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arXiv 1503.02198math.NAcs.NA
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一种简单、高效、高阶精度的滑动网格界面方法用于耦合旋转和静止域上的谱差法

A Simple, Efficient, High-order Accurate Sliding-Mesh Interface Approach to the Spectral Difference Method on Coupled Rotating and Stationary Domains

The George Washington University(乔治华盛顿大学)

Bin Zhang, Chunlei Liang

AI总结:

本文提出了一种简单高效的滑动网格界面方法,用于耦合旋转和静止域的谱差法,通过求解二维可压缩纳维-斯托克斯方程验证了方法的高阶精度和高效性,适用于并行计算。

摘要:

本文提出了一种简单、高效且高阶准确的滑动网格界面方法,用于谱差(SD)方法在耦合旋转和静止域上的应用。我们通过求解二维可压缩纳维-斯托克斯方程验证了该方法。该方法是Kopriva为静止域最初设计的直mortar方法的扩展,它在滑动网格界面使用弯曲动态mortars来耦合旋转和静止域。在非匹配的滑动网格界面中,相关变量首先从单元面投影到mortars以计算公共通量,然后将公共通量从mortars投影回单元面以确保守恒。为了验证滑动网格谱差(SSD)方法的空间精度,进行了无粘和有粘流场测试。结果显示,SSD方法保持了SD方法的高阶精度。同时,SSD方法在计算成本方面也表现出很高的效率。这种新的滑动网格界面方法非常适合并行处理与域分解。它可以应用于广泛的问题,如旋翼航空器、风力涡轮机和振荡翼风力发电机等。

英文摘要:

This paper presents a simple, efficient, and high-order accurate sliding-mesh interface approach to the spectral difference (SD) method. We demonstrate the approach by solving the two-dimensional compressible Navier-Stokes equations on quadrilateral grids. This approach is an extension of the straight mortar method originally designed for stationary domains by Kopriva, it employs curved dynamic mortars on sliding-mesh interfaces to couple rotating and stationary domains. On the nonconforming sliding-mesh interfaces, the related variables are first projected from cell faces to mortars to compute common fluxes, and then the common fluxes are projected back from the mortars to the cell faces to ensure conservation. To verify the spatial order of accuracy of the sliding-mesh spectral difference (SSD) method, both inviscid and viscous flow cases are tested. It is shown that the SSD method preserves the high-order accuracy of the SD method. Meanwhile, the SSD method is found to be very efficient in terms of computational cost. This novel sliding-mesh interface method is very suitable for parallel processing with domain decomposition. It can be applied to a wide range of problems, such as the aerodynamics of rotorcraft, wind turbines, and oscillating wing wind power generators, etc.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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