An Improved Parallel Overset Grid Method for Fluid Simulation with Moving Boundary
Ran Zhao, Chao Li, Xiao‐Wei Guo, Yi Liu, Sifan Long, Sen Zhang, Yanlong Qiu, Canqun Yang · 2023
The Overset Grid method is a promising computational approach for tackling the challenging moving boundary problems in Computational Fluid Dynamics (CFD) simulations. The computational efficiency and accuracy of the method are critically dependent on the effectiveness of the Overset Grid Assembly (OGA) process. However, the OGA process is plagued by unavoidable issues of load imbalance and communication overheads, which adversely impact the parallel efficiency of the method, particularly when dealing with sub-grids in motion. This paper proposes an improved parallel assembly approach as an effective alternative to address these challenges. Specifically, we introduce a Balanced Merging After Decomposition (BMAD) approach, which ensures that each processor possesses a uniform number of cells from each sub-grid after partitioning and a consistent donor search time. In addition, we deploy a fine-grained list to reduce the data transfer domain, thereby minimizing communication redundancy and cost. We validate the efficiency of our approach in the case of a moving Autonomous Underwater Vehicle (AUV). Experimental results in 3 × 106 grid cells indicate that the proposed approach reduces the parallel computational cost of the OGA process by an average of 21.9% and the speedup has increased by 23.9% with 128 processors. Additionally, it demonstrated equally effective and stable performance in tests using 6 × 106 grid cells, especially achieving the highest speedup of 55.0 with 256 processors.