Abstract
Six core issues for vortex definition and identification concern with (1) the absolute strength, (2) the relative strength, (3) the rotational axis, (4) the vortex core center, (5) the vortex core size, and (6) the vortex boundary (Liu C. 2019). However, most of the currently popular vortex identification methods, including the Q criterion, the λ2 criterion and the λci criterion et al, are Eulerian local region-type vortex identification criteria and can only approximately identify the vortex boundary by somewhat arbitrary threshold. On the other hand, the existing Eulerian local line-type methods, which seek to extract line-type features such as vortex core line, are not entirely satisfactory since most of these methods are based on vorticity or pressure minimum that will fail in many cases. The key issue is the lack of a reasonable mathematical definition for vortex core center. To address this issue, a Liutex (previously named Rortex) based definition of vortex core center is proposed in this paper. The vortex core center, also called vortex rotation axis line here, is defined as a line where the Liutex magnitude gradient vector is aligned with the Liutex vector, which mathematically implies that the cross product of the Liutex magnitude gradient vector and the Liutex vector on the line is equal to zero. Based on this definition, a novel three-step method for extracting vortex rotation axis lines is presented. Two test cases, namely the Burgers vortex and hairpin vortices, are examined to justify the proposed method. The results demonstrate that the proposed method can successfully identify vortex rotation axis lines without any user-specified threshold, so that the proposed method is very straightforward, robust and efficient.
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References
Lugt H. J. Vortex flow in nature and technology [M]. New York, USA: Wiley, 1983.
Hussain A. K. M. F. Coherent structures and turbulence [J]. Journal of Fluid Mechanics, 1986, 173: 303–356.
Robinson S. K. Coherent motion in the turbulent boundary layer [J]. Annual Review of Fluid Mechanics, 1991, 23: 601–639.
Sirovich L. Turbulence and the dynamics of coherent structures. Part I: Coherent structures [J]. Quarterly of Applied Mathematics, 1987, 45(3): 561–571.
Liu C., Yan Y., Lu P. Physics of turbulence generation and sustenance in a boundary layer [J]. Computers and Fluids, 2014, 102: 353–384.
Bake S., Meyer D., Rist U. Turbulence mechanism in Klebanoff transition: A quantitative comparison of experiment and direct numerical simulation [J]. Journal of Fluid Mechanics, 2002, 459: 217–243.
Wu X., Moin P. Direct numerical simulation of turbulence in a nominally zeropressure gradient flat-plate boundary layer [J]. Journal of Fluid Mechanics, 2009, 630: 5–41.
Theodorsen T. Mechanism of turbulence [C]. Proceedings of the Second Midwestern Conference on Fluid Mechanics, Columbus, OH, USA: Ohio State University, 1952.
Adrian R. J. Hairpin vortex organization in wall turbulence [J]. Physics of Fluids, 2007, 19(4): 041301.
Eitel-Amorl G., Örlü R., Schlatter P. et al. Hairpin vortices in turbulent boundary layers [J]. Physics of Fluids, 2015, 27(2): 025108.
Brooke J. W., Hanratty T. J. Origin of turbulence-producing eddies in a channel flow [J]. Physics of Fluids A: Fluid Dynamics, 1993, 5(4): 1011–1022.
Jeong J., Hussain F., Schoppa W. et al. Coherent structures near the wall in a turbulent channel flow [J]. Journal of Fluid Mechanics, 1997, 332: 185–214.
Liu C., Gao Y., Dong X. et al. Third generation of vortex identification methods: Omega and Liutex/Rortex based systems [J]. Journal of Hydrodynamics, 2019, 31(2): 205–223.
Liu C., Cai X. New theory on turbulence generation and structure-DNS and experiment [J]. Science China Physics, Mechanics and Astronomy, 2017, 60(8): 084731.
Lugt H. J. “The dilemma of dening a vortex,” in recent developments in theoretical and experimental fluid mechanics [M]. Berlin Heidelberg, Germany: Springer-Verlag, 1979.
Lamb H. Hydrodynamics [M]. Cambridge, UK: Cambridge University Press, 1932.
Saffman P. Vortices dynamics [M]. Cambridge, UK: Cambridge University Press, 1992.
Robinson S. K. “A review of vortex structures and associated coherent motions in turbulent boundary layers,” in structure of turbulence and drag reduction [M]. Berlin Heidelberg, Germany: Springer-Verlag, 1990.
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.
Gao Q., Ortiz-Dueñas C., Longmire E. K. Analysis of vortex populations in turbulent wall-bounded flows [J]. Journal of Fluid Mechanics, 2011, 678: 87–123.
Pirozzoli S., Bernardini M., Grasso F. Characterization of coherent vortical structures in a supersonic turbulent boundary layer [J]. Journal of Fluid Mechanics, 2008, 613: 205–231.
Epps B. Review of vortex identification methods [R]. 2017, AIAA 2017-0989.
Gao Y., Liu C. Rortex and comparison with eigenvalue-based vortex identification criteria [J]. Physics of Fluids, 2018, 30(8): 085107.
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.
Chong M. S., Perry A. E. A general classification of three-dimensional flow fields [J]. Physics of Fluids A, 1990, 2(5): 765–777.
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.
Jeong J., Hussain F. On the identification of a vortex [J]. Journal of Fluid Mechanics, 1995, 285: 69–94.
Chakraborty P., Balachandar S., Adrian R. J. On the relationships between local vortex identification schemes [J]. Journal of Fluid Mechanics, 2005, 535: 189–214.
Liu C. Numerical and theoretical study on ‘vortex breakdown’ [J]. International Journal of Computer Mathema-tics, 2011, 88(17): 3702–3708.
Liu C., Wang Y., Yang Y. et al. New omega vortex identification method [J]. Science China Physics, Mechanics and Astronomy, 2016, 59(8): 684711.
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.
Maciel Y., Robitaille M., Rahgozar S. A method for characterizing cross-sections of vortices in turbulent flows [J]. International Journal of Heat and Fluid Flow, 2012, 37: 177–188.
Chen H., Adrian R. J., Zhong Q. et al. Analytic solutions for three dimensional swirling strength in compressible and incompressible flows [J]. Physics of Fluids, 2014, 26(8): 081701.
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): 035103.
Gao Y., Liu C. Rortex based velocity gradient tensor decomposition [J]. Physics of Fluids, 2019, 31(1): 011704.
Dong X., Gao Y., Liu C. New normalized Rortex/vortex identification method [J]. Physics of Fluids, 2019, 31(1): 011701.
Strawn R. C., Kenwright D. N, Ahmad Jasim. Computer visualization of vortex wake systems [J]. AIAA Journal, 1999, 37(4): 511–512.
Banks D. C., Singer B. A. Vortex tubes in turbulent flows: Identication, representation, reconstruction [C]. Proceedings of the Conference on Visualization’ 94, Washinton DC, USA, 1994.
Levy Y., Degani D., Seginer A. Graphical visualization of vortical flows by means of helicity [J]. AIAA Journal, 1990, 28(8): 1347–1352.
Zhang S., Choudhury D. Eigen helicity density: A new vortex identification scheme and its application in accelerated inhomogeneousows [J]. Physics of Fluids, 2006, 18(5): 058104.
Mura H., Kida S. Identification of tubular vortices in turbulence [J]. Journal of the Physical Society of Japan, 1997, 66(5): 1331–1334.
Kida S., Mura H. Identification and analysis of vertical structures [J]. European Journal of Mechanics-B/Fluids, 1998, 17(4): 471–488.
Linnick M., Rist U. Vortex identification and extraction in a boundary-layer flow [C]. Vision, Modelling, and Visualization 2005, Erlangen, Germany, 2005.
Sujudi D., Haimes R. Identification of swirling flow in 3D vector fields [R]. 1995, AIAA Paper 95–1715.
Roth M. Automatic extraction of vortex core lines and other line-type features for scientific visualization [D]. Doctoral Thesis, Zürich, Switzerland: ETH Zürich, 2000.
Zhang Y., Liu K., Xian H. et al. A review of methods for vortex identification in hydroturbines [J]. Renewable and Sustainable Energy Reviews, 2018, 81: 1269–1285.
Wang Y. Q., Gao Y. S., Liu J. et al. Explicit formula for the Liutex vector and physical meaning of vorticity based on the Liutex-Shear decomposition [J]. Journal of Hydrodynamics, 2019, https://doi.org/10.1007/s42241-019-0032-2.
Acknowledgements
This work was supported by the Department of Mathematics at University of Texas at Arlington and AFOSR (Grant No. MURI FA9559-16-1-0364), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 18KJA110001) and the Visiting Scholar Scholarship of the China Scholarship Council (Grant No. 201808320079). The authors are grateful to Texas Advanced Computational Center (TACC) for providing computation hours. This work is accomplished by using code DNSUTA developed by Dr. Chaoqun Liu at the University of Texas at Arlington.
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Project supported by the National Natural Science Foundation of China (Grant No. 91530325).
Biography: Yi-sheng Gao (1984-), Male, Ph. D.
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Gao, Ys., Liu, Jm., Yu, Yf. et al. A Liutex based definition and identification of vortex core center lines. J Hydrodyn 31, 445–454 (2019). https://doi.org/10.1007/s42241-019-0048-7
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DOI: https://doi.org/10.1007/s42241-019-0048-7