernel expansion and gas flux into the buffer are systematically varied to generate a dataset that samples the range of temperatures, burnup, and gas release conditions to fit an improved constitutive model for buffer densification. Preliminary results are presented including mesh generation and the resulting predicted stress, strain, and density evolution of the buffer layer. |
| Proceedings Inclusion? |
Undecided |