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The molten salt reactor (MSR) flowing-fuel simulation capability of the Griffin-Pronghorn-coupled multiphysics code system developed by Idaho National Laboratory (INL) was verified against the Center National de la Recherche Scientifique (CNRS) MSR benchmark problem. Griffin and Pronghorn, which are INL's neutronics and thermal-hydraulics codes built upon the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, have been recently extended to handle the flowing fuel of MSRs causing the drift of delayed neutron precursors (DNP). In the Griffin-Pronghorn code system, Griffin provides the fission rate density to Pronghorn, which simulates the generation, decay, and transport of DNPs along with the fluid, and the redistributed DNP densities are fed back to Griffin. The coupling and transfers are largely automatically managed at the framework level by the powerful MultiApp system of MOOSE. The verification results against the CNRS benchmark problem demonstrate that the Griffin-Pronghorn code system can accurately simulate the unique physics phenomena of MSRs in both steady-state and transient conditions. [ABSTRACT FROM AUTHOR]

The Chebyshev Rational Approximation Method (CRAM) has become one of the dominant methods for solving the Bateman equations for nuclear fuel depletion analysis. Since its introduction over a decade ago, several improvements have been made to CRAM improving its accuracy and reducing its run time. We analyzed its run time using two previously published methods for solving the CRAM system of equations, direct matrix inversion (DMI) and sparse Gaussian elimination (SGE), for depletion systems of varying numbers of nuclides to see how the two methods perform relative to one another. In addition to these two methods, we introduced the Gauss-Seidel (GS) method for solving the CRAM system of equations and compared its performance relative to DMI and SGE for depletion systems with varying numbers of nuclides. We demonstrated that for practical purposes, GS is faster than SGE and DMI and achieves a practical level of accuracy. All testing was performed using the CRAM implementation in the Griffin reactor physics analysis application. [ABSTRACT FROM AUTHOR]

The whole-core transport code nTRACER has made many advances in recent years. Several innovative cross section treatment methods were developed, a new axial transport solver was introduced for stabilizing the 2D/1D scheme, and substantial computational enhancements were achieved using NVIDIA CUDA and Intel Math Kernel Library (MKL). In addition, gamma transport solver was implemented to predict the power distributions more physically, and the flexibility of the restart calculation was improved using an offline processing code nTIG (nTRACER Input Generator). This paper is the compilation of the recent progresses in nTRACER developments.

AbstractThe SOPHIA code is a graphical processing unit (GPU)–based smoothed particle hydrodynamics (SPH) framework for fundamental nuclear thermal-hydraulic and safety applications developed by Seoul National University. Focusing on particle-based SPH methods, the SOPHIA code provides capabilities for computational fluid dynamics–level analysis in addressing complex multiphase and multiphysics issues related to severe accidents and reactor safety. Since the SPH method requires high computational cost due to the nature of the particle-based method, the SOPHIA code was parallelized with multiple GPUs. However, using multiple GPUs may cause load imbalance as particles migrate between GPUs, which degrades performance.In this study, we developed a dynamic load-balancing algorithm to increase computational efficiency by reducing the load imbalance. Additionally, a novel cumulative time comparison approach is proposed as a criterion for adjusting boundaries between GPUs, ensuring low load imbalance. To evaluate the performance of the algorithm, three-dimensional dam-break simulations were conducted. The results demonstrated enhanced computational efficiency and equitable load distribution among GPUs compared to using fixed subdomains. Additionally, the developed algorithm was utilized to analyze the VULCANO VE-U7 experiment, and the results were well aligned with the experimental data. Therefore, the practical applicability of the proposed dynamic load-balancing algorithm in nuclear safety analyses has been confirmed. [ABSTRACT FROM AUTHOR]