Litcius/Paper detail

GeN-ROM—An OpenFOAM®-based multiphysics reduced-order modeling framework for the analysis of Molten Salt Reactors

Péter German, Mauricio Tano, Carlo Fiorina, Jean C. Ragusa

2022Progress in Nuclear Energy20 citationsDOIOpen Access PDF

Abstract

This work presents a projection-based multiphysics Model Order Reduction (MOR) framework for the analysis of nuclear systems and its application to parametric simulations of Molten Salt Reactors (MSR). The framework, named GeN-ROM, is developed using OpenFOAM® and employs a Proper Orthogonal Decomposition aided Reduced-Basis technique (POD-RB). It can be used to reduce steady-state and transient multiphysics problems involving parametric fluid dynamics, heat exchange, and neutronics phenomena. For the treatment of structural elements in the hydraulic systems, a porous medium approach has been adopted. The reduction process is data-driven and snapshot information is extracted via POD to learn the solution manifold and to build global spatial basis functions. At the data collection phase, GeN-ROM makes use of the solvers available in GeN-Foam, a similarly OpenFOAM®-based multiphysics framework developed for the analysis of nuclear reactors. The global bases are used both to approximate the solution fields and to project the full-order equations onto lower-dimensional subspaces, thus considerably reducing the number of unknowns in a numerical system. This reduction leads to significant computational speedups, which is ideal for multi-query applications such as uncertainty quantification or design optimization. The developed tool has been tested using a 2D multiphysics model of the Molten Salt Fast Reactor (MSFR) with steady-state and transient scenarios, with speedups on the order of 10−105.

Topics & Concepts

MultiphysicsComputer scienceNeutron transportMolten saltModel order reductionParametric statisticsComputational scienceReduction (mathematics)Projection (relational algebra)Finite element methodAlgorithmPhysicsMathematicsThermodynamicsNeutronGeometryQuantum mechanicsStatisticsModel Reduction and Neural NetworksNuclear reactor physics and engineeringNuclear Engineering Thermal-Hydraulics