A Reduced Basis Technique for Long-Time Unsteady Turbulent Flows
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Yvon Maday | Tommaso Taddei | Lambert Fick | A. Patera | Y. Maday | T. Taddei | Lambert Fick | Anthony T Patera
[1] Habib N. Najm,et al. Bayesian estimation of Karhunen-Loève expansions; A random subspace approach , 2016, J. Comput. Phys..
[2] P. Fischer,et al. High-Order Methods for Incompressible Fluid Flow , 2002 .
[3] Traian Iliescu,et al. Proper orthogonal decomposition closure models for turbulent flows: A numerical comparison , 2011, 1106.3585.
[4] R. Temam,et al. Nonlinear Galerkin methods: The finite elements case , 1990 .
[5] Sigal Gottlieb,et al. Spectral Methods , 2019, Numerical Methods for Diffusion Phenomena in Building Physics.
[6] Stephen J. Wright,et al. Numerical Optimization , 2018, Fundamental Statistical Inference.
[7] Mario Ohlberger,et al. Nonlinear reduced basis approximation of parameterized evolution equations via the method of freezing , 2013 .
[8] C. Farhat,et al. Efficient non‐linear model reduction via a least‐squares Petrov–Galerkin projection and compressive tensor approximations , 2011 .
[9] Pierre Sagaut,et al. Intermodal energy transfers in a proper orthogonal decomposition–Galerkin representation of a turbulent separated flow , 2003, Journal of Fluid Mechanics.
[10] Charles-Henri Bruneau,et al. Enablers for robust POD models , 2009, J. Comput. Phys..
[11] Nadine Aubry,et al. Spatio-temporal symmetries and bifurcations via bi-orthogonal decompositions , 1992 .
[12] M. D. Deshpande,et al. FLUID MECHANICS IN THE DRIVEN CAVITY , 2000 .
[13] Earl H. Dowell,et al. Stabilization of projection-based reduced order models of the Navier–Stokes , 2012 .
[14] M. Bergmann. Optimisation aérodynamique par réduction de modèle POD et contrôle optimal : application au sillage laminaire d'un cylindre circulaire , 2004 .
[15] Jens L. Eftang,et al. An hp certified reduced basis method for parametrized parabolic partial differential equations , 2011 .
[16] L. Sirovich. Turbulence and the dynamics of coherent structures. I. Coherent structures , 1987 .
[17] Jean-Antoine Désidéri,et al. Stability Properties of POD–Galerkin Approximations for the Compressible Navier–Stokes Equations , 2000 .
[18] P. Sagaut,et al. Calibrated reduced-order POD-Galerkin system for fluid flow modelling , 2005 .
[19] E. Tadmor,et al. Convergence of spectral methods for nonlinear conservation laws. Final report , 1989 .
[20] G. Karniadakis,et al. Spectral/hp Element Methods for Computational Fluid Dynamics , 2005 .
[21] G. Rozza,et al. POD-Galerkin reduced order methods for CFD using Finite Volume Discretisation: vortex shedding around a circular cylinder , 2017, 1701.03424.
[22] A. Patera. A spectral element method for fluid dynamics: Laminar flow in a channel expansion , 1984 .
[23] D. Rovas,et al. A blackbox reduced-basis output bound method for noncoercive linear problems , 2002 .
[24] Alessandro Alla,et al. Nonlinear Model Order Reduction via Dynamic Mode Decomposition , 2016, SIAM J. Sci. Comput..
[25] Zhu Wang,et al. Approximate Deconvolution Reduced Order Modeling , 2015, 1510.02726.
[26] George Em Karniadakis,et al. Dynamics and low-dimensionality of a turbulent near wake , 2000, Journal of Fluid Mechanics.
[27] B. R. Noack,et al. A hierarchy of low-dimensional models for the transient and post-transient cylinder wake , 2003, Journal of Fluid Mechanics.
[28] A. Debussche,et al. IC S THE NONLINEAR GALERKIN METHOD : A MULTI-SCALE METHOD APPLIED TO THE SIMULATION OF HOMOGENEOUS TURBULENT FLOWS , 2022 .
[29] P. Sagaut. BOOK REVIEW: Large Eddy Simulation for Incompressible Flows. An Introduction , 2001 .
[30] Gianluigi Rozza,et al. Advances in Reduced order modelling for CFD: vortex shedding around a circular cylinder using a POD-Galerkin method , 2017 .
[31] I. Kevrekidis,et al. Low‐dimensional models for complex geometry flows: Application to grooved channels and circular cylinders , 1991 .
[32] Gianluigi Rozza,et al. Reduced basis approximation and a posteriori error estimation for Stokes flows in parametrized geometries: roles of the inf-sup stability constants , 2013, Numerische Mathematik.
[33] Nadine Aubry,et al. The dynamics of coherent structures in the wall region of a turbulent boundary layer , 1988, Journal of Fluid Mechanics.
[34] P. Schmid,et al. Dynamic mode decomposition of numerical and experimental data , 2008, Journal of Fluid Mechanics.
[35] Arthur Veldman,et al. Proper orthogonal decomposition and low-dimensional models for driven cavity flows , 1998 .
[36] Stefan Volkwein,et al. Galerkin proper orthogonal decomposition methods for parameter dependent elliptic systems , 2007 .
[37] S. Volkwein,et al. MODEL REDUCTION USING PROPER ORTHOGONAL DECOMPOSITION , 2008 .
[38] B. Bouriquet,et al. Stabilization of (G)EIM in presence of measurement noise: application to nuclear reactor physics , 2016, 1611.02219.
[39] P. Holmes,et al. The Proper Orthogonal Decomposition in the Analysis of Turbulent Flows , 1993 .
[40] C. Canuto. Spectral methods in fluid dynamics , 1991 .
[41] Bernard Haasdonk,et al. Convergence Rates of the POD–Greedy Method , 2013 .
[42] Matthew F. Barone,et al. Stable Galerkin reduced order models for linearized compressible flow , 2009, J. Comput. Phys..
[43] P. Schmid,et al. Applications of the dynamic mode decomposition , 2011 .
[44] Stefan Volkwein,et al. Galerkin Proper Orthogonal Decomposition Methods for a General Equation in Fluid Dynamics , 2002, SIAM J. Numer. Anal..
[45] R. Murray,et al. Model reduction for compressible flows using POD and Galerkin projection , 2004 .
[46] Charles-Henri Bruneau,et al. Low-order modelling of laminar flow regimes past a confined square cylinder , 2004, Journal of Fluid Mechanics.
[47] B. Haasdonk,et al. REDUCED BASIS METHOD FOR FINITE VOLUME APPROXIMATIONS OF PARAMETRIZED LINEAR EVOLUTION EQUATIONS , 2008 .
[48] Traian Iliescu,et al. SUPG reduced order models for convection-dominated convection–diffusion–reaction equations , 2014 .
[49] Gianluigi Rozza,et al. Model Order Reduction in Fluid Dynamics: Challenges and Perspectives , 2014 .
[50] Edmond Chow,et al. A cross-validatory method for dependent data , 1994 .
[51] Harbir Antil,et al. Galerkin v. least-squares Petrov-Galerkin projection in nonlinear model reduction , 2015, J. Comput. Phys..
[52] I. Mezić,et al. Spectral analysis of nonlinear flows , 2009, Journal of Fluid Mechanics.
[53] Lars Davidson,et al. Low-Reynolds-number flow around a square cylinder at incidence: study of blockage, onset of vortex shedding and outlet boundary condition , 1998 .
[54] Y. Maday,et al. A Two-grid Finite-element/reduced Basis Scheme for the Approximation of the Solution of Parameter Dependent P.d.e , 2009 .
[55] P. Moin,et al. DIRECT NUMERICAL SIMULATION: A Tool in Turbulence Research , 1998 .
[56] D. Rempfer,et al. On Low-Dimensional Galerkin Models for Fluid Flow , 2000 .
[57] Gianluigi Rozza,et al. Reduced-order semi-implicit schemes for fluid-structure interaction problems , 2017, 1711.10829.
[58] Alfio Quarteroni,et al. An online intrinsic stabilization strategy for the reduced basis approximation of parametrized advection-dominated problems , 2016 .
[59] Traian Iliescu,et al. Proper orthogonal decomposition closure models for fluid flows: Burgers equation , 2013, 1308.3276.
[60] Yvon Maday,et al. A reduced basis element method for the steady stokes problem , 2006 .
[61] G. Karniadakis,et al. A spectral viscosity method for correcting the long-term behavior of POD models , 2004 .
[62] Bernd R. Noack,et al. The need for a pressure-term representation in empirical Galerkin models of incompressible shear flows , 2005, Journal of Fluid Mechanics.
[63] Ian T. Jolliffe,et al. Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.
[64] David Amsallem,et al. An adaptive and efficient greedy procedure for the optimal training of parametric reduced‐order models , 2015 .
[65] A. Quarteroni,et al. Reduced Basis Techniques For Nonlinear Conservation Laws , 2015 .
[66] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[67] George Em Karniadakis,et al. A low-dimensional model for simulating three-dimensional cylinder flow , 2002, Journal of Fluid Mechanics.
[68] Karsten Urban,et al. A new error bound for reduced basis approximation of parabolic partial differential equations , 2012 .
[69] Benjamin Stamm,et al. Model Order Reduction for Problems with Large Convection Effects , 2018, Computational Methods in Applied Sciences.
[70] Jeffrey S. Racine,et al. Consistent cross-validatory model-selection for dependent data: hv-block cross-validation , 2000 .
[71] G. Rozza,et al. On the stability of the reduced basis method for Stokes equations in parametrized domains , 2007 .
[72] Charbel Farhat,et al. The GNAT method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows , 2012, J. Comput. Phys..
[73] Steven A. Orszag,et al. Order and disorder in two- and three-dimensional Bénard convection , 1984, Journal of Fluid Mechanics.
[74] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[75] G. Rozza,et al. POD-Galerkin method for finite volume approximation of Navier–Stokes and RANS equations , 2016 .
[76] Eusebio Valero,et al. Local POD Plus Galerkin Projection in the Unsteady Lid-Driven Cavity Problem , 2011, SIAM J. Sci. Comput..
[77] Bernd R. Noack,et al. Identification strategies for model-based control , 2013 .
[78] Christian Himpe,et al. Hierarchical Approximate Proper Orthogonal Decomposition , 2016, SIAM J. Sci. Comput..
[79] Maciej Balajewicz,et al. A New Approach to Model Order Reduction of the Navier-Stokes Equations , 2012 .
[80] Masayuki Yano,et al. A Space-Time Petrov-Galerkin Certified Reduced Basis Method: Application to the Boussinesq Equations , 2014, SIAM J. Sci. Comput..
[81] Erwan Liberge,et al. A minimum residual projection to build coupled velocity-pressure POD-ROM for incompressible Navier-Stokes equations , 2015, Commun. Nonlinear Sci. Numer. Simul..