Enhanced adaptive mesh refinement method using advanced vortex identification sensors in wake flow

被引:10
|
作者
Pang, Chao [1 ]
Yang, Hua [1 ]
Gao, Zhenghong [1 ]
Chen, Shusheng [1 ,2 ]
机构
[1] Northwestern Polytech Univ, Sch Aeronaut, Xian 710072, Shaanxi, Peoples R China
[2] AVIC First Aircraft Inst, Xian 710089, Peoples R China
关键词
Adaptive mesh refinement; Vortex identification; Vorticity magnitude; New Omega method; Rortex/Liutex method; Wingtip vortex;
D O I
10.1016/j.ast.2021.106796
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Wake vortices including wingtip vortex appear widely in the flow behind an aircraft. The adaptive mesh refinement method is universal and popular in dealing with the wake vortex flow efficiently using Computational Fluid Dynamics method. A key point in adaptive mesh refinement method is the sensor function which determines the refinement regions. For the wake vortex flow, the vorticity magnitude is a classical sensor, which strongly relies on the users' experiences. To overcome the shortage of the existing method, advanced vortex identification methods, including the new Omega method and the Rortex/Liutex method, are employed as sensor functions in the adaptive mesh refinement routine leading to the enhanced adaptive mesh refinement method proposed in this paper. Subsequently, the proposed method is applied to simulate the wingtip vortex behind a standard half-wing model. The results show that the advanced sensor functions have the superior ability than the vorticity magnitude sensor function to capture both the strong and the weak wingtip vortex. The advanced sensor functions preserve or improve the numerically accuracy with less grid (30%similar to 50% grid reduction) compared to the vorticity magnitude. Additionally, a more reasonable refinement grid to capture the wingtip vortex is generated by the advanced sensor functions. The advanced vortex identification methods can be regarded as the competitive sensor functions in the adaptive mesh refinement method. (C) 2021 Elsevier Masson SAS. All rights reserved.
引用
收藏
页数:11
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