Fast and robust computation of coherent Lagrangian vortices on very large two-dimensional domains
The SMAI Journal of computational mathematics, Tome 6 (2020), pp. 101-124.

We describe a new method for computing coherent Lagrangian vortices in two-dimensional flows according to any of the following approaches: black-hole vortices [24], objective Eulerian Coherent Structures (OECSs) [39], material barriers to diffusive transport [25, 26], and constrained diffusion barriers [26]. The method builds on ideas developed previously in [30], but our implementation alleviates a number of shortcomings and allows for the fully automated detection of such vortices on unprecedentedly challenging real-world flow problems, for which specific human interference is absolutely infeasible. Challenges include very large domains and/or parameter spaces. We demonstrate the efficacy of our method in dealing with such challenges on two test cases: first, a parameter study of a turbulent flow, and second, computing material barriers to diffusive transport in the global ocean.

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Publié le :
DOI : 10.5802/smai-jcm.63
Classification : 65P99, 86-08
Mots clés : Lagrangian coherent structures, coherent vortices, turbulent flows
Karrasch, Daniel 1 ; Schilling, Nathanael 1

1 Department of Mathematics, Technische Universität München, Garching bei München, Germany
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     title = {Fast and robust computation of coherent {Lagrangian} vortices on very large two-dimensional domains},
     journal = {The SMAI Journal of computational mathematics},
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Karrasch, Daniel; Schilling, Nathanael. Fast and robust computation of coherent Lagrangian vortices on very large two-dimensional domains. The SMAI Journal of computational mathematics, Tome 6 (2020), pp. 101-124. doi : 10.5802/smai-jcm.63. http://www.numdam.org/articles/10.5802/smai-jcm.63/

[1] Abernathey, R.; Haller, G. Transport by Lagrangian Vortices in the Eastern Pacific, J. Phys. Ocean., Volume 48 (2018) no. 3, pp. 667-685 | DOI

[2] Allshouse, M. R.; Thiffeault, J.-L. Detecting coherent structures using braids, Physica D, Volume 241 (2012) no. 2, pp. 95-105 | DOI

[3] Banisch, R.; Koltai, P. Understanding the geometry of transport: diffusion maps for Lagrangian trajectory data unravel coherent sets, Chaos, Volume 27 (2017) no. 3, 035804 | DOI | MR | Zbl

[4] Bezanson, J.; Edelman, A.; Karpinski, S.; Shah, V. B. Julia: A fresh approach to numerical computing, SIAM Rev., Volume 59 (2017) no. 1, pp. 65-98 | DOI | MR | Zbl

[5] Carlsson, K. NearestNeighbors.jl: High performance nearest neighbor data structures and algorithms for Julia, 2018 (https://github.com/kristofferc/nearestneighbors.jl)

[6] Chilenski, M.; Faust, I.; Walk, J. eqtools: Modular, extensible, open-source, cross-machine Python tools for working with magnetic equilibria, Comput. Phys. Commun., Volume 210 (2017), pp. 155-162 | DOI

[7] Constantinou, N. C. Formation of large-scale structures by turbulence in rotating planets, Ph. D. Thesis, National and Kapodistrian University of Athens (2015) | arXiv

[8] Constantinou, N. C.; Wagner, G. L. FourierFlows/GeophysicalFlows.jl: GeophysicalFlows v0.3.0, 2019 (https://github.com/fourierflows/geophysicalflows.jl) | DOI

[9] de Ruijter, W. P. M.; Biastoch, A.; Drijfhout, S. S.; Lutjeharms, J. R. E.; Matano, R. P.; Pichevin, T.; van Leeuwen, P. J.; Weijer, W. Indian-Atlantic interocean exchange: Dynamics, estimation and impact, J. Geophys. Res. Oceans, Volume 104 (1999) no. C9, pp. 20885-20910 | DOI

[10] Delmarcelle, T.; Hesselink, L. The topology of symmetric, second-order tensor fields, Proceedings of the conference on Visualization ’94, IEEE (1994), pp. 140-147 | DOI

[11] Duff, G. F. D. Limit-Cycles and Rotated Vector Fields, Ann. Math., Volume 57 (1953) no. 1, pp. 15-31 | DOI | MR | Zbl

[12] Farazmand, M.; Blazevski, D.; Haller, G. Shearless transport barriers in unsteady two-dimensional flows and maps, Physica D, Volume 278-279 (2014), pp. 44-57 | DOI | MR | Zbl

[13] Froyland, G. An analytic framework for identifying finite-time coherent sets in time-dependent dynamical systems, Physica D, Volume 250 (2013) no. 0, pp. 1-19 | DOI | MR | Zbl

[14] Froyland, G. Dynamic isoperimetry and the geometry of Lagrangian coherent structures, Nonlinearity, Volume 28 (2015) no. 10, pp. 3587-3622 | DOI | MR | Zbl

[15] Froyland, G.; Junge, O. Robust FEM-Based Extraction of Finite-Time Coherent Sets Using Scattered, Sparse, and Incomplete Trajectories, SIAM J. Appl. Dyn. Syst., Volume 17 (2018) no. 2, pp. 1891-1924 | DOI | MR | Zbl

[16] Froyland, G.; Llyod, S.; Santitissadeekorn, N. Coherent sets for nonautonomous dynamical systems, Physica D, Volume 239 (2010) no. 16, pp. 1527-1541 | DOI | MR

[17] Froyland, G.; Padberg-Gehle, K. A rough-and-ready cluster-based approach for extracting finite-time coherent sets from sparse and incomplete trajectory data, Chaos, Volume 25 (2015) no. 8, 087406 | DOI | MR | Zbl

[18] Froyland, G.; Rock, Chr. P.; Sakellariou, K. Sparse eigenbasis approximation: Multiple feature extraction across spatiotemporal scales with application to coherent set identification, Commun. Nonlinear Sci. Numer. Simul., Volume 77 (2019), pp. 81-107 | DOI | MR

[19] Froyland, G.; Santitissadeekorn, N.; Monahan, A. Transport in time-dependent dynamical systems: Finite-time coherent sets, Chaos, Volume 20 (2010) no. 4, 043116 | DOI | MR | Zbl

[20] Hadjighasem, A.; Farazmand, M.; Blazevski, D.; Froyland, G.; Haller, G. A critical comparison of Lagrangian methods for coherent structure detection, Chaos, Volume 27 (2017) no. 5, 053104 | DOI | MR | Zbl

[21] Hadjighasem, A.; Haller, G. Geodesic Transport Barriers in Jupiter’s Atmosphere: A Video-Based Analysis, SIAM Rev., Volume 58 (2016) no. 1, pp. 69-89 | DOI | MR | Zbl

[22] Hadjighasem, A.; Karrasch, D.; Teramoto, H.; Haller, G. Spectral-clustering approach to Lagrangian vortex detection, Phys. Rev. E, Volume 93 (2016), 063107 | DOI

[23] Haller, G.; Beron-Vera, F. Geodesic theory of transport barriers in two-dimensional flows, Physica D, Volume 241 (2012) no. 20, pp. 1680-1702 | DOI | Zbl

[24] Haller, G.; Beron-Vera, F. Coherent Lagrangian vortices: the black holes of turbulence, J. Fluid Mech., Volume 731 (2013), R4 | DOI | Zbl

[25] Haller, G.; Karrasch, D.; Kogelbauer, F. Material barriers to diffusive and stochastic transport, Proc. Natl. Acad. Sci. USA, Volume 115 (2018) no. 37, pp. 9074-9079 | DOI | MR | Zbl

[26] Haller, G.; Karrasch, D.; Kogelbauer, F. Barriers to the Transport of Diffusive Scalars in Compressible Flows (2019) (submitted preprint, https://arxiv.org/abs/1902.09786) | Zbl

[27] Hopf, H. Lectures on differential geometry in the large, Lecture Notes in Mathematics, 1000, Springer, 1989 | DOI | MR

[28] Huhn, F.; van Rees, W. M.; Gazzola, M.; Rossinelli, D.; Haller, G.; Koumoutsakos, P. Quantitative flow analysis of swimming dynamics with coherent Lagrangian vortices, Chaos, Volume 25 (2015) no. 8, 087405 | DOI | MR

[29] Karatzas, I.; Shreve, S. Brownian Motion and Stochastic Calculus, Graduate Texts in Mathematics, 113, Springer, 1991 | DOI | MR | Zbl

[30] Karrasch, D.; Huhn, F.; Haller, G. Automated detection of coherent Lagrangian vortices in two-dimensional unsteady flows, Proc. A, R. Soc. Lond., Volume 471 (2015) no. 2173, 20140639 | DOI | MR | Zbl

[31] Karrasch, D.; Keller, J. A geometric heat-flow theory of Lagrangian coherent structures (2016) (https://arxiv.org/abs/1608.05598)

[32] Lekien, F.; Marsden, J. E. Tricubic interpolation in three dimensions, Int. J. Numer. Meth. Engng., Volume 63 (2005) no. 3, pp. 455-471 | DOI | MR | Zbl

[33] Onu, K.; Huhn, F.; Haller, G. LCS Tool: A computational platform for Lagrangian coherent structures, J. Comput. Sci., Volume 7 (2015), pp. 26-36 | DOI

[34] Padberg-Gehle, K.; Schneide, C. Network-based study of Lagrangian transport and mixing, Nonlinear Process. Geophys., Volume 24 (2017) no. 4, pp. 661-671 | DOI

[35] Perko, L. Differential Equations and Dynamical Systems, Texts in Applied Mathematics, 7, Springer, 2001 | DOI | MR | Zbl

[36] Press, W. H.; Rybicki, G. B. Enhancement of Passive Diffusion and Suppression of Heat Flux in a Fluid with Time Varying Shear, Astrophys. J., Volume 248 (1981), pp. 751-766 | DOI | MR

[37] Rackauckas, C.; Nie, Q. DifferentialEquations.jl – A Performant and Feature-Rich Ecosystem for Solving Differential Equations in Julia, J. Open Res. Softw., Volume 5 (2017) no. 1, p. 15 | DOI

[38] Schilling, N. OceanTools.jl (2020) (https://github.com/CoherentStructures/OceanTools.jl)

[39] Serra, M.; Haller, G. Objective Eulerian coherent structures, Chaos, Volume 26 (2016) no. 5, 053110 | DOI | MR | Zbl

[40] Serra, M.; Haller, G. Efficient computation of null geodesics with applications to coherent vortex detection, Proc. A, R. Soc. Lond., Volume 473 (2017) no. 2199, 20160807 | DOI | MR | Zbl

[41] Serra, M.; Sathe, P.; Beron-Vera, F.; Haller, G. Uncovering the Edge of the Polar Vortex, J. Atmos. Sci., Volume 74 (2017) no. 11, pp. 3871-3885 | DOI

[42] Spivak, M. A Comprehensive Introduction to Differential Geometry, 3, Publish or Perish Inc., 1999 | Zbl

[43] Thiffeault, J.-L. Advection–diffusion in Lagrangian coordinates, Phys. Lett. A, Volume 309 (2003) no. 5–6, pp. 415-422 | DOI | MR | Zbl

[44] Tricoche, X.; Scheuermann, G. Topology simplification of symmetric, second-order 2D tensor fields, Geometric Modeling for Scientific Visualization (Mathematics and Visualization), Springer, 2004, pp. 275-291 | DOI

[45] Tricoche, X.; Scheuermann, G.; Hagen, H.; Clauss, St. Vector and Tensor Field Topology Simplification on Irregular Grids, Data Visualization (Ebert, D. S.; Favre, J. M.; Peikert, R., eds.), Springer (2001), pp. 107-116 | DOI

[46] Wagner, G. L.; Constantinou, N. C.; Piibeleht, M. FourierFlows/FourierFlows.jl: FourierFlows v0.3., 2019 (https://zenodo.org/record/2530192) | DOI

[47] Wischgoll, T.; Scheuermann, G. Detection and visualization of closed streamlines in planar flows, IEEE Trans. Visual. Comput. Graph., Volume 7 (2001) no. 2, pp. 165-172 | DOI

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