Evaluation of compressible flow in spherical fueled reactors using the porous media model

Abstract

In this study, using porous media approach, the compressible flow within the core of a Pebble Bed Modular Reactor (PBMR) is simulated. This reactor has been composed of coated fuel particles with compressible gas as a coolant and graphite as a moderator and reflector. Containing about 450,000 fuel complexes, the reactor core is considered a porous medium subject to high temperature and high pressure helium flow. The porosity and permeability parameters are calculated and utilized. The coolant compressibility has been introduced as an effective parameter in the thermal–hydraulic analysis. Accordingly, using the ANSYS CFX code, which is capable of simulating compressible flow in porous media, the reactor core is simulated and thermal–hydraulic parameters of the core are obtained through Computational Fluid Dynamic (CFD) approach. The heat flux in the core is first obtained in axial and radial coordinates by MCNP code and is then used in CFD simulation as a semi sine and an algebraic function. The major characteristics of the flow field have been calculated whereby the thermal–hydraulic parameters such as temperature and pressure profiles have been obtained and compared with other data. Comparing the results obtained with other codes and software, the outcomes show that the inclusion of compressibility is reasonable and will lead to a slight difference between the measured and actual temperature, pressure and velocity. In another stage, pressure drop, flow vortices and helium flow lines are explored for two fuel complexes. The empirical formula of pressure drop presented by Kugeler and Schulten is modified and gas density is considered as a function of the core length. Fuel complexes in the reactor core are randomly arranged. However, because Body Center Cubic (BCC) is the closest arrangement to the random distribution, flow parameters are obtained using the BCC arrangement and they are found to deviate very slightly when compared with predictions of other codes.