Efficient Lagrangian particle tracking algorithms for distributed-memory architectures. (30th April 2023)

• Record Type: Journal Article
• Authors: Baldan, Giacomo; Bellosta, Tommaso; Guardone, Alberto
• Is Part Of: Computers & fluids. Volume 256(2023)
• Publication Date: 2023-04-30
• Subjects: Particle tracking -- Mesh partitioning -- Parallel computing -- High performance computing -- Distributed memory -- Computational fluid dynamics; Fluid dynamics -- Data processing -- Periodicals; 532.050285
• DOI: 10.1016/j.compfluid.2023.105856
• Languages: English
• ISSNs: 0045-7930

Abstract

Abstract: This paper focuses on the solution of the dispersed phase of Eulerian–Lagrangian one-way coupled particle laden flows. An efficient two-constraint domain partitioning for 2D and 3D unstructured hybrid meshes is proposed and implemented in distributed memory architectures. A preliminary simulation, using a set of representative particles, is performed first to suitably tag the cells with a weight proportional to the probability of being crossed by a particle. In addition, an innovative parallel ray-tracing location algorithm is presented. A global identifier is assigned to each particle resulting in a significant reduction of the overall communication among processes. The proposed approaches are verified against two steady reference cases for ice accretion simulation: a NACA 0012 profile and a NACA 64A008 swept horizontal tail. Furthermore, a cloud droplet impact test case starting from an unsteady flow around a 3D cylinder is performed to evaluate the code performances on unsteady problems. Highlights: Distributed memory algorithms for Lagrangian particle tracking in unstructured grids. Particle location using a parallel ray-tracing algorithm. Multi-constrained mesh partitioning for multi-physics problems. Steady and unsteady in-flight ice accretion simulations.