top-ii-vol: Massively Parallel Scalable Meshing for Seismic Risk Assessment of Nuclear Sites

Abstract

High performance computing is widely used for conducting high-resolution geophysics Finite Element Method (FEM) simulations. These simulations are crucial for risk assessment at nuclear sites and help gain deeper insights into underlying physics. However, generating FEM-compatible meshes from point-cloud data – which often serves as input for mesh generation from geomodelling tools – poses significant challenges due to the lack of associated CAD data and extremely large-scale nature. This article introduces a workflow for automatically converting Digital Elevation Model (DEM) point-cloud data into three-dimensional unstructured volumetric meshes. Leveraging domaindecomposition method via the parallel MPI I/O programming, our meshing algorithm efficiently constructs meshes, accommodating an arbitrary number of CPUs and enabling either single or distributed mesh generation. Demonstrating parallel efficiency and scalability, we produced a 68 billion element tetrahedral mesh from real DEM point-cloud data of the Cadarache region in France in approximately 1 second using over 24000 processing units. Meshes produced by this technique are utilized for seismic hazard FEM simulations, one of which is presented in this study. Scalability tests on massively parallel computers show high scalability, with quasi-linear strong scaling characteristics up to 24000 processing units.