Multiphysics Pebble-Bed Reactor Control Rod Withdrawal Study
This work studied the responses of both a generic gas- and a fluoride-cooled PBR concept—the gPBR-200 and gFHR, respectively—during reactivity insertion accidents. Both models rely on 2-D axisymmetric simulations to solve the neutron flux distribution, nuclide concentrations, and temperature across the core—in addition to numerous representative pebble and TRISO particle simulations for determining fuel and […]
MOOSE Stochastic Tools: A module for performing parallel, memory efficient in-situ stochastic simulations
Stochastic simulations are ubiquitous across scientific disciplines. The Multiphysics Object-Oriented Simulation Environment (MOOSE) includes an optional module – stochastic tools – for implementing stochastic simulations. It implements an efficient and scalable scheme for performing stochastic analysis in memory. It can be used for building meta models to reduce the computational expense of multiphysics problems as […]
Accelerated statistical failure analysis of multifidelity TRISO fuel models
Statistical nuclear fuel failure analysis is critical for the design and development of advanced reactor technologies. Although Monte Carlo Sampling (MCS) is a standard method of statistical failure analysis for fuels, the low failure probabilities of some advanced fuel forms and the correspondingly large number of required model evaluations limit its application to low-fidelity (e.g., […]
Reliability Estimation of an Advanced Nuclear Fuel using Coupled Active Learning, Multifidelity Modeling, and Subset Simulation
Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel and determining its reliability is critical for the success of advanced nuclear technologies. However, TRISO failure probabilities are small and the associated computational models are expensive. We used coupled active learning, multifidelity modeling, and subset simulation to estimate the failure probabilities of TRISO fuels using […]
Reduced Order Models Generation for HTGRs Pebble Shuffling Procedure Optimization Studies
This report provides an initial study for producing reduced-order models (ROMs) of pebble-bed high temperature gas reactor (HTGR) models for the purposes of design optimization. As an initial study, this work is meant to be exploratory—identifying useful workflows and methods for ROM generation—and not meant to be a catch-all analysis of HTGR ROM generation and […]
Efficient high-fidelity TRISO statistical failure analysis using Bison: Applications to AGR-2 irradiation testing
The ability of tri-structural isotropic (TRISO) 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 containing defects. The Bison fuel performance code has capabilities to predict failure […]
Physics based modeling and data analytics
This presentation contains a summary of ongoing work within the physics-based modeling and data analytics work package within the Nuclear Materials Discovery and Qualification initiative (NMDQi). Topics include work on MOOSE-based crystal plasticity, molecular dynamics modeling of recombination in metals and alloys, the MOOSE Stochastic Tools Module, and machine learning and atomistic modeling to predict […]