Pebble bed High Temperature Reactors (HTRs) are characterized by many advantageous design features, such as excellent passive heat removal in accidents, large margins to fuel failure, and online refueling potential. However, a significant challenge in the core modeling of pebble bed reactors is the complex fuel-coolant structure. This paper presents a new porous media simulation code, Pronghorn, that aims to alleviate modeling challenges for pebble bed reactors by providing a fast-running, mediumfidelity core simulator. Pronghorn is intended to accelerate the design and analysis cycle for pebble bed and prismatic HTRs by permitting fast scoping studies and providing boundary conditions for systems-level analysis. Pronghorn is built on the Multiphysics Object-Oriented Simulation Environment (MOOSE) using modern software practices and a thorough testing framework. This paper describes the physical models used in Pronghorn and demonstrates Pronghorn's capability for modeling gas-cooled pebble bed HTRs by presenting simulation results obtained for the German SANA pebble bed decay heat experiments. Within the limitations of the porous media approximation and existing available closure relationships, Pronghorn predicts the SANA experimental pebble temperatures well, expanding the code's validation base. A brief code-To-code comparison shows a level of accuracy comparable to other porous media simulation tools. Pronghorn's advantages over these related tools include: An arbitrary equation of state, unstructured mesh capabilities, compressible flow models, the ability to couple to MOOSE fuels performance and systems-level thermal-hydraulics codes, and modern software design.

Pebble bed High Temperature Reactors (HTRs) are characterized by many advantageous design features, such as excellent passive heat removal in accidents and large margins to fuel failure. However, a significant challenge in thermal-hydraulic core modeling of pebble bed reactors is the double heterogeneity random packing of hundreds of thousands of fuel pebbles and thousands of fuel particles per pebble. A new porous media thermal-hydraulics code, Pronghorn, is under development to provide a fast-running, medium-fidelity core simulator and serve as a bridge between low-resolution system level codes and high-resolution Computational Fluid Dynamics (CFD) codes for multiscale analysis. Pronghorn is based on the Mul-tiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, and permits an arbitrary equation of state, unstructured mesh capabilities, modern software design, and the ability to couple to MOOSE fuels performance and systems-level Thermal-Hydraulic (T/H) codes. To address the wide variety in gas- and liquid-cooled pebble bed reactor designs, Pronghorn includes several different flow models, each most appropriate to a range of compressibilities and operating conditions. This paper reviews benchmarking efforts of a low-advection flow model appropriate for Loss of Forced Circulation (LOFC) simulations and introduces the new fully compressible flow model with preliminary validation by comparison to potential flow theory for low Mach number flow over a cylinder.

A significant challenge in the core modeling of pebble bed reactors (PBRs) is the complex fuel-coolant structure. At the expense of approximating local flow and heat transfer effects, porous media models can provide medium-fidelity predictions of complicated thermal-fluid systems with significantly less computational cost than high-fidelity Computational Fluid Dynamics (CFD) models. This paper presents a new porous media code, Pronghorn – a fast-running core simulator intended to accelerate the design and analysis cycle for PBRs and provide boundary conditions for systems-level analysis. This paper describes the physical models in Pronghorn and demonstrates the capability of a friction-dominated model for predicting gas-cooled PBR decay heat removal by presenting simulation results for all 52 of the steady-state axisymmetric German SANA experiments, which include two different fluids and three different types of pebbles. The pebble temperature in all 52 cases is predicted with a mean error (predicted minus experimental) of +22.6 °C with standard deviation of 54.6 °C. To demonstrate Pronghorn's capability for modeling bed-to-plenum heat and mass transfer, one open-plenum SANA experimental case is also simulated. A code-to-code comparison with Flownex and GAMMA shows that Pronghorn is comparable in accuracy to other porous media simulation tools, with the additional advantages of 1) an arbitrary equation of state; 2) 3-D unstructured mesh capabilities; and 3) multiphysics coupling to other Multiphysics Object-Oriented Simulation Environment (MOOSE) applications. Finally, the effect of several porous media closure selections, in particular the porosity, the near-wall treatment for effective solid thermal conductivity, the interphase drag and heat transfer, and the fluid thermal dispersion, on temperature predictions are quantified.