Numerical simulation of the molten pool stratification using moving particle simulation method. (November 2021)

• Record Type: Journal Article
• Authors: Fu, Shengwei; Wang, Wei; Wang, Xi
• Is Part Of: Annals of nuclear energy. Volume 162(2021)
• Publication Date: 2021-11
• Subjects: Moving Particle Simulation -- CFD -- Severe accident -- Molten pool; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2021.108464
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: A polygon wall model is proposed for the MPS method, and it is validated by a sloshing benchmark case. The two phase simulation model of the particle method is validated by several stratification cases. A large scale 3D simulation is carried out for a scenario of molten materials injected into a RPV. Abstract: In the design of third generation nuclear power plants, severe accident mitigation is an important feature. In the study of severe accident phenomena, the immigration of the molten core materials involves physical procedures like mixing of multiple materials, melting and solidification, and complex surface flows. With the conventional lump parameter method, the local 3 dimensional behavior of the molten corium can not be simulated. With the Euler based Computational Fluid Dynamics (CFD) method, it is difficult to simulate the mixing and stratification of multiple molten materials, also the free surface flow is hard to capture in the simulation. In the present study, the Lagrangian based Moving Particle Simulation (MPS) method is applied to investigate the stratification of molten pools. The test results of two immiscible fluids are used to validate the MPS method. A polygon wall model is applied in these simulations, which reduces the number of particles used in the simulation and enables to simulate industry relevant cases in 3 dimensions. A simulation of injection of three different molten materials into a stratified molten pool is carried out to analyze a hypothetical severe accident scenario.