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Collapse of transitional wall turbulence captured using a rare events algorithm

Published online by Cambridge University Press:  26 November 2021

Joran Rolland*
Affiliation:
Laboratoire de Physique à l'ENS de Lyon, UMR CNRS 5672, Univ. Lyon, Univ. Claude Bernard Lyon 1, France UMR CNRS 9014 - LMFL - Laboratoire de Mécanique des Fluides de Lille - Kampé de Fériet, Univ. Lille, Centrale Lille, ENSAM, ONERA, France
*
Email address for correspondence: joran.rolland@centralelille.fr

Abstract

This text presents one of the first successful applications of a rare events sampling method for the study of multistability in a turbulent flow without stochastic energy injection. The trajectories of collapse of turbulence in plane Couette flow, and their probability and rate of occurrence are systematically computed using adaptive multilevel splitting (AMS). The AMS computations are performed in a system of size $L_x\times L_z=24\times 18$ at Reynolds number $R=370$ with an acceleration by a factor ${O}(10)$ with respect to direct numerical simulations (DNS) and in a system of size $L_x\times L_z=36\times 27$ at Reynolds number $R=377$ with an acceleration by a factor ${O}(10^3)$. The AMS results are validated by a comparison with DNS in the smaller system. Visualisations indicate that turbulence collapses because the self-sustaining process of turbulence fails locally. The streamwise vortices decay first in streamwise elongated holes, leaving streamwise invariant streamwise velocity tubes that experience viscous decay. These holes then extend in the spanwise direction. The examination of more than a thousand trajectories in the $(E_{k,x}=\int u_x^2/2\,\textrm {d}^3\boldsymbol {x},E_{k,y-z}=\int (u_y^2/2+u_z^2/2)\,\textrm {d}^3\boldsymbol {x})$ plane in the smaller system confirms the faster decay of streamwise vortices and shows concentration of trajectories. This hints at an instanton phenomenology in the large size limit. The computation of turning point states, beyond which laminarisation is certain, confirms the hole formation scenario and shows that it is more pronounced in larger systems. Finally, the examination of non-reactive trajectories indicates that both the vortices and the streaks reform concomitantly when the laminar holes close.

Type
JFM Papers
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

REFERENCES

Baars, S., Castellana, D., Wubs, F.W. & Dijkstra, H.A. 2021 Application of adaptive multilevel splitting to high-dimensional dynamical systems. J. Comput. Phys. 424, 109876.CrossRefGoogle Scholar
Berhanu, M., et al. 2007 Magnetic field reversals in an experimental turbulent dynamo. Europhys. Lett. 77 (5), 59001.CrossRefGoogle Scholar
Bottin, S. & Chaté, H. 1998 Statistical analysis of the transition to turbulence in plane Couette flow. Eur. Phys. J. B 6 (1), 143155.CrossRefGoogle Scholar
Bouchet, F. & Reygner, J. 2016 Generalisation of the Eyring–Kramers transition rate formula to irreversible diffusion processes. Ann. Henri Poincaré 17, 34993532. Springer.CrossRefGoogle Scholar
Bouchet, F., Rolland, J. & Simonnet, E. 2019 a Rare event algorithm links transitions in turbulent flows with activated nucleations. Phys. Rev. Lett. 122 (7), 074502.CrossRefGoogle ScholarPubMed
Bouchet, F., Rolland, J. & Wouters, J. 2019 b Rare event sampling methods. Chaos 29 (8), 2.CrossRefGoogle ScholarPubMed
Bréhier, C.-E., Gazeau, M., Goudenège, L., Lelièvre, T. & Rousset, M. 2016 Unbiasedness of some generalized adaptive multilevel splitting algorithms. Ann. Appl. Probab. 26 (6), 35593601.CrossRefGoogle Scholar
Cérou, F., Delyon, B., Guyader, A. & Rousset, M. 2019 a On the asymptotic normality of adaptive multilevel splitting. SIAM/ASA J. Uncertain. Quantif. 7 (1), 130.CrossRefGoogle Scholar
Cérou, F. & Guyader, A. 2007 Adaptive multilevel splitting for rare event analysis. Stoch. Anal. Appl. 25 (2), 417443.CrossRefGoogle Scholar
Cérou, F., Guyader, A., Lelievre, T. & Malrieu, F. 2013 On the length of one-dimensional reactive paths. Lat. Am. J. Probab. Math. Stat. 10 (1), 359389.Google Scholar
Cérou, F., Guyader, A., Lelievre, T. & Pommier, D. 2011 A multiple replica approach to simulate reactive trajectories. J. Chem. Phys. 134 (5), 054108.CrossRefGoogle ScholarPubMed
Cérou, F., Guyader, A. & Rousset, M. 2019 b Adaptive multilevel splitting: historical perspective and recent results. Chaos 29 (4), 043108.CrossRefGoogle ScholarPubMed
Chantry, M., Tuckerman, L.S. & Barkley, D. 2017 Universal continuous transition to turbulence in a planar shear flow. J. Fluid Mech. 824, R1.CrossRefGoogle Scholar
De Lozar, A., Mellibovsky, F., Avila, M. & Hof, B. 2012 Edge state in pipe flow experiments. Phys. Rev. Lett. 108 (21), 214502.CrossRefGoogle Scholar
De Souza, D., Bergier, T. & Monchaux, R. 2020 Transient states in plane Couette flow. J. Fluid Mech. 903, A33.CrossRefGoogle Scholar
Devetsikiotis, M. & Townsend, J.K. 1993 Statistical optimization of dynamic importance sampling parameters for efficient simulation of communication networks. IEEE ACM Trans. Netw. 1 (3), 293305.CrossRefGoogle Scholar
Duguet, Y., Le Maitre, O. & Schlatter, P. 2011 Stochastic and deterministic motion of a laminar-turbulent front in a spanwisely extended Couette flow. Phys. Rev. E 84 (6), 066315.CrossRefGoogle Scholar
Ebener, L., Margazoglou, G., Friedrich, J., Biferale, L. & Grauer, R. 2019 Instanton based importance sampling for rare events in stochastic PDES. Chaos 29 (6), 063102.CrossRefGoogle ScholarPubMed
Eckhardt, B., Faisst, H., Schmiegel, A. & Schneider, T.M. 2008 Dynamical systems and the transition to turbulence in linearly stable shear flows. Phil. Trans. R. Soc. A 366 (1868), 12971315.CrossRefGoogle ScholarPubMed
Eckhardt, B., Schneider, T.M., Hof, B. & Westerweel, J. 2007 Turbulence transition in pipe flow. Annu. Rev. Fluid Mech. 39, 447468.CrossRefGoogle Scholar
Faisst, H. & Eckhardt, B. 2003 Sensitive dependence on initial conditions in transition to turbulence in pipe flow. arXiv:physics/0312078.CrossRefGoogle Scholar
Gibson, J.F., Halcrow, J. & Cvitanović, P. 2008 Visualizing the geometry of state space in plane Couette flow. J. Fluid Mech. 611, 107130.CrossRefGoogle Scholar
Glasserman, P., Heidelberger, P., Shahabuddin, P. & Zajic, T. 1998 A large deviations perspective on the efficiency of multilevel splitting. IEEE Trans. Autom. Control 43 (12), 16661679.CrossRefGoogle Scholar
Gomé, S., Tuckerman, L.S. & Barkley, D. 2020 Statistical transition to turbulence in plane channel flow. Phys. Rev. Fluids 5, 083905.CrossRefGoogle Scholar
Grafke, T. & Vanden-Eijnden, E. 2019 Numerical computation of rare events via large deviation theory. Chaos 29 (6), 063118.CrossRefGoogle ScholarPubMed
Grandemange, M., Gohlke, M. & Cadot, O. 2013 Turbulent wake past a three-dimensional blunt body. Part 1. Global modes and bi-stability. J. Fluid Mech. 722, 5184.CrossRefGoogle Scholar
Hamilton, J.M., Kim, J. & Waleffe, F. 1995 Regeneration mechanisms of near-wall turbulence structures. J. Fluid Mech. 287 (1), 317348.CrossRefGoogle Scholar
Hänggi, P., Talkner, P. & Borkovec, M. 1990 Reaction-rate theory: fifty years after Kramers. Rev. Mod. Phys. 62 (2), 251.CrossRefGoogle Scholar
Hartmann, C., Kebiri, O., Neureither, L. & Richter, L. 2019 Variational approach to rare event simulation using least-squares regression. Chaos 29 (6), 063107.CrossRefGoogle ScholarPubMed
Herbert, C., Caballero, R. & Bouchet, F. 2020 Atmospheric bistability and abrupt transitions to superrotation: wave–jet resonance and Hadley cell feedbacks. J. Atmos. Sci. 77 (1), 3149.CrossRefGoogle Scholar
Jiménez, J. & Moin, P. 1991 The minimal flow unit in near-wall turbulence. J. Fluid Mech. 225, 213240.CrossRefGoogle Scholar
Kawahara, G., Jiménez, J., Uhlmann, M. & Pinelli, A. 2003 Linear instability of a corrugated vortex sheet-a model for streak instability. J. Fluid Mech. 483, 315342.CrossRefGoogle Scholar
Kim, H.-J. & Durbin, P.A. 1988 Investigation of the flow between a pair of circular cylinders in the flopping regime. J. Fluid Mech. 196, 431448.CrossRefGoogle Scholar
L'Ecuyer, P., Mandjes, M. & Tuffin, B. 2009 Importance Sampling in Rare Event Simulation. Wiley Online Library.CrossRefGoogle Scholar
Lestang, T., Bouchet, F. & Lévêque, E. 2020 Numerical study of extreme mechanical force exerted by a turbulent flow on a bluff body by direct and rare-event sampling techniques. J. Fluid Mech. 895, A19.CrossRefGoogle Scholar
Lestang, T., Ragone, F., Bréhier, C.-E., Herbert, C. & Bouchet, F. 2018 Computing return times or return periods with rare event algorithms. J. Stat. Mech. 2018 (4), 043213.CrossRefGoogle Scholar
Liu, T., Semin, B., Klotz, L., Godoy-Diana, R., Wesfreid, J.E. & Mullin, T. 2020 Anisotropic decay of turbulence in plane Couette-Poiseuille flow. J. Fluid Mechanics 915, A65.CrossRefGoogle Scholar
Lopes, L.J.S. & Lelièvre, T. 2019 Analysis of the adaptive multilevel splitting method on the isomerization of alanine dipeptide. J. Comput. Chem. 40 (11), 11981208.CrossRefGoogle ScholarPubMed
Manneville, P. 2011 On the decay of turbulence in plane Couette flow. Fluid Dyn. Res. 43 (6), 065501.CrossRefGoogle Scholar
Marquillie, M., Ehrenstein, U. & Laval, J.-P. 2011 Instability of streaks in wall turbulence with adverse pressure gradient. J. Fluid Mech. 681, 205240.CrossRefGoogle Scholar
Metzner, P., Schütte, C. & Vanden-Eijnden, E. 2006 Illustration of transition path theory on a collection of simple examples. J. Chem. Phys. 125 (8), 084110.CrossRefGoogle ScholarPubMed
Moxey, D. & Barkley, D. 2010 Distinct large-scale turbulent-laminar states in transitional pipe flow. Proc. Natl Acad. Sci. USA 107 (18), 80918096.CrossRefGoogle ScholarPubMed
Onsager, L. 1938 Initial recombination of ions. Phys. Rev. 54 (8), 554.CrossRefGoogle Scholar
Podvin, B. & Sergent, A. 2017 Precursor for wind reversal in a square Rayleigh–Bénard cell. Phys. Rev. E 95 (1), 013112.CrossRefGoogle Scholar
Pope, S.B. 2001 Turbulent Flows. IOP Publishing.Google Scholar
Ragone, F. & Bouchet, F. 2019 Computation of extreme values of time averaged observables in climate models with large deviation techniques. J. Stat. Phys. 179, 16371665.CrossRefGoogle Scholar
Ragone, F. & Bouchet, F. 2021 Rare event algorithm study of extreme warm summers and heat waves over Europe. Geophys. Res. Lett. 48 (12), e2020GL091197.CrossRefGoogle Scholar
Rolland, J. 2015 Mechanical and statistical study of the laminar hole formation in transitional plane Couette flow. Eur. Phys. J. B 88 (3), 66.CrossRefGoogle Scholar
Rolland, J. 2018 Extremely rare collapse and build-up of turbulence in stochastic models of transitional wall flows. Phys. Rev. E 97 (2), 023109.CrossRefGoogle ScholarPubMed
Rolland, J., Bouchet, F. & Simonnet, E. 2016 Computing transition rates for the 1-d stochastic Ginzburg–Landau–Allen–Cahn equation for finite-amplitude noise with a rare event algorithm. J. Stat. Phys. 162 (2), 277311.CrossRefGoogle Scholar
Rolland, J. & Simonnet, E. 2015 Statistical behaviour of adaptive multilevel splitting algorithms in simple models. J. Comput. Phys. 283, 541558.CrossRefGoogle Scholar
Romanov, V.A. 1973 Stability of plane-parallel Couette flow. Funct. Anal. Applics. 7 (2), 137146.CrossRefGoogle Scholar
Schmiegel, A. & Eckhardt, B. 1997 Fractal stability border in plane Couette flow. Phys. Rev. Lett. 79 (26), 5250.CrossRefGoogle Scholar
Schneider, T.M., Eckhardt, B. & Yorke, J.A. 2007 Turbulence transition and the edge of chaos in pipe flow. Phys. Rev. Lett. 99 (3), 034502.CrossRefGoogle ScholarPubMed
Shi, L., Avila, M. & Hof, B. 2013 Scale invariance at the onset of turbulence in Couette flow. Phys. Rev. Lett. 110 (20), 204502.CrossRefGoogle Scholar
Simonnet, E. 2016 Combinatorial analysis of the adaptive last particle method. Stat. Comput. 26 (1–2), 211230.CrossRefGoogle Scholar
Simonnet, E., Rolland, J. & Bouchet, F. 2021 Multistability and rare spontaneous transitions between climate and jet configurations in a barotropic model of the Jovian mid-latitude troposphere. J. Atmos. Sci. 78, 18891911.Google Scholar
Touchette, H. 2009 The large deviation approach to statistical mechanics. Phys. Rep. 478 (1–3), 169.CrossRefGoogle Scholar
Waleffe, F. 1997 On a self-sustaining process in shear flows. Phys. Fluids 9 (4), 883900.CrossRefGoogle Scholar
Wan, X. & Yu, H. 2017 A dynamic-solver–consistent minimum action method: with an application to 2D Navier–Stokes equations. J. Comput. Phys. 331, 209226.CrossRefGoogle Scholar
Willis, A.P. & Kerswell, R.R. 2009 Turbulent dynamics of pipe flow captured in a reduced model: puff relaminarization and localized ‘edge's states. J. Fluid Mech. 619, 213233.CrossRefGoogle Scholar

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