CFD Simulations of Thermal-Hydraulic Flows in a Model Containment: Phase Change Model and Verification of Grid Convergence

Abdennaceur Mansour (), Christian Kaltenbach () and Eckart Laurien ()
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Abdennaceur Mansour: University of Stuttgart, Institute of Nuclear Technology and Energy Systems
Christian Kaltenbach: University of Stuttgart, Institute of Nuclear Technology and Energy Systems
Eckart Laurien: University of Stuttgart, Institute of Nuclear Technology and Energy Systems

A chapter in High Performance Computing in Science and Engineering ´16, 2016, pp 511-528 from Springer

Abstract: Abstract Two-phase flows with water droplets greatly affect the thermal-hydraulic behaviour in the containment of a Pressurized Water Reactor PWR. Such flows occur, inter alia, in French PWR in the form of spray cooling. Spray cooling ensures in case of a leak in the primary circuit the reduction of increased pressure and temperature in the containment due to the released steam. Purpose of the current paper is to present an application-oriented CFD model concerning heat and mass transfer between droplets and gas during the spray cooling process with an Euler-Euler two-fluid approach. In the current model, the resistance to droplet heating is taken into account. A grid convergence study GCI was also performed to quantify the spatial discretization error for a three dimensional natural convection flow simulation using the commercial CFD package Ansys CFX 16.1. Five numerical grids with up to 39. 73 ⋅ 106 elements have been considered to perform this study. Low grid convergence indexes were reported for the fine-mesh comparisons of 7. 11 ⋅ 106–16. 85 ⋅ 106 and 16. 85 ⋅ 106–39. 73 ⋅ 106, resulting in averaged GCI values of less than 1 % for all considered flow variables. The parallel scalability of the simulations was also investigated in this work. Due to the large size and complexity of containment simulations as well as the physically complex flow phenomena in nuclear applications, numerical meshes with large cell numbers may have to be generated in order to minimize the numerical errors. Hence, efficient parallel computing is very important to get realistic computing time. Good scalability of CFX 16.1 is achieved up to 1800 computational cores on a mesh with 83 ⋅ 106 elements and 24 ⋅ 106 nodes.

Date: 2016
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DOI: 10.1007/978-3-319-47066-5_35

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