EPJ Web Conf.
Volume 247, 2021PHYSOR2020 – International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future
|Number of page(s)||11|
|Published online||22 February 2021|
TOWARDS CAD-BASED GEOMETRY MODELLING WITH THE RANDOM RAY METHOD
1 Argonne National Laboratory 9700 S. Cass Avenue Lemont, IL, USA
2 United Kingdom Atomic Energy Agency Culham Science Centre, Abingdon OX14 3DB, United Kingdom
Published online: 22 February 2021
The Advanced Random Ray Code (ARRC) is a high performance computing application capable of high-fidelity simulations of full core nuclear reactor models. ARRC leverages a recently developed stochastic method for neutron transport, known as The Random Ray Method (TRRM), which offers a variety of computational and numerical advantages as compared to existing methods. In particular, TRRM has been shown to be capable of efficient simulation of explicit three dimensional geometry representations without assumptions about axial homogeneity. To date, ARRC has utilized Constructive Solid Geometry (CSG) combined with a nested lattice geometry which works well for typical pressurized water reactors, but is not performant for the general case featuring arbitrary geometries.
To facilitate simulation of arbitrarily complex geometries in ARRC efficiently, we propose performing transport directly on Computer-Aided Design (CAD) models of the geometry. In this study, we utilize the Direct-Accelerated Geometry Monte Carlo (DAGMC) toolkit which tracks particles on tessellated CAD geometries using a bounding volume hierarchy to accelerate the process, as a replacement for ARRC’s current lattice-based accelerations. Additionally, we present a method for automatically subdividing the large CAD regions in the DAGMC model into smaller mesh cells required by random ray to achieve high accuracy. We test the new DAGMC geometry implementation in ARRC on several test problems, including a 3D pincells, 3D assemblies, and an axial section of the Advanced Test Reactor. We show that DAGMC allows for simulation of complex geometries in ARRC that would otherwise not be possible using the traditional approach while maintaining solution accuracy.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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