A minimization principle for the description of modes associated with finite-time instabilities

We introduce a minimization formulation for the determination of a finite-dimensional, time-dependent, orthonormal basis that captures directions of the phase space associated with transient instabilities. While these instabilities have finite lifetime, they can play a crucial role either by altering the system dynamics through the activation of other instabilities or by creating sudden nonlinear energy transfers that lead to extreme responses. However, their essentially transient character makes their description a particularly challenging task. We develop a minimization framework that focuses on the optimal approximation of the system dynamics in the neighbourhood of the system state. This minimization formulation results in differential equations that evolve a time-dependent basis so that it optimally approximates the most unstable directions. We demonstrate the capability of the method for two families of problems: (i) linear systems, including the advection–diffusion operator in a strongly non-normal regime as well as the Orr–Sommerfeld/Squire operator, and (ii) nonlinear problems, including a low-dimensional system with transient instabilities and the vertical jet in cross-flow. We demonstrate that the time-dependent subspace captures the strongly transient non-normal energy growth (in the short-time regime), while for longer times the modes capture the expected asymptotic behaviour.

[1]  Themistoklis P. Sapsis,et al.  Quantification and prediction of extreme events in a one-dimensional nonlinear dispersive wave model , 2014, 1401.3397.

[2]  Conditional statistics for a passive scalar with a mean gradient and intermittency , 2006 .

[3]  Henk A. Dijkstra,et al.  Interaction of Additive Noise and Nonlinear Dynamics in the Double-Gyre Wind-Driven Ocean Circulation , 2013 .

[4]  O. Marxen,et al.  Steady solutions of the Navier-Stokes equations by selective frequency damping , 2006 .

[5]  D. Solli,et al.  Recent progress in investigating optical rogue waves , 2013 .

[6]  Themistoklis P. Sapsis,et al.  Reduced-order precursors of rare events in unidirectional nonlinear water waves , 2015, Journal of Fluid Mechanics.

[7]  Alan S. Osborne,et al.  THE FOURTEENTH 'AHA HULIKO' A HAWAIIAN WINTER WORKSHOP , 2005 .

[8]  Thomas Y. Hou,et al.  A dynamically bi-orthogonal method for time-dependent stochastic partial differential equations I: Derivation and algorithms , 2013, J. Comput. Phys..

[9]  Dan S. Henningson,et al.  Pseudospectra of the Orr-Sommerfeld Operator , 1993, SIAM J. Appl. Math..

[10]  Themistoklis P Sapsis,et al.  Unsteady evolution of localized unidirectional deep-water wave groups. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  Hessam Babaee,et al.  Analysis and optimization of film cooling effectiveness , 2013 .

[12]  Alexis Tantet,et al.  An early warning indicator for atmospheric blocking events using transfer operators. , 2015, Chaos.

[13]  John Kim,et al.  Regeneration mechanisms of near-wall turbulence structures , 1995, Journal of Fluid Mechanics.

[14]  A. Majda Challenges in Climate Science and Contemporary Applied Mathematics , 2012 .

[15]  Hessam Babaee,et al.  Uncertainty quantification of film cooling effectiveness in gas turbines , 2013 .

[16]  H. Lugt,et al.  Laminar flow behavior under slip−boundary conditions , 1975 .

[17]  Piotr K. Smolarkiewicz,et al.  CRCP: a cloud resolving convection parameterization for modeling the tropical convecting atmosphere , 1999 .

[18]  Lloyd N. Trefethen,et al.  Pseudospectra of Linear Operators , 1997, SIAM Rev..

[19]  D. Pullin,et al.  On the two-dimensional stability of the axisymmetric Burgers vortex , 1995 .

[20]  Andrew J. Majda,et al.  Blending Modified Gaussian Closure and Non-Gaussian Reduced Subspace Methods for Turbulent Dynamical Systems , 2013, J. Nonlinear Sci..

[21]  Igor Chueshov,et al.  Stability and Capsizing of Ships in Random Sea – a Survey , 2004 .

[22]  T. Sapsis,et al.  Dynamical criteria for the evolution of the stochastic dimensionality in flows with uncertainty , 2012 .

[23]  Pierre F. J. Lermusiaux,et al.  Dynamically orthogonal field equations for continuous stochastic dynamical systems , 2009 .

[24]  Stephen B. Pope,et al.  Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation , 1997 .

[25]  Andrew J. Majda,et al.  Lessons in uncertainty quantification for turbulent dynamical systems , 2012 .

[26]  Ilarion V. Melnikov,et al.  Mechanisms of extensive spatiotemporal chaos in Rayleigh–Bénard convection , 2000, Nature.

[27]  I. Mezic,et al.  Nonlinear Koopman Modes and a Precursor to Power System Swing Instabilities , 2012, IEEE Transactions on Power Systems.

[28]  P. Schmid Linear stability theory and bypass transition in shear flows , 2000 .

[29]  L. Böberg,et al.  Onset of Turbulence in a Pipe , 1988 .

[30]  S. Orszag Accurate solution of the Orr–Sommerfeld stability equation , 1971, Journal of Fluid Mechanics.

[31]  Andrew J. Majda,et al.  Intermittency in turbulent diffusion models with a mean gradient , 2015 .

[32]  Anne E. Trefethen,et al.  Hydrodynamic Stability Without Eigenvalues , 1993, Science.

[33]  Andrew J. Majda,et al.  Blended reduced subspace algorithms for uncertainty quantification of quadratic systems with a stable mean state , 2013 .

[34]  G. Karniadakis,et al.  Spectral/hp Element Methods for Computational Fluid Dynamics , 2005 .

[35]  A. Bourlioux,et al.  Elementary models with probability distribution function intermittency for passive scalars with a mean gradient , 2002 .

[36]  Gary J. Chandler,et al.  Invariant recurrent solutions embedded in a turbulent two-dimensional Kolmogorov flow , 2013, Journal of Fluid Mechanics.

[37]  Andrew J. Majda Real world turbulence and modern applied mathematics , 2000 .

[38]  Yoshihiko Susuki,et al.  Nonlinear Koopman modes and power system stability assessment without models , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[39]  Andrew J. Majda,et al.  Blended particle methods with adaptive subspaces for filtering turbulent dynamical systems , 2015 .

[40]  Themistoklis P. Sapsis,et al.  Attractor local dimensionality, nonlinear energy transfers and finite-time instabilities in unstable dynamical systems with applications to two-dimensional fluid flows , 2013, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[41]  Umberto Bortolozzo,et al.  Rogue waves and their generating mechanisms in different physical contexts , 2013 .

[42]  D. Barkley,et al.  Distinct large-scale turbulent-laminar states in transitional pipe flow , 2010, Proceedings of the National Academy of Sciences.

[43]  S. P. Cornelius,et al.  Realistic control of network dynamics , 2013, Nature Communications.

[44]  David E. Keyes,et al.  Numerical Solution of Two-Dimensional Axisymmetric Laminar Diffusion Flames , 1986 .

[45]  Alexander F. Vakakis,et al.  Some results on the dynamics of the linear parametric oscillator with general time-varying frequency , 2006, Appl. Math. Comput..

[46]  W. Grabowski Coupling Cloud Processes with the Large-Scale Dynamics Using the Cloud-Resolving Convection Parameterization (CRCP) , 2001 .

[47]  Kathryn M. Butler,et al.  Three‐dimensional optimal perturbations in viscous shear flow , 1992 .

[48]  Gilead Tadmor,et al.  Reduced-order models for closed-loop wake control , 2011, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[49]  F. Fedele Rogue waves in oceanic turbulence , 2008 .

[50]  C. Garrett Rogue waves , 2012 .

[51]  Andrew J. Majda,et al.  A statistically accurate modified quasilinear Gaussian closure for uncertainty quantification in turbulent dynamical systems , 2013 .

[52]  D. Barkley,et al.  The Onset of Turbulence in Pipe Flow , 2011, Science.

[53]  Themistoklis P. Sapsis,et al.  Probabilistic response and rare events in Mathieu׳s equation under correlated parametric excitation , 2016, 1706.00109.

[54]  Andrew J. Majda,et al.  Filtering Complex Turbulent Systems , 2012 .

[55]  S. Grossmann The onset of shear flow turbulence , 2000 .

[56]  George Haller,et al.  Localized Instability and Attraction along Invariant Manifolds , 2010, SIAM J. Appl. Dyn. Syst..

[57]  Brian F. Farrell,et al.  Generalized Stability Theory. Part II: Nonautonomous Operators , 1996 .

[58]  Andrew J Majda,et al.  Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems , 2013, Proceedings of the National Academy of Sciences.

[59]  Di Qi,et al.  Blended particle filters for large-dimensional chaotic dynamical systems , 2014, Proceedings of the National Academy of Sciences.

[60]  D. Henningson,et al.  A mechanism for bypass transition from localized disturbances in wall-bounded shear flows , 1993, Journal of Fluid Mechanics.

[61]  Themistoklis P. Sapsis,et al.  Probabilistic Description of Extreme Events in Intermittently Unstable Dynamical Systems Excited by Correlated Stochastic Processes , 2014, SIAM/ASA J. Uncertain. Quantification.

[62]  B. R. Noack,et al.  Feedback shear layer control for bluff body drag reduction , 2008, Journal of Fluid Mechanics.

[63]  Pierre F. J. Lermusiaux,et al.  Global analysis of Navier–Stokes and Boussinesq stochastic flows using dynamical orthogonality , 2013, Journal of Fluid Mechanics.

[64]  A Montina,et al.  Granularity and inhomogeneity are the joint generators of optical rogue waves. , 2011, Physical review letters.

[65]  Dan S. Henningson,et al.  Global stability of a jet in crossflow , 2009, Journal of Fluid Mechanics.

[66]  Andrew J. Majda,et al.  Quantifying uncertainty for predictions with model error in non-Gaussian systems with intermittency , 2012 .

[67]  P. Schmid Nonmodal Stability Theory , 2007 .