Parameterized Model Order Reduction Strategy for Fast Running CFD-Quality Transient Transport through Nuclear Reactors

Computational fluid dynamics methods are increasingly used for high fidelity modeling of complex systems, especially nuclear power systems. For example, the phenomenon of thermal stratification in a sodium-cooled fast reactor under natural circulation conditions is resolvable with computational fluid dynamics, but not traditional system-level models. The high accuracy of computational fluid dynamics incurs increased computational cost, however. Therefore methods providing high quality results at a reduced cost are in high demand.The goal of this project is to develop software to enable the production of high quality reduced order models using a parameterized proper orthogonal decomposition approach. The technology will enable high fidelity fast running models for arbitrary transients to be constructed from a set of steady state simulations. The fast running models will then be used to compute boron concentrations in the lower plenum and core region of a reactor or density variations in stratified pools of sodium cooled fast reactors.A reduced order model production workflow using proper orthogonal decomposition will be established with accompanying software. Large eddy simulation example problems will be carried out to be used as test cases. A prototype model will be generated with a parameterized inlet mass flow rate. The proposed formulation will be revisited to add the effects of pressure gradients and to allow for parameterization of more boundary conditions of different types, such as pressure outlets. The stability of the models will be assessed and recommendations for stabilization, such as adding closure models, will be made for Phase II work.Commercial Applications and Other Benefits: Proper orthogonal decomposition and similar methods have been well understood for decades. However, they have not been widely adopted for a few reasons including that they are difficult and time consuming to compute, their stability properties are unfavorable, and their calculation requires ad hoc software development. By leveraging recent developments and internal expertise, each of these concerns is addressed in the proposed work. The models produced by this work will have applications in nuclear reactor design and safety analysis as well as drag force computation for airfoils and automotive frames, to name just a few. Nearly any industry with large modeling and simulation components will benefit. A key application in the nuclear engineering community is for production of surrogate computational fluid dynamics models to couple with system level codes for safety analyses. The tool will be usable to rapidly compute detailed boron concentrations in the lower reactor plenum after certain accidents.