Cardinal: A Lower-Length-Scale Multiphysics Simulator for Pebble-Bed Reactors

Abstract

This paper demonstrates a multiphysics solver for pebble-bed reactors, in particular, for Berkeley's pebble-bed -fluoride-salt-cooled high-temperature reactor (PB-FHR) (Mark I design). The FHR is a class of advanced nuclear reactors that combines the robust coated particle fuel form from high-temperature gas-cooled reactors, the direct reactor auxiliary cooling system passive decay removal of liquid-metal fast reactors, and the transparent, high-volumetric heat capacitance liquid-fluoride salt working fluids (e.g., FLiBe) from molten salt reactors. This fuel and coolant combination enables FHRs to operate in a high-temperature, low-pressure design space that has beneficial safety and economic implications. The PB-FHR relies on a pebblebed approach, and pebble-bed reactors are, in a sense, the poster child for multiscale analysis.Relying heavily on the MultiApp capability of the Multiphysics Object-Oriented Simulation Environment (MOOSE), we have developed Cardinal, a new platform for lower-length-scale simulation of pebble-bed cores. The lower-length-scale simulator comprises three physics: neutronics (OpenMC), thermal fluids (Nek5000/ NekRS), and fuel performance (BISON). Cardinal tightly couples all three physics and leverages advances in MOOSE, such as the MultiApp system and the concept of MOOSE-wrapped applications. Moreover, Cardinal can utilize graphics processing units for accelerating solutions. In this paper, we discuss the development of Cardinal and the verification and validation and demonstration simulations.

All-Hex Meshing Strategies For Densely Packed Spheres

“…The cardinality of {∆ij} is O(N ), so it makes sense to scale the x-axis by 1/N so that graphs for different data sets can be plotted in the same figure. 2 With this scaling, we see that the ten data sets in Fig. 4 exhibit plateaus on the interval k/N ≈ [0, 5].…”

“…Spherical beds are common in many industrial processes in chemical engineering [1]. The flow of coolant through packed beds is of particular interest in the design of pebble-bed reactors, and researchers have expressed significant interest in detailed simulations tha can provide insight into heat transfer in new pebble-bed designs [2]. For simulations that resolve turbulent eddies in the flow, high-order discretizations having minimal numerical dissipation and dispersion provide high accuracy with a relatively small number of gridpoints, n. The spectral element method (SEM) [3], which uses local tensor-product bases on curved hexahedral elements, is efficient, with memory costs scaling as O(n), independent of local approximation order N (for n fixed), and computational cost that is only O(nN ).…”

Comparison of Pebble Bed Velocity Profiles Between High-Fidelity and Intermediate-Fidelity Codes

“…Two cases were created and simulated with NekRS, one with 1,568 pebbles and one with 45,000 pebbles. The meshes for these cases were created using a novel Voronoi cell approach as part of the Cardinal multi-physics project [17]. This is a tailored approach to the generation of all-hexahedral meshes in the pebble void regions that is based on a tessellation of the Voronoi cells defined by the pebble centers.…”

Initial use of Nek5000/Cardinal to improve closure models in Pronghorn

“…The goal of the present work is to develop tools that should couple closure models obtained from lower-length-scale simulations to engineering-length-scale ones. This is an existing demand in the development of Cardinal [1], a new platform for lower-length-scale simulation of pebble-bed cores. In the context of the present work, we employ the lower scale simulator NekRS to derive heat transfer formulations that might be supplied to engineering scale codes such as Pronghorn [2] and Mammoth [3].…”