A two-dimensional shock wave pattern recognition algorithm based on cluster analysis

被引：0
|
作者：
Chang S. [1 ]
Bai X. [1 ]
Liu J. [1 ]
机构：
[1] School of Aeronautics and Astronautics, Dalian University of Technology, Dalian
来源：
Liu, Jun (liujun65@dlut.edu.cn) | 1600年 / AAAS Press of Chinese Society of Aeronautics and Astronautics卷 / 41期
基金：
中国国家自然科学基金;
关键词：
Cluster analysis; Computational fluid dynamics; Shock interaction; Shock wave detection; Shock-capturing; Unsteady flow;
D O I：
10.7527/S1000-6893.2019.23626
中图分类号：
学科分类号：
摘要：
Based on compressible and inviscid flow solutions computed by shock-capturing solvers, a new technique for detecting and recognizing two-dimensional shock wave interaction patterns is proposed. The implementation process of this algorithm is illustrated from three aspects. Firstly, using a traditional shock wave detection approach based on local flow parameters, a series of grid-cells near the shock waves are identified. Next, the shock cells are divided into various clusters by means of a classical K-means clustering algorithm, and the category of each cluster is defined according to its adjacent information. Finally, a criterion is introduced to merge related adjacent clusters and to further determine the locations of shock interaction points. The clusters contained in each shock wave are recorded, and then all the fitting shock lines can be obtained by the Bézier curve algorithm. Numerical experiments show that this newly developed technique can be used in different types of mesh, The new technique produces fitted shock lines with high quality and positional accuracy. Meanwhile, the multiple shock wave interaction patterns are clearly recognized and provide a good visualization method for analyzing the motion and evolution of shock waves in complex, unsteady flow. © 2020, Press of Chinese Journal of Aeronautics. All right reserved.
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共 26 条
  • [1] BUNING P, STEGER J., Graphics and flow visualization in computational fluid dynamics, 7th Computational Physics Conference, (1985)
  • [2] DARMOFAL D L., Hierarchal visualization of three-dimensional vortical flow calculations, pp. 42-43, (1991)
  • [3] LIOU S P, SINGH A, MEHLIG S, Et al., An image analysis based approach to shock identification in CFD, 33rd Aerospace Sciences Meeting and Exhibit, (1995)
  • [4] LOVELY D, HAIMES R., Shock detection from computational fluid dynamics results, 14th Computational Fluid Dynamics Conference, (1999)
  • [5] PAGENDARM H G, SEITZ B., An algorithm for detection and visualization of discontinuities in scientific data fields applied to flow data with shock waves, Scientific Visualization: Advanced Software Techniques, pp. 161-177, (1993)
  • [6] MA K L, VAN ROSENDALE J, VERMEER W., 3D shock wave visualization on unstructured grids, Proceedings of 1996 Symposium on Volume Visualization, pp. 87-94, (1996)
  • [7] VAN ROSENDALE J., Floating shock fitting via Lagrangian adaptive meshes, pp. 89-94, (1994)
  • [8] KANAMORI M, SUZUKI K., Shock wave detection in two-dimensional flow based on the theory of characteristics from CFD data, Journal of Computational Physics, 230, 8, pp. 3085-3092, (2011)
  • [9] KANAMORI M, SUZUKI K., Three-dimensional shock wave detection based on the theory of characteristics, AIAA Journal, 51, 9, pp. 2126-2132, (2013)
  • [10] AKHLAGHI H, DALIRI A, SOLTANI M R., Shock-wave-detection technique for high-speed rarefied-gas flows, AIAA Journal, 55, 11, pp. 3747-3756, (2017)
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