Skip to main content
SpringerLink
Log in

Liutex-based vortex control with implications for cavitation suppression

  • Article
  • Published:
Journal of Hydrodynamics Aims and scope Submit manuscript

Abstract

Viewed as sinews and muscles of fluid motion, coherent vortical structures with their interactions are key to understanding the flow dynamics. Based upon this observation, we explore the possibility of efficient flow control by directly manipulating vortices numerically inside the flow field based on the vortex definition and identification system of Liutex. The objective is twofold: (1) to study the vortex dynamics, for example, by observing the response of the flow to strengthening or weakening of certain vortices, and (2) to obtain efficient vortex-based control strategies which might lead us to practical applications. In the present numerical study, the manipulating of vortices is achieved by introducing additional source (force) terms to the Navier-Stokes equations, which hereafter will be collectively called Liutex force field model. Methodologies including controlling the rotation strength and centripetal force of particular vortices are detailed in a flow past a cylinder with different control purposes at Reynolds number of 200. Further examples are provided with a cavitating flow around two-dimensional Clark-Y hydrofoil, with particular interests on cavitation suppression. It is illustrated particular vortex with cavitation encircled could be effectively suppressed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Luo X., Ji B., Tsujimoto Y. A review of cavitation in hydraulic machinery [J]. Journal of Hydrodynamics, 2016, 28(3): 335–358.

    Article  Google Scholar 

  2. Huang B., Qiu S. C., Li X. B. et al. A review of transient flow structure and unsteady mechanism of cavitating flow [J]. Journal of Hydrodynamics, 2019, 31(3): 429–444.

    Article  Google Scholar 

  3. Nakamura K., Kurosawa S. Design optimization of a high specific speed Francis turbine using multi-objective genetic algorithm [J]. International Journal of Fluid Machinery and Systems, 2009, 2(2): 102–109.

    Article  Google Scholar 

  4. Enomoto Y., Kurosawa S., Kawajiri H. Design optimization of a high specific speed Francis turbine runner [J]. IOP Conference Series: Earth and Environmental Science, 2012, 15(3): 032010.

    Article  Google Scholar 

  5. Che B., Chu N., Schmidt S. J. et al. Control effect of micro vortex generators on leading edge of attached cavitation [J]. Physics of Fluids, 2019, 31(4): 044102.

    Article  Google Scholar 

  6. Che B., Chu N., Cao L. et al. Control effect of micro vortex generators on attached cavitation instability [J]. Physics of Fluids, 2019, 31(6): 064102.

    Article  Google Scholar 

  7. Küchemann D. Report on the I.U.T.A.M. symposium on concentrated vortex motions in fluids [J]. Journal of Fluid Mechanics, 1965, 21(1): 1–20.

    Article  Google Scholar 

  8. Liu C., Yan Y., Lu P. Physics of turbulence generation and sustenance in a boundary layer [J]. Computers and Fluids, 2014, 102: 353–384.

    Article  Google Scholar 

  9. Liu C., Gao Y. S., Dong X. R. et al. Third generation of vortex identification methods: Omega and Liutex/Rortex based systems [J]. Journal of Hydrodynamics, 2019, 31(2): 205–223.

    Article  Google Scholar 

  10. Robinson S. K. Coherent motion in the turbulent boundary layer [J]. Annual Review of Fluid Mechanics, 1991, 23: 601–639.

    Article  Google Scholar 

  11. 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.

    Article  MathSciNet  Google Scholar 

  12. Hunt J., Wray A., Moin P. Eddies, streams, and convergence zones in turbulent flows [R]. Proceedings of the Summer Program. Center for Turbulence Research Report CTR-S88, 1988, 193–208.

  13. Jeong J., Hussain F. On the identification of a vortex [J]. Journal of Fluid Mechanics, 1995, 285: 69–94.

    Article  MathSciNet  Google Scholar 

  14. Chong M. S., Perry A. E., Cantwell B. J. A general classification of three-dimensional flow fields [J]. Physics of Fluids A, 1990, 2(5): 765–777.

    Article  MathSciNet  Google Scholar 

  15. 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: 252–296.

    Article  MathSciNet  Google Scholar 

  16. Liu C., Gao Y., Tian S. et al. Rortex-A new vortex vector definition and vorticity tensor and vector decompositions [J]. Physics of Fluids, 2018, 30(3): 034103.

    Article  Google Scholar 

  17. Liu J., Gao Y., Liu C. An objective version of the Rortex vector for vortex identification [J]. Physics of Fluids, 2019, 31(6): 065112.

    Article  Google Scholar 

  18. Dong X., Gao Y., Liu C. New normalized Rortex/vortex identification method [J]. Physics of Fluids, 2019, 31(1): 011701.

    Article  Google Scholar 

  19. Liu J., Liu C. Modified normalized Rortex/vortex identification method [J]. Physics of Fluids, 2019, 31(6): 061704.

    Article  Google Scholar 

  20. Gao Y., Liu J., Yu Y. et al. A Liutex based definition of vortex rotation axis line [J]. Journal of Hydrodynamics, 2019, 31(3): 445–454.

    Article  Google Scholar 

  21. Xu H., Cai X. S., Liu C. Liutex (vortex) core definition and automatic identification for turbulence vortex structures [J]. Journal of Hydrodynamics, 2019, 31(5): 857–863.

    Article  Google Scholar 

  22. Wang Y. Q., Gao Y. S., Xu H. et al. Liutex theoretical system and six core elements of vortex identification [J]. Journal of Hydrodynamics, 2020, 32(2): 197–211.

    Article  Google Scholar 

  23. Liu C., Gao Y. Liutex-based and other mathematical, computational and experimental methods for turbulence structure [M]. Sharjah, United Arab Emirates: Benthom Science Publishers, 2020.

  24. Liu C., Xu H., Cai X. et al. Liutex and its applications in turbulence research [M]. Cambridge, Massachusetts, USA: Academic Press, 2020.

    Google Scholar 

  25. Vainchtein D., Meziç I. Vortex-based control algorithms (Koumoutsakos P., Meziç I. Controlof fluid flow. Lecture notes in control and information sciences) [M]. Berlin, Germany: Springer, 2006.

    Google Scholar 

  26. Protas B. Vortex dynamics models in flow control problems [J]. Nonlinearity, 2008, 21(9): 203–250.

    Article  MathSciNet  Google Scholar 

  27. Yu H. D., Wang Y. Q. Liutex-based vortex dynamics: A preliminary study [J]. Journal of Hydrodynamics, 2020, 32(6): 1217–1220.

    Article  Google Scholar 

  28. Gao Y., Liu C. Rortex and comparison with eigenvalue-based vortex identification criteria [J]. Physics of Fluids, 2018, 30(8): 085107.

    Article  Google Scholar 

  29. Wang Y. Q., Gao Y. S., Liu J. M. et al. Explicit formula for the Liutex vector and physical meaning of vorticity based on the Liutex-Shear decomposition [J]. Journal of Hydrodynamics, 2019, 31(3): 464–474.

    Article  Google Scholar 

  30. Braza M., Chassaing P., Minh H. Numerical study and physical analysis of the pressure and velocity fields in the near wake of a circular cylinder [J]. Journal of Fluid Mechanics, 1986, 165: 79–130.

    Article  MathSciNet  Google Scholar 

  31. Huang B., Wang G. Y. Partially averaged Navier-Stokes method for time-dependent turbulent cavitating flows [J]. Journal of Hydrodynamics, 2011, 23(1): 26–33.

    Article  Google Scholar 

Download references

Acknowledgment

Communications with Profs. Liandi Zhou, Chaoqun Liu, and Zheng Ma are highly appreciated.

Author information

Authors and Affiliations

  1. School of Mathematical Science, Soochow University, Suzhou, 215006, China

    Yi-qian Wang

  2. School of Aerospace Engineering, Tsinghua University, Beijing, 100084, China

    Hai-dong Yu

  3. Computational Marine Hydrodynamics Lab (CMHL), State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Wei-wen Zhao & De-cheng Wan

Authors
  1. Yi-qian Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hai-dong Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wei-wen Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. De-cheng Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to De-cheng Wan.

Additional information

Project supported by the National Nature Science Foundation of China (Grant Nos. 11702159, 51879159 and 51909160).

Biography

Yi-qian Wang (1987-), Male, Ph. D., Associate Professor, E-mail: yiqianw@sina.com

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, Yq., Yu, Hd., Zhao, Ww. et al. Liutex-based vortex control with implications for cavitation suppression. J Hydrodyn 33, 74–85 (2021). https://doi.org/10.1007/s42241-021-0013-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42241-021-0013-0

Key words

Search

Navigation