@article{6b1f8a0a146540329a06079103f7cddc,
title = "High fidelity multiphysics tightly coupled model for a lead cooled fast reactor concept and application to statistical calculation of hot channel factors",
abstract = "A tightly coupled multiphysics code system is established using the MOOSE framework for hot channel factor (HCF) evaluation on a Lead Fast Reactor (LFR) concept. The coupled system is driven by the Griffin multiphysics coupling capability under which the MOOSE Heat Transfer module and NekRS computational fluid dynamics solver are coupled for conjugate heat transfer using the Cardinal application. The coupled capability is demonstrated on an LFR assembly model based on materials and geometry of a prototypical lead-cooled fast reactor design by Westinghouse Electric Company, LLC. Moreover, the work integrates the Multiphysics Object Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM) to perform calculations for statistical analysis of HCF. The coupling strategy and workflow demonstrated in this paper is not only useful for predicting accurate hot channel factors for different kinds of advanced reactors but also for other engineering applications such as control rod worth assessment, generation of high-fidelity database for Artificial intelligence (AI)/machine learning (ML) training, design optimization and multi-resolution modeling.",
keywords = "Cardinal, Griffin, Hot Channel Factor, MOOSE, Multiphysics Coupling, NekRS",
author = "Y. Yu and H. Park and A. Novak and E. Shemon",
note = "This work was supported by the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation Program (NEAMS) under the Multiphysics Applications Technical Area. The integration of the MOOSE Stochastic Tools Modules with NekRS and Cardinal was co-funded by the NEAMS Thermal Fluids Technical Area. Argonne National Laboratory's work was supported by the U.S. Department of Energy, Office of Nuclear Energy, under contract DE-AC02-06CH11357. We gratefully acknowledge the computing resources provided on Bebop, a High Performance Computing (HPC) cluster operated by the Laboratory Computing Resource Center at Argonne National Laboratory. This research made use of the resources of the High Performance Computing Center at Idaho National Laboratory, which is supported by the Office of Nuclear Energy of the U.S. Department of Energy and the Nuclear Science User Facilities under Contract No. DE-AC07-05ID14517. Support from NekRS developers (Elia Merzari, Dillon Shaver, Ananias Tomboulides, Paul Fisher), Griffin developers (Changho Lee, Javier Ortensi, Yaqi Wang, Zachary Prince, Vincent Laboure and Yeon Sang Jung), and the MOOSE framework team (Guillaume Giudicelli, Cody Permann, Derek Gaston, and Roy Stogner) was greatly appreciated. This work was supported by the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation Program (NEAMS) under the Multiphysics Applications Technical Area. The integration of the MOOSE Stochastic Tools Modules with NekRS and Cardinal was co-funded by the NEAMS Thermal Fluids Technical Area. Argonne National Laboratory 's work was supported by the U.S. Department of Energy , Office of Nuclear Energy , under contract DE-AC02-06CH11357 . This research made use of the resources of the High Performance Computing Center at Idaho National Laboratory , which is supported by the Office of Nuclear Energy of the U.S. Department of Energy and the Nuclear Science User Facilities under Contract No. DE-AC07-05ID14517 .",
year = "2025",
month = apr,
day = "15",
doi = "10.1016/j.nucengdes.2025.113915",
language = "English (US)",
volume = "435",
journal = "Nuclear Engineering and Design",
issn = "0029-5493",
publisher = "Elsevier B.V.",
}