DESIGN OF A CODE-AGNOSTIC DRIVER APPLICATION FOR HIGH-FIDELITY COUPLED NEUTRONICS AND THERMAL-HYDRAULIC SIMULATIONS

While the literature has numerous examples of Monte Carlo and computational fluid dynamics (CFD) coupling, most are hard-wired codes intended primarily for research rather than as standalone, general-purpose codes. In this work, we describe an open source application, ENRICO, that allows coupled neutronic and thermal-hydraulic simulations between multiple codes that can be chosen at runtime (as opposed to a coupling between two specific codes). In particular, we outline the class hierarchy in ENRICO and show how it enables a clean separation between the logic and data required for a coupled simulation (which is agnostic to the individual solvers used) from the logic/data required for individual physics solvers. ENRICO also allows coupling between high-order (and generally computationally expensive) solvers to low-order “surrogate” solvers; for example, Nek5000 can be swapped out with a subchannel solver.

ENRICO has been designed for use on distributed-memory computing environments. The transfer of solution fields between solvers is performed in memory rather than through file I/O.We describe the process topology among the different solvers and how it is leveraged to carry out solution transfers. We present results for a coupled simulation of a single light-water reactor fuel assembly using Monte Carlo neutron transport and CFD.

High-resolution coupled physics solvers for analysing fine-scale nuclear reactor design problems

An integrated multi-physics simulation capability for the design and analysis of current and future nuclear reactor models is being investigated, to tightly couple neutron transport and thermal-hydraulics physics under the SHARP framework. Over several years, high-fidelity, validated mono-physics solvers with proven scalability on petascale architectures have been developed independently. Based on a unified component-based architecture, these existing codes can be coupled with a mesh-data backplane and a flexible coupling-strategy-based driver suite to produce a viable tool for analysts. The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in order to reduce the overall numerical uncertainty while leveraging available computational resources. The coupling methodology and software interfaces of the framework are presented, along with verification studies on two representative fast sodium-cooled reactor demonstration problems to prove the usability of the SHARP framework.