ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)


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Govorukhin V. N. Identification and dynamics prediction of a plane vortex structure based on a mathematical model of a point vortices system. Izvestiya VUZ. Applied Nonlinear Dynamics, 2023, vol. 31, iss. 6, pp. 710-726. DOI: 10.18500/0869-6632-003071, EDN: PHVMFU

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Language: 
Russian
Article type: 
Article
UDC: 
532.54:51-72
EDN: 

Identification and dynamics prediction of a plane vortex structure based on a mathematical model of a point vortices system

Autors: 
Govorukhin V. N., Southern Federal University
Abstract: 

The aim of the article is developing and analyse an algorithmic method for solution finding of one inverse problem of 2d vortex fluid dynamics. It is identification and prediction of the flow structure evolution of the based on the data on fluid velocity vectors in a set of reference points. Theoretical analysis of convergence and adequacy of the method is difficult due to the ill-posedness typical of inverse problems, these issues studied experimentally.

Methods. The proposed method uses a mathematical model of a point vortex dynamics system for identification and prediction flow structures. The parameters of the model system are found by minimising the functional that evaluates the closeness of the original and model vectors fields at the reference points. The prediction of the vortex structure dynamics is based on the solution of the Cauchy problem for a system of ordinary differential equations with the parameters found in the first stage.

Results. As a result of the calculations, we found it out: the algorithm converges to the desired minimum from a wide range of initial approximations; the algorithm converges in all cases when the identified structure consists of sufficiently distant vortices; the forecast of the development of the current gives good results with a steady flow; if the above conditions are violated, the part of successful calculations decreases, false identification and an erroneous forecast may occur; with the convergence of the method, the coordinates and circulation of the eddies of the model system are close to the characteristics of the eddies of the test configurations; the structures of the streamlines of the flows are topologically equivalent; convergence depends more on location than on the number of vectors used for identification.

Conclusion. An algorithm for solving the problem of identifying and the evolution forecast of a 2d vortex flow structure is proposed when the fluid velocity vectors in a finite set of reference points are known. The method showed its high efficiency when using from 40 to 200 reference points. The results of the study make it possible to recommend the proposed algorithm for identifying flat vortex structures, which consist of vortices separated from each other.

Acknowledgments: 
This work was supported by the grants the Russian Science Foundation, № 23-21-00371
Reference: 
  1. Aleksanina MG, Eremenko AS, Zagumennov AA, Kachur VA. Eddies in the ocean and atmosphere: Identification by satellite imagery. Russian Meteorology and Hydrology. 2016;41(9):620–628. DOI: 10.3103/S1068373916090041.
  2. Belonenko TV, Sholeninova PV. On identification of mesoscale eddies from satellite altimetry based on the area in the NW Pacific. Current Problems in Remote Sensing of the Earth from Space. 2016;13(5):79–90 (in Russian). DOI: 10.21046/2070-7401-2016-13-5-79-90.
  3. Graftieaux L, Michard M, Grosjean N. Combining PIV, POD and vortex identification algorithms for the study of unsteady turbulent swirling flows. Meas. Sci. Technol. 2001;12(9):1422–1429. DOI: 10.1088/0957-0233/12/9/307.
  4. Kida S, Miura H. Identification and analysis of vortical structures. European Journal of Mechanics - B/Fluids. 1998;17(4):471–488. DOI: 10.1016/S0997-7546(98)80005-8.
  5. Menon K, Mittal R. Quantitative analysis of the kinematics and induced aerodynamic loading of individual vortices in vortex-dominated flows: A computation and data-driven approach. Journal of Computational Physics. 2021;443:110515. DOI: 10.1016/j.jcp.2021.110515.
  6. Volkov KN, Emel’yanov VN, Teterina IV, Yakovchuk MS. Visualization of vortical flows in computational fluid dynamics. Computational Mathematics and Mathematical Physics. 2017;57(8): 1360–1375. DOI: 10.1134/S0965542517080139.
  7. Yang K, Wu S, Ghista DN, Yang D, Wong KKL. Automated vortex identification based on Lagrangian averaged vorticity deviation in analysis of blood flow in the atrium from phase contrast MRI. Computer Methods and Programs in Biomedicine. 2022;216:106678. DOI: 10.1016/j.cmpb. 2022.106678.
  8. Soto-Valle R, Cioni S, Bartholomay S, Manolesos M, Nayeri CN, Bianchini A, Paschereit CO. Vortex identification methods applied to wind turbine tip vortices. Wind Energy Science. 2022;7(2): 585–602. DOI: 10.5194/wes-7-585-2022.
  9. Zhang Z, Dong S, Jin R, Dong K, Hou L, Wang B. Vortex characteristics of a gas cyclone determined with different vortex identification methods. Powder Technology. 2022;404:117370. DOI: 10.1016/j.powtec.2022.117370.
  10. Xue Y, Kumar C, Lee SK, Giacobello M, Manovski P. Identification and analysis of the meandering of a fin-tip vortex using Proper Orthogonal Decomposition (POD). International Journal of Heat and Fluid Flow. 2020;82:108556. DOI: 10.1016/j.ijheatfluidflow.2020.108556.
  11. Xiong S, He X, Tong Y, Deng Y, Zhu B. Neural vortex method: From finite Lagrangian particles to infinite dimensional Eulerian dynamics. Computers & Fluids. 2023;258:105811. DOI: 10.1016/j.compfluid.2023.105811.
  12. Govorukhin VN. Numerical analysis of the dynamics of distributed vortex configurations. Computational Mathematics and Mathematical Physics. 2016;56(8):1474–1487. DOI: 10.1134/ S0965542516080078.
  13. Filimonova AМ. Dynamics and advection in a vortex parquet. Izvestiya VUZ. Applied Nonlinear Dynamics. 2019;27(4):71–84. DOI: 10.18500/0869-6632-2019-27-4-71-84.
  14. Jeong J, Hussain F. On the identification of a vortex. Journal of Fluid Mechanics. 1995;285:69–94. DOI: 10.1017/S0022112095000462.
  15. Kolar V. Vortex identification: New requirements and limitations. International Journal of Heat and Fluid Flow. 2007;28(4):638–652. DOI: 10.1016/j.ijheatfluidflow.2007.03.004.
  16. Giagkiozis I, Fedun V, Scullion E, Jess DB, Verth G. Vortex flows in the solar atmosphere: Automated identification and statistical analysis. The Astrophysical Journal. 2018;869(2):169. DOI: 10.3847/1538-4357/aaf797.
  17. Bai X, Cheng H, Ji B, Long X, Qian Z, Peng X. Comparative Study of different vortex identification methods in a tip-leakage cavitating flow. Ocean Engineering. 2020;207:107373. DOI: 10.1016/j.oceaneng.2020.107373.
  18. Canivete Cuissa JR, Steiner O. Innovative and automated method for vortex identification. A&A. 2022;668:A118. DOI: 10.1051/0004-6361/202243740.
  19. Sadarjoen IA, Post FH. Detection, quantification, and tracking of vortices using streamline geometry. Computers & Graphics. 2000;24(3):333–341. DOI: 10.1016/S0097-8493(00)00029-7.
  20. Govorukhin VN, Filimonova AM. Analysis of the structure of vortex planar flows and their changes with time. Computational Continuum Mechanics. 2021;14(4):367–376. DOI: 10.7242/1999- 6691/2021.14.4.30.
  21. Govorukhin VN. An extended and improved particle-spectral method for analysis of unsteady inviscid incompressible flows through a channel of finite length. International Journal for Numerical Methods in Fluids. 2023;95(4):579–602. DOI: 10.1002/fld.5163.
  22. Ahmed SE, Pawar S, San O, Rasheed A, Tabib M. A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction. Computers & Fluids. 2021;221: 104895. DOI: 10.1016/j.compfluid.2021.104895.
  23. Govorukhin VN. An algorithm of vortex patches identification based on models of point vortices. Bulletin of Higher Education Institutes. North Caucasus Region. Natural Sciences. 2020;(3(207)):11–18 (in Russian). DOI: 10.18522/1026-2237-2020-3-11-18.
  24. Govorukhin VN. Transfer of passive particles in the velocity field of vortex tripole moving on a plane. Izvestiya VUZ. Applied Nonlinear Dynamics. 2023;31(3):286–304. DOI: 10.18500/0869- 6632-003039.
  25. Velasco Fuentes OU, van Heijst GJF, van Lipzig NPM. Unsteady behaviour of a topography modulated tripole. Journal of Fluid Mechanics. 1996;307:11–41. DOI: 10.1017/S0022112096 00002X.
  26. Geldhauser C, Romito M. The point vortex model for the Euler equation. AIMS Mathematics. 2019;4(3):534–575. DOI: 10.3934/math.2019.3.534.
  27. Govorukhin VN. A vortex method for computing two-dimensional inviscid incompressible flows. Computational Mathematics and Mathematical Physics. 2011;51(6):1061–1073. DOI: 10.1134/ S096554251106008X.
  28. Govorukhin VN, Filimonova АM. Numerical calculation of planar geophysical flows of an inviscid incompressible fluid by a meshfree-spectral method. Computer Research and Modeling. 2019;11(3):413–426 (in Russian). DOI: 10.20537/2076-7633-2019-11-3-413-426.
  29. Leweke T, Le Dizes S, Williamson CHK. Dynamics and instabilities of vortex pairs. Annual Review of Fluid Mechanics. 2016;48:507–541. DOI: 10.1146/annurev-fluid-122414-034558.
Received: 
13.07.2023
Accepted: 
27.09.2023
Available online: 
13.11.2023
Published: 
30.11.2023