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AbstractIn the present work, two large eddy simulations (LESs) of single isothermal jets discharging into large enclosure facilities are proposed. The geometries and tested flow conditions correspond to scaled experiments of the upper plenum of high-temperature gas-cooled reactors. More specifically, two reference experiments were conducted at Texas A&M University and Michigan University. The objective of the present work is to validate these simulations with their corresponding reference experiments. The proposed LES models are performed with NekRS, a spectral element code with graphics processing unit capabilities developed at Argonne National Laboratory. These simulations were performed on the Summit supercomputer at Oak Ridge National Laboratory. For validation purposes, first- and second-order statistics from the computational fluid dynamics (CFD) calculation are compared with measurements obtained from the experiments. The models proved to be accurate, as these results are in good agreement. Additionally, flow visualization is provided showing that these models are able to retrieve similar effects to what are described in the literature for this type of flow configuration. Finally, the proposed models are part of a broader effort under the current Integrated Research Project of Nuclear Energy Advanced Modeling and Simulation 1.1, whose main objective is to deliver fast-running models to accurately predict complex physical phenomena, including for instance, turbulent mixing and thermal stratification. In this regard, the CFD models proposed here will be used to generate a high-fidelity data set to be applied in conjunction with data-driven methods to improve turbulence modeling closures.

AbstractFlow circulation and heat removal through shield and reflector assemblies can have major impacts on safety in long transients for sodium fast reactors (SFRs). These transients are typically categorized by reduced flow rates and large-scale organized flow patterns, including potential intra-assembly circulation. Such low-flow cases can provide challenges for experiments because of complications in measuring the flow rates and temperatures with high accuracy in different areas. This consequently also raises the uncertainty of many modeling approaches for these phenomena. In an effort to address some of these issues, high-fidelity large eddy simulations are performed using the highly parallel solver NekRS. A 19-pin configuration of a tight-lattice wire-wrapped hexagonal bundle (pitch-to-diameter ratio = 1.07), representing a prototypical internal configuration of a shield assembly, was investigated. The sodium flow was set at a bundle Reynolds number of 2000, with simulations being performed for modified Richardson numbers of 0.0 (i.e., no buoyancy), 0.01, and 0.04, where mixed-convection effects are anticipated. The flow and temperature fields for these cases are discussed in detail. The high-fidelity data should prove useful as reference data for expanding and improving on various reduced-resolution approaches. A basic framework for combining subchannel and computational fluid dynamics methodologies in SFRs is also presented, with preliminary results from simulations of light water reactor bundles and a discussion of changes that need to be made for potential application to SFRs.

AbstractTraditional one-dimensional system thermal-hydraulic analysis has been widely applied in the nuclear industry for licensing purposes because of its numerical efficiency. However, such tools have inherently limited opportunities for modeling multiscale multidimensional flows in large reactor enclosures. Recent interest in three-dimensional coarse grid (CG) simulations has shown their potential in improving the predictive capability of system-level analysis. At the same time, CGs do not allow one to accurately resolve and capture turbulent mixing and stratification, whereas implemented in CG solvers relatively simple turbulence models exhibit large model form uncertainties. Therefore, there is a strong interest in further advances in CG modeling techniques. In this work, two high-to-low data-driven (DD) methodologies (and their combination) are explored to reduce grid and model-induced errors using a case study based on the Texas A&M upper plenum of a high-temperature gas-cooled reactor facility. The first approach relies on the use of a DD turbulence closure [eddy viscosity predicted by a neural network (NN)]. A novel training framework is suggested to consider the influence of grid cell size on closure. The second methodology uses a NN to predict velocity errors to improve low-fidelity results. Both methodologies and their combination have shown the potential to improve CG simulation results by using data with higher fidelity.

AbstractThe Sodium-Cooled Fast Reactor (SFR) is a promising concept chosen in the Generation IV International Forum as a possible design for pursuing the sustainable use of nuclear energy. Its core consists of multiple hydraulically isolated assemblies, with a tightly packed triangular lattice array of fuel pins enclosed in a hexagonal duct present within each assembly. Helical wire spacers are wrapped along the axis of the rods to maintain a gap between them, inducing a secondary flow, increasing the channel mixing, and enhancing convective heat transfer. In this study, a direct numerical simulation campaign is conducted for a simplified 7-pin wire wrapper geometry, with Reynolds numbers ranging from $Re$Re = 1000 to 10 000 and a Prandtl number of $Pr$Pr = 0.005, to investigate heat transfer in low-flow conditions. The wire wrapper case is compared to a bare bundle case with seven pins. The results are discussed, and heat transfer predictions are compared between our numerical results and classic correlations. An anisotropy invariant map is obtained for the above-mentioned cases, and turbulent kinetic energy and turbulent heat flux budgets are computed and analyzed. Our findings provide unique insights into the flow behavior within a wire-wrapped bundle.

AbstractWhile the literature has numerous examples of Monte Carlo (MC) and computational fluid dynamics (CFD) coupling, most are hardwired codes intended primarily for research rather than as stand-alone, general-purpose applications. In this work, we describe an open source application, the Exascale Nuclear Reactor Investigative COde (ENRICO), which enables coupled neutronic and thermal-hydraulic simulations between multiple codes that can be chosen at run time (as opposed to a coupling between two specific codes). The application has been designed such that the control flow logic, domain mapping, nonlinear fixed-point iteration, solution transfers, and convergence checks are all agnostic to the underlying physics solvers used. Special emphasis has also been placed on enabling efficient execution on distributed-memory computing environments. The transfer of solution fields between solvers is performed in memory rather than through filesystem input/output. Additionally, solvers can be configured to run on overlapping or disjoint sets of processes.To date, coupling with the OpenMC and Shift MC codes, the Nek5000 CFD code, and a simplified heat diffusion and subchannel solver has been implemented in ENRICO. We present results for coupled simulations of a single light water reactor fuel assembly based on the NuScale reactor using various combinations of the physics solvers. For this problem, the coupled simulations are shown to converge in about four Picard iterations. A comparison of the heat source and temperature distributions computed by ENRICO using OpenMC coupled with Nek5000 and Shift coupled with Nek5000 illustrates remarkable agreement between the codes.