Diffusive orthogonal load balancing for Euler–Lagrange simulations

Abstract

In the context of unsteady 3D simulations of particle-laden flows, a new double-constraint load balancing strategy for Euler–Lagrange models is proposed. The method relies on an existing Eulerian partitioning and implements a Lagrangian load balancing step, which is orthogonal to the pre-existing Eulerian balancing. This orthogonality property ensures to keep a near-to-ideal Eulerian load balance while strongly improving the distribution of the Lagrangian particles on the processors. The method has been designed to handle large unstructured 3D meshes on complex geometries. Lagrangian performance measurements performed on massively parallel simulations of realistic spray cases show a CPU cost reduction up to 70% compared to the unbalanced case.