IAEA CRP benchmark of ROCOM PTS test case for the use of CFD in reactor design using the CFD-codes ANSYS CFX and TRIOCFD

Over the last 15 years, considerable effort has been expended in assembling the available information on the use of CFD in the nuclear reactor safety field. Typical application areas here are heterogeneous mixing and heat transfer in complex geometries, buoyancy-induced natural and mixed convection, etc., with specific reference to Nuclear Reactor Safety (NRS) accident scenarios such as Pressurized Thermal Shock (PTS), boron dilution, hydrogen build-up in containments, thermal fatigue and thermal striping issues, etc. The development, verification and validation of CFD codes in respect to Nuclear Power Plant (NPP) design necessitates further work on the complex physical modelling processes involved, and on the development of efficient numerical schemes needed to solve the basic equations. Therefore, a set of ROCOM CFD-grade test data were made available to set up an International Atomic Energy Agency (IAEA) benchmark, relating to PTS scenarios. The benchmark deals with the injection of the relatively cold Emergency Core Cooling (ECC) water which can induce buoyancy-driven stratification. Data obtained from the PTS experiment were compared in the study presented here with predictions obtained from the CFD software ANSYS CFX and TrioCFD. In addition a test case without buoyancy forces was selected to show the influence of density differences.

The results of the two test cases and the numerical calculations show that mixing efficiency is strongly influenced by buoyancy effects. At higher mass flow rates without density differences the injected slug propagates in the circumferential direction around the core barrel. Buoyancy forces reduce this azimuthal propagation. The ECC water falls in an almost vertical path and reaches the lower down¬comer sen¬sor below the inlet nozzle. Therefore, density effects play an important role during natural convection with ECC injection in PWRs. Both CFD codes were able to predict the observed flow patterns and mixing phenomena.