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Journal of Hydrodynamics

, Volume 31, Issue 2, pp 205–223 | Cite as

Third generation of vortex identification methods: Omega and Liutex/Rortex based systems

  • Chaoqun LiuEmail author
  • Yi-sheng Gao
  • Xiang-rui Dong
  • Yi-qian Wang
  • Jian-ming Liu
  • Yu-ning Zhang
  • Xiao-shu Cai
  • Nan Gui
Feature Article

Abstract

A vortex is intuitively recognized as the rotational/swirling motion of fluids, but a rigorous and universally-accepted definition is still not available. Vorticity tube/filament has been regarded equivalent to a vortex since Helmholtz proposed the concepts of vorticity tube/filament in 1858 and the vorticity-based methods can be categorized as the first generation of vortex identification methods. During the last three decades, a lot of vortex identification methods, including Q, Δ, λ2 and λci criteria, have been proposed to overcome the problems associated with the vorticity-based methods. Most of these criteria are based on the Cauchy-Stokes decomposition and/or eigenvalues of the velocity gradient tensor and can be considered as the second generation of vortex identification methods. Starting from 2014, the Vortex and Turbulence Research Team at the University of Texas at Arlington (the UTA team) focus on the development of a new generation of vortex identification methods. The first fruit of this effort, a new omega (Ω) vortex identification method, which defined a vortex as a connected region where the vorticity overtakes the deformation, was published in 2016. In 2017 and 2018, a Liutex (previously called Rortex) vector was proposed to provide a mathematical definition of the local rigid rotation part of the fluid motion, including both the local rotational axis and the rotational strength. Liutex/Rortex is a new physical quantity with scalar, vector and tensor forms exactly representing the local rigid rotation of fluids. Meanwhile, a decomposition of the vorticity to a rotational part namely Liutex/Rortex and an anti-symmetric shear part (RS decomposition) was introduced in 2018, and a universal decomposition of the velocity gradient tensor to a rotation part (R) and a non-rotation part (NR) was also given in 2018 as a counterpart of the traditional Cauchy-Stokes decomposition. Later in early 2019, a Liutex/Rortex based Omega method called Omega-Liutex, which combines the respective advantages of both Liutex/Rortex and Omega methods, was developed. And a latest objective Omega method, which is still under development, is also briefly introduced. These advances are classified as the third generation of vortex identification methods in the current paper. To elaborate the advantages of the third-generation methods, six core issues for vortex definition and identification have been raised, including: (1) the absolute strength, (2) the relative strength, (3) the rotational axis, (4) the vortex core center location, (5) the vortex core size, (6) the vortex boundary. The new third generation of vortex identification methods can provide reasonable answers to these questions, while other vortex identification methods fail to answer all questions except for the approximation of vortex boundaries. The purpose of the current paper is to summarize the main ideas and methods of the third generation of vortex identification methods rather than to conduct a comprehensive review on the historical development of vortex identification methods.

Key words

Vortex definition vortex identification Omega Liutex/Rortex direct numerical simulation turbulence 

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Notes

Acknowledgements

The authors acknowledge that the UTA team leader Dr. Chaoqun Liu was supported by UTA Mathematics Department since 2000 and US AFOSR and NASA grants for long time since 1990 and the members were supported by US MURI/AFOSR grant and Chinese Scholarship Council (CSC). The authors are grateful to Texas Advanced Computation Center (TACC) for providing computing resources. The DNS code called DNSUTA was released by Dr. Chaoqun Liu in 2009. The authors also appreciate the very beneficial discussions with Profs. Lian-di Zhou and Jie-min Zhan. In addition, there were three conferences on new vortex identification methods with hundreds of participants who gave many constructive suggestions and useful feedbacks on our new methods. The first one was held in Shanghai on December 15–17, 2017, organized by Prof. Xiao-shu Cai, the second one was held in Hangzhou on June 22–27, 2018, organized by Prof. Li-hua Chen and the third one was held in Beijing on December 21–24, 2018, organized by Dr. Yu-ning Zhang.

References

  1. [1]
    Liu C., Yan Y., Lu, P, Physics of turbulence generation and sustenance in a boundary layer [J]. Computers and Fluids, 2014, 102: 353–384.CrossRefGoogle Scholar
  2. [2]
    Wallace J. M, Highlights from 50 years of turbulent boundary layer research [J]. Journal of Turbulence, 2013, 13(53): 1–70.Google Scholar
  3. [3]
    Robinson S. K, Coherent motion in the turbulent boundary layer [J]. Annual Review of Fluid Mechanics, 1991, 23: 601–639.CrossRefGoogle Scholar
  4. [4]
    Hunt J. C. R., Wray A. A., Moin P. Eddies, stream, and convergence zones in turbulent flows [R]. Center for Turbulent Research Report CTR-S88, 1988, 193–208.Google Scholar
  5. [5]
    Chong M. S., Perry A. E. A general classification of threedimensional flow fields [J]. Physics of Fluids A, 1990, 2(5): 765–777.MathSciNetCrossRefGoogle Scholar
  6. [6]
    Jeong J., Hussain F, On the identification of a vortex [J]. Journal of Fluid Mechanics, 1995, 285: 69–94.MathSciNetCrossRefzbMATHGoogle Scholar
  7. [7]
    Zhou J., Adrian R., Balachandar S. et al, Mechanisms for generating coherent packets of hairpin vortices in channel flow [J]. Journal of Fluid Mechanics, 1999, 387: 353–396.MathSciNetCrossRefzbMATHGoogle Scholar
  8. [8]
    Chakraborty P., Balachandar S., Adrian R. J, On the relationships between local vortex identification schemes [J]. Journal of Fluid Mechanics, 2005, 535: 189–214.MathSciNetCrossRefzbMATHGoogle Scholar
  9. [9]
    Liu C., Wang Y., Yang Y. et al, New omega vortex identification method [J]. Science China Physics, Mechanics and Astronomy, 2016, 59(8): 684711.CrossRefGoogle Scholar
  10. [10]
    Dong X. R., Wang Y. Q., Chen X. P. et al, Determination of epsilon for omega vortex identification method [J]. Journal of Hydrodynamics, 2018, 30(4): 541–548.CrossRefGoogle Scholar
  11. [11]
    Zhang Y. N., Liu K. H., Li J. W. et al, Analysis of the vortices in the inner flow of reversible pump turbine with the new omega vortex identification method [J]. Journal of Hydrodynamics, 2018, 30(3): 463–469.CrossRefGoogle Scholar
  12. [12]
    Zhang Y. N., Qiu X., Chen F. P. et al. A selected review of vortex identification methods with applications [J]. Journal of Hydrodynamics, 2018, 30(5): 767–779.CrossRefGoogle Scholar
  13. [13]
    Liu C., Gao Y., Tian S. et al, RortexA new vortex vector definition and vorticity tensor and vector decompositions [J]. Physics of Fluids, 2018, 30: 035103.CrossRefGoogle Scholar
  14. [14]
    Gao Y., Liu C, Rortex and comparison with eigenvaluebased vortex identification criteria [J]. Physics of Fluids, 2018, 30: 085107.CrossRefGoogle Scholar
  15. [15]
    Dong X., Gao Y., Liu C, New normalized Rortex/Vortex identification method [J]. Physics of Fluids, 2019, 31: 011701.CrossRefGoogle Scholar
  16. [16]
    Liu J., Gao Y., Wang Y, et al. Objective omega vortex identification method [EB/OL]. https://doi.org/www.researchgate.net/publication/330370638_Objective_omega_vortex_identification_method.
  17. [17]
    Epps B. Review of vortex identification methods [R]. 2017, AIAA 2017–0989.Google Scholar
  18. [18]
    Zhang Y., Liu K., Xian H. et al. A review of methods for vortex identification in hydroturbines [J]. Renewable and Sustainable Energy Reviews, 2017, 81: 1269–1285.CrossRefGoogle Scholar
  19. [19]
    Helmholtz H. Übe, Integrale der hydrodynamischen Gleichungen, welche den Wirbelbewegungen entsprechen [J]. Journal für die reine und angewandte Mathematik, 1858, 55: 25–55.MathSciNetCrossRefGoogle Scholar
  20. [20]
  21. [21]
    Lamb H. Hydrodynamics [M]. Cambridge, UK: Cambridge University Press,1932.zbMATHGoogle Scholar
  22. [22]
    Saffman P. Vortices dynamics [M]. Cambridge, UK: Cambridge University Press,1992.Google Scholar
  23. [23]
    Nitsche M. “Vortex dynamics,” in Encyclopedia of mathematics and physics [M]. Oxford, UK: Academic Press, 2006.Google Scholar
  24. [24]
    Wu J., Ma H., Zhou M. Vorticity and vortices dynamics [M]. Berlin Heidelberg, Germany: Springer-Verlag, 2006.CrossRefGoogle Scholar
  25. [25]
    Wang Y., Yang Y., Yang G. et al. DNS study on vortex and vorticity in late boundary layer transition [J]. Communications in Computational Physics, 2017, 22(2): 441–459.MathSciNetCrossRefGoogle Scholar
  26. [26]
    Robinson S. K., Kline S. J., Spalart P. R. A review of quasi-coherent structures in a numerically simulated turbulent boundary layer [R]. NASA TM-102191, 1989.Google Scholar
  27. [27]
    Lugt H. J. Vortex flow in nature and technology [M]. New York, USA: Wiley, 1983.Google Scholar
  28. [28]
    Wang Y., Gao Y., Liu C. Physical meaning of vorticity based on the Liutex-shear decomposition and explicit formula for the Liutex vector [J]. arXiv:1812.10672 (also submitted to Physics of Fluids).Google Scholar

Copyright information

© China Ship Scientific Research Center 2019

Authors and Affiliations

  • Chaoqun Liu
    • 1
    Email author
  • Yi-sheng Gao
    • 1
  • Xiang-rui Dong
    • 2
  • Yi-qian Wang
    • 3
  • Jian-ming Liu
    • 1
    • 4
  • Yu-ning Zhang
    • 5
  • Xiao-shu Cai
    • 2
  • Nan Gui
    • 6
  1. 1.Department of MathematicsUniversity of Texas at ArlingtonArlingtonUSA
  2. 2.College of Energy and Power EngineeringUniversity of Shanghai for Science and TechnologyShanghaiChina
  3. 3.School of Aerospace EngineeringTsinghua UniversityBeijingChina
  4. 4.School of Mathematics and StatisticsJiangsu Normal UniversityXuzhouChina
  5. 5.Key Laboratory of Condition Monitoring and Control for Power Plant Equipment (Ministry of Education), School of Energy, Power and Mechanical EngineeringNorth China Electric Power UniversityBeijingChina
  6. 6.Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advanced Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of EducationTsinghua UniversityBeijingChina

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