Accelerated Parallel Numerical Simulation of Large-Scale Nuclear Reactor Thermal Hydraulic Models by Renumbering Methods

Abstract

Numerical simulation of thermal hydraulics of nuclear reactors is widely concerned, but large-scale fluid simulation is still prohibited due to the complexity of components and huge computational effort. Some applications of open source CFD programs still have a large gap in terms of comprehensiveness of physical models, computational accuracy and computational efficiency compared with commercial CFD programs. Therefore, it is necessary to improve the computational performance of in-house CFD software (YHACT, the parallel analysis code of thermohydraulices) to obtain the processing capability of large-scale mesh data and better parallel efficiency. In this paper, we will form a unified framework of meshing and mesh renumbering for solving fluid dynamics problems with unstructured meshes. Meanwhile, the effective Greedy, RCM (reverse Cuthill-Mckee), and CQ (cell quotient) grid renumbering algorithms are integrated into YHACT software. An important judgment metric, named median point average distance (MDMP), is applied as the discriminant of sparse matrix quality to select the renumbering methods with better effect for different physical models. Finally, a parallel test of the turbulence model with 39.5 million grid volumes is performed using a pressurized water reactor engineering case component with 3*3 rod bundles. The computational results before and after renumbering are also compared to verify the robustness of the program. Experiments show that the CFD framework integrated in this paper can correctly perform simulations of the thermal engineering hydraulics of large nuclear reactors. The parallel size of the program reaches a maximum of 3072 processes. The renumbering acceleration effect reaches its maximum at a parallel scale of 1536 processes, 56.72%. It provides a basis for our future implementation of open-source CFD software that supports efficient large-scale parallel simulations.