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A review of vortex feature extraction methods for fluid

  

  1. (1. School of Control and Computer Engineering, North China Electric Power University, Baoding Hebei 071003, China; 2. Equipment Project Management Center of Naval Equipment Department, Beijing 100071, China)
  • Online:2020-10-31 Published:2020-11-05
  • About author:First author:SHAO Xu-qiang (1982–), male, associate professor, Ph.D. His main research interests cover computer graphics and virtual reality. E-mail:shaoxuqiang@163.com
  • Supported by:
    Natural Science Foundation of Hebei Province (F2020502014); National Natural Science Foundation of China (61502168); Special Fund for Basic Scientific Research Business Expenses of Central University (2018MS068); Project Support of Beijing Natural Science Foundation (4182018)

Abstract: In recent years, flow visualization has become a research hotspot in computer graphics, and one of its most important research goals is the extraction and visualization of vortex features. Since there is still no general definition of vortex, the evidences to determine whether vortex exists are different in the pertinent literature. In order to make a systematic review of the vortex feature extraction methods of fluid, the paper firstly explained the relevant research directions of vortex extraction, and then reviewed and summarized the development of the vortex feature extraction methods of fluids. The commonly used vortex extraction methods were classified into four categories, including point-based, line-based, geometry-based and machine learning-based methods. For the newly proposed invariance of reference frame, the vortex extraction methods were divided into three types, Galilean invariance, rotation invariance and Lagrange invariance. To compare the advantages and disadvantages of various methods, several classical methods of each type were given in the review, therefore providing a clear outline for future studies. Finally, the difficulties and problems of each method were concluded, and the possible future research focus were introduced.

Key words: vortex extraction method, feature visualization, reference frame invariance, flow feature; vortex core