An Improved Level-Set-Based Immersed Boundary Reconstruction Method for Computing Bio-Inspired Underwater Propulsion

Yu Pan, Haibo Dong, Wei Zhang
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Abstract

The immersed boundary method (IBM) has been widely employed to study bio-inspired underwater propulsion which often involves the high Reynolds number, complex body morphologies and large computational domain. Due to these problems, the immersed boundary (IB) reconstruction can be very costly in a simulation. Based on our previous work, an improved level-set-based immersed boundary method (LS-IBM) has been developed in this paper by introducing the narrow-band technique. Comparing with the previous LS-IBM, the narrowband level-set-based immersed boundary method (NBLS-IBM) is only required to propagate the level set values from the points near the boundaries to all the points in the narrow band. This improvement reduces the computational cost from O((LD/Δx)3) to O(k(LD/Δx)2). By simulating a steady-swimming Jackfish-like body, the consistency and stability of the new reconstruction method in the flow solver have been verified. Applications to a dolphin-like body swimming and a shark-like body swimming are used to demonstrate the efficiency and accuracy of the NBLS-IBM. The time for reconstructions shows that the reconstruction efficiency can increase up to 64.6% by using the NBLS-IBM while keeping the accuracy and robustness of the original LS-IBM. The vortex wake of the shark-like body in steady swimming shows the robustness, fastness and compatibility of the NBLS-IBM to our current flow solver.
一种改进的基于水平集的水下推进边界重建方法
浸入边界法(IBM)被广泛应用于高雷诺数、复杂体形和大计算域的仿生水下推进研究。由于这些问题,在模拟中,浸入边界(IB)重建是非常昂贵的。本文在前人工作的基础上,引入窄带技术,提出了一种改进的基于水平集的浸入边界法(LS-IBM)。与之前的LS-IBM相比,基于窄带水平集的浸入边界方法(NBLS-IBM)只需要将水平集值从边界附近的点传播到窄带内的所有点。这种改进将计算成本从O((LD/Δx)3)降低到O(k(LD/Δx)2)。通过模拟一个稳定游动的类jackfish体,验证了该方法在流动求解器中的一致性和稳定性。通过对海豚类身体游泳和鲨鱼类身体游泳的应用,验证了NBLS-IBM的效率和准确性。重建时间表明,在保持原LS-IBM的精度和鲁棒性的前提下,NBLS-IBM的重建效率可提高64.6%。鲨鱼状体在稳定游动时的涡尾迹表明了NBLS-IBM对当前流求解器的鲁棒性、快速性和兼容性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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