Abstract
Greedy algorithm is one of the important point selection methods in the radial basis function based mesh deformation. However, in large-scale mesh, the conventional greedy selection will generate expensive time consumption and result in performance penalties. To accelerate the computational procedure of the point selection, a block iteration with parallelization method is proposed in this paper. By the block iteration method, the computational complexities of three steps in the greedy selection are all reduced from O ( n 3 ) to O ( n 2 ) . In addition, the parallelization of two steps in the greedy selection separates boundary points into sub-cores, efficiently accelerating the procedure. Specifically, three typical models of three-dimensional undulating fish, ONERA M6 wing and three-dimensional Super-cavitating Hydrofoil are taken as the test cases to validate the proposed method and the results show that it improves 17.41 times performance compared to the conventional method.
Highlights
Simulation based on computational fluid dynamics (CFD) is an effective solution for various problems in aerospace engineering and ocean engineering [1], etc
The linear elastic analogy [4,5,6], in which the mesh cell is abstracted into an elastic solid, solves the mesh deformation based on the partial differential equation
We just need to compare whether the results of the block iteration with parallelization method are equal to the original results or not
Summary
Simulation based on computational fluid dynamics (CFD) is an effective solution for various problems in aerospace engineering and ocean engineering [1], etc. One typical instance of connectivity methods is the spring analogy [2]. In large-scale mesh systems, the spring analogy method will produce an expensive cost due to its requirement for the whole mesh connectivity. The linear elastic analogy [4,5,6], in which the mesh cell is abstracted into an elastic solid, solves the mesh deformation based on the partial differential equation. This method has great robustness in large-scale mesh deformation but still produces a huge expensive cost
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