期刊
JOURNAL OF COMPUTATIONAL PHYSICS
卷 478, 期 -, 页码 -出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcp.2023.111985
关键词
GPU; Immersed boundary method; Sharp interface; Field extension; Complex geometry (bluff and thin)
We introduce a GPU-accelerated sharp interface Immersed Boundary (IB) method for versatile geometries on a staggered Cartesian grid. The current IB solver accurately predicts flow around both finite and negligible thickness arbitrary surfaces, with improved accuracy near sharp edges. The proposed method tracks complex geometries on a structured Cartesian grid using a modified signed distance algorithm, and applies boundary conditions by reconstructing flow variables on near boundary nodes in fluid and solid domains. The solver's accuracy is demonstrated for low Reynolds numbers and various stationary and moving rigid geometries with sharp edges relevant to engineering applications. The paper also discusses GPU optimization and achieves significant speedup on NVIDIA V100 GPU for three-dimensional oscillating sphere simulation.
We present a Graphical Processing Unit (GPU) accelerated sharp interface Immersed Boundary (IB) method that can be applied to versatile geometries on a staggered Cartesian grid. The current IB solver predicts the flow around arbitrary surfaces of both finite and negligible thicknesses with improved accuracy near the sharp edges. The proposed methodology first uses a modified signed distance algorithm to track the complex geometries on the structured Cartesian grid accurately. Afterwards, we impose the boundary conditions by reconstructing the flow variables on the near boundary nodes in both fluid and solid domains. We have also shown a reduction of Spurious Force Oscillations (SFOs) near the moving boundaries with reduced divergence error. The accuracy of the present solver is demonstrated at low Reynolds numbers over different stationary and moving rigid geometries associated with sharp edges pertaining to several engineering applications. We have discussed the steps for GPU optimisation of the present solver. Our implementation ensures the concurrent execution of threads for the field extension-based velocity and pressure reconstruction algorithm on a GPU. More than 100x speedup is obtained on NVIDIA V100 GPU for the three-dimensional oscillating sphere simulation. It is observed that the speedup is higher for larger mesh sizes. The computational performance over both the multi-core Control Processing Units (CPUs) and NVIDIA GPUs (V100 and A100) using OpenACC is also provided for the insect flow simulation.(c) 2023 Elsevier Inc. All rights reserved.
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