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An improved ghost-cell immersed boundary method for compressible flow simulations

机译:用于可压缩流模拟的改进的幻影细胞浸入边界方法

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摘要

This study presents an improved ghost-cell immersed boundary approach to represent a solid body in compressible flow simulations. In contrast to the commonly used approaches, in the present work ghost cells are mirrored through the boundary described using a level-set method to farther image points, incorporating a higher-order extra/interpolation scheme for the ghost cell values. A sensor is introduced to deal with image points near the discontinuities in the flow field. Adaptive mesh refinement (AMR) is used to improve the representation of the geometry efficiently in the Cartesian grid system. The improved ghost-cell method is validated against four test cases: (a) double Mach reflections on a ramp, (b) smooth Prandtl-Meyer expansion flows, (c) supersonic flows in a wind tunnel with a forward-facing step, and (d) supersonic flows over a circular cylinder. It is demonstrated that the improved ghost-cell method can reach the accuracy of second order in L1 norm and higher than first order in L∞ norm. Direct comparisons against the cut-cell method demonstrate that the improved ghost-cell method is almost equally accurate with better efficiency for boundary representation in high-fidelity compressible flow simulations. Copyright © 2016 John Wiley & Sons, Ltd.
机译:这项研究提出了一种改进的重影细胞浸入边界方法,以可压缩流模拟来表示固体。与常用方法相反,在当前工作中,通过使用水平集方法描述的边界将鬼像元镜像到更远的图像点,并为鬼像元值合并了更高阶的附加/插值方案。引入传感器来处理流场中不连续附近的图像点。自适应网格细化(AMR)用于在笛卡尔网格系统中有效地改善几何图形的表示。改进的幻影单元法已针对四个测试案例进行了验证:(a)在坡道上进行两次Mach反射;(b)平滑的Prandtl-Meyer膨胀流;(c)带有前向台阶的风洞中的超音速流;以及(d)超音速流过圆柱体。结果表明,改进的重像元法在L1范数下可以达到二阶精度,在L∞范数下可以达到一阶精度。与Cut-cell方法的直接比较表明,改进的Ghost-cell方法几乎同样准确,并且在高保真可压缩流模拟中具有更好的边界表示效率。版权所有©2016 John Wiley&Sons,Ltd.

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