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All issues ESAIM: M2AN, 42 2 (2008) 277-302 Article references

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Frontiers in Applied Mathematics and Statistics 4 (2018)
DOI: 10.3389/fams.2018.00018
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Accelerating optimization and uncertainty quantification of nonlinear SMB chromatography using reduced-order models

Yongjin Zhang, Lihong Feng, Andreas Seidel-Morgenstern and Peter Benner
Computers & Chemical Engineering 96 237 (2017)
DOI: 10.1016/j.compchemeng.2016.09.017
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The rocky road to extended simulation frameworks covering uncertainty, inversion, optimization and control

Daniel Wirtz and Wolfgang Nowak
Environmental Modelling & Software 93 180 (2017)
DOI: 10.1016/j.envsoft.2016.10.003
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An Efficient Output Error Bound for Model Order Reduction of Parametrized Evolution Equations

Yongjin Zhang, Lihong Feng, Suzhou Li and Peter Benner
IFAC-PapersOnLine 48 (1) 9 (2015)
DOI: 10.1016/j.ifacol.2015.05.096
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An Efficient Output Error Estimation for Model Order Reduction of Parametrized Evolution Equations

Yongjin Zhang, Lihong Feng, Suzhou Li and Peter Benner
SIAM Journal on Scientific Computing 37 (6) B910 (2015)
DOI: 10.1137/140998603
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An empirical interpolation approach to reduced basis approximations for variational inequalities

E. Bader, Z. Zhang and K. Veroy
Mathematical and Computer Modelling of Dynamical Systems 22 (4) 345 (2016)
DOI: 10.1080/13873954.2016.1198388
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A-posteriori error analysis for lithium-ion concentrations in batteries utilizing the reduced-basis method

L. Iapichino, S. Volkwein and A. Wesche
Mathematical and Computer Modelling of Dynamical Systems 22 (4) 362 (2016)
DOI: 10.1080/13873954.2016.1198387
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On the Application of Reduced Basis Methods to Bifurcation Problems in Incompressible Fluid Dynamics

Giuseppe Pitton and Gianluigi Rozza
Journal of Scientific Computing (2017)
DOI: 10.1007/s10915-017-0419-6
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Isogeometric analysis-based reduced order modelling for incompressible linear viscous flows in parametrized shapes

Filippo Salmoiraghi, Francesco Ballarin, Luca Heltai and Gianluigi Rozza
Advanced Modeling and Simulation in Engineering Sciences 3 (1) (2016)
DOI: 10.1186/s40323-016-0076-6
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WITHDRAWN: An algorithm for the study of parameter dependence applied to hyperbolic systems

Gianni Arioli
Applied Mathematical Modelling (2016)
DOI: 10.1016/j.apm.2016.08.012
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Model reduction using L 1 -norm minimization as an application to nonlinear hyperbolic problems

R. Abgrall and R. Crisovan
International Journal for Numerical Methods in Fluids 87 (12) 628 (2018)
DOI: 10.1002/fld.4507
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Accurate and efficient evaluation of failure probability for partial different equations with random input data

Peng Chen and Alfio Quarteroni
Computer Methods in Applied Mechanics and Engineering 267 233 (2013)
DOI: 10.1016/j.cma.2013.08.016
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Optimal Local Approximation Spaces for Component-Based Static Condensation Procedures

Kathrin Smetana and Anthony T. Patera
SIAM Journal on Scientific Computing 38 (5) A3318 (2016)
DOI: 10.1137/15M1009603
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Model Reduction for Transport-Dominated Problems via Online Adaptive Bases and Adaptive Sampling

Benjamin Peherstorfer
SIAM Journal on Scientific Computing 42 (5) A2803 (2020)
DOI: 10.1137/19M1257275
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CERTIFIED REDUCED BASIS METHODS FOR NONAFFINE LINEAR TIME-VARYING AND NONLINEAR PARABOLIC PARTIAL DIFFERENTIAL EQUATIONS

MARTIN A. GREPL
Mathematical Models and Methods in Applied Sciences 22 (03) 1150015 (2012)
DOI: 10.1142/S0218202511500151
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A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems

Peter Benner, Serkan Gugercin and Karen Willcox
SIAM Review 57 (4) 483 (2015)
DOI: 10.1137/130932715
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Reduced Basis Approximation for Nonlinear Parametrized Evolution Equations based on Empirical Operator Interpolation

Martin Drohmann, Bernard Haasdonk and Mario Ohlberger
SIAM Journal on Scientific Computing 34 (2) A937 (2012)
DOI: 10.1137/10081157X
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A Reduced Basis Method for Parametrized Variational Inequalities

B. Haasdonk, J. Salomon and B. Wohlmuth
SIAM Journal on Numerical Analysis 50 (5) 2656 (2012)
DOI: 10.1137/110835372
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Reduced Basis Collocation Methods for Partial Differential Equations with Random Coefficients

Howard C. Elman and Qifeng Liao
SIAM/ASA Journal on Uncertainty Quantification 1 (1) 192 (2013)
DOI: 10.1137/120881841
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A Posteriori Error Estimation for DEIM Reduced Nonlinear Dynamical Systems

D. Wirtz, D. C. Sorensen and B. Haasdonk
SIAM Journal on Scientific Computing 36 (2) A311 (2014)
DOI: 10.1137/120899042
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A reduced basis Kalman filter for parametrized partial differential equations

Markus Dihlmann and Bernard Haasdonk
ESAIM: Control, Optimisation and Calculus of Variations 22 (3) 625 (2016)
DOI: 10.1051/cocv/2015019
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Lyapunov-Based Error Bounds for the Reduced-Basis Method

Robert O’Connor
IFAC-PapersOnLine 49 (8) 1 (2016)
DOI: 10.1016/j.ifacol.2016.07.409
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Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD–Galerkin method and a vascular shape parametrization

Francesco Ballarin, Elena Faggiano, Sonia Ippolito, et al.
Journal of Computational Physics 315 609 (2016)
DOI: 10.1016/j.jcp.2016.03.065
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A fast, certified and “tuning free” two-field reduced basis method for the metamodelling of affinely-parametrised elasticity problems

K.C. Hoang, P. Kerfriden and S.P.A. Bordas
Computer Methods in Applied Mechanics and Engineering 298 121 (2016)
DOI: 10.1016/j.cma.2015.08.016
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Failure Probability Estimation of Linear Time Varying Systems by Progressive Refinement of Reduced Order Models

Agnimitra Dasgupta and Debraj Ghosh
SIAM/ASA Journal on Uncertainty Quantification 7 (3) 1007 (2019)
DOI: 10.1137/18M1165840
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A certified natural-norm successive constraint method for parametric inf–sup lower bounds

Yanlai Chen
Applied Numerical Mathematics 99 98 (2016)
DOI: 10.1016/j.apnum.2015.09.003
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Finite Volumes for Complex Applications VI Problems & Perspectives

Martin Drohmann, Bernard Haasdonk and Mario Ohlberger
Springer Proceedings in Mathematics, Finite Volumes for Complex Applications VI Problems & Perspectives 4 369 (2011)
DOI: 10.1007/978-3-642-20671-9_39
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Recent Advances in Computational Engineering

Christopher Spannring, Sebastian Ullmann and Jens Lang
Lecture Notes in Computational Science and Engineering, Recent Advances in Computational Engineering 124 145 (2018)
DOI: 10.1007/978-3-319-93891-2_9
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Projection-based model reduction with dynamically transformed modes

Felix Black, Philipp Schulze and Benjamin Unger
ESAIM: Mathematical Modelling and Numerical Analysis 54 (6) 2011 (2020)
DOI: 10.1051/m2an/2020046
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Accelerating CFD solver computation time with reduced‐order modeling in a multigrid environment

Niklas Karcher and Marcel Wallraff
International Journal for Numerical Methods in Fluids 93 (2) 462 (2021)
DOI: 10.1002/fld.4892
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A Flow feature detection framework for large-scale computational data based on incremental proper orthogonal decomposition and data mining

Eric D. Robertson, Yi Wang, Kapil Pant, Matthew J. Grismer and José A. Camberos
International Journal of Computational Fluid Dynamics 32 (6-7) 261 (2018)
DOI: 10.1080/10618562.2018.1508657
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A Reduced Basis Approach for Modeling the Movement of Nuclear Reactor Control Rods

Alberto Sartori, Antonio Cammi, Lelio Luzzi and Gianluigi Rozza
Journal of Nuclear Engineering and Radiation Science 2 (2) 021019 (2016)
DOI: 10.1115/1.4031945
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Reduced order modeling of random linear dynamical systems based on a new a posteriori error bound

Md. Nurtaj Hossain and Debraj Ghosh
International Journal for Numerical Methods in Engineering 116 (12-13) 741 (2018)
DOI: 10.1002/nme.5942
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Adaptive basis construction and improved error estimation for parametric nonlinear dynamical systems

Sridhar Chellappa, Lihong Feng and Peter Benner
International Journal for Numerical Methods in Engineering 121 (23) 5320 (2020)
DOI: 10.1002/nme.6462
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Solving Parameter-Dependent Lyapunov Equations Using the Reduced Basis Method with Application to Parametric Model Order Reduction

Nguyen Thanh Son and Tatjana Stykel
SIAM Journal on Matrix Analysis and Applications 38 (2) 478 (2017)
DOI: 10.1137/15M1027097
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Computing Reduced Order Models via Inner-Outer Krylov Recycling in Diffuse Optical Tomography

Meghan O'Connell, Misha E. Kilmer, Eric de Sturler and Serkan Gugercin
SIAM Journal on Scientific Computing 39 (2) B272 (2017)
DOI: 10.1137/16M1062880
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Reduced Basis Methods for Uncertainty Quantification

Peng Chen, Alfio Quarteroni and Gianluigi Rozza
SIAM/ASA Journal on Uncertainty Quantification 5 (1) 813 (2017)
DOI: 10.1137/151004550
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Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization

Benjamin Peherstorfer, Karen Willcox and Max Gunzburger
SIAM Review 60 (3) 550 (2018)
DOI: 10.1137/16M1082469
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Dynamical Model Reduction Method for Solving Parameter-Dependent Dynamical Systems

Marie Billaud-Friess and Anthony Nouy
SIAM Journal on Scientific Computing 39 (4) A1766 (2017)
DOI: 10.1137/16M1071493
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Interpolation of Functions with Parameter Dependent Jumps by Transformed Snapshots

G. Welper
SIAM Journal on Scientific Computing 39 (4) A1225 (2017)
DOI: 10.1137/16M1059904
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Data-Driven Reduced Model Construction with Time-Domain Loewner Models

Benjamin Peherstorfer, Serkan Gugercin and Karen Willcox
SIAM Journal on Scientific Computing 39 (5) A2152 (2017)
DOI: 10.1137/16M1094750
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Model order reduction for parametrized nonlinear hyperbolic problems as an application to uncertainty quantification

R. Crisovan, D. Torlo, R. Abgrall and S. Tokareva
Journal of Computational and Applied Mathematics 348 466 (2019)
DOI: 10.1016/j.cam.2018.09.018
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Greedy Nonintrusive Reduced Order Model for Fluid Dynamics

Wang Chen, Jan S. Hesthaven, Bai Junqiang, et al.
AIAA Journal 56 (12) 4927 (2018)
DOI: 10.2514/1.J056161
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Finite volume POD-Galerkin stabilised reduced order methods for the parametrised incompressible Navier–Stokes equations

Giovanni Stabile and Gianluigi Rozza
Computers & Fluids 173 273 (2018)
DOI: 10.1016/j.compfluid.2018.01.035
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Data-driven reduced order modeling for time-dependent problems

Mengwu Guo and Jan S. Hesthaven
Computer Methods in Applied Mechanics and Engineering 345 75 (2019)
DOI: 10.1016/j.cma.2018.10.029
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Reduced Basis Approximation and a Posteriori Error Estimation for Affinely Parametrized Elliptic Coercive Partial Differential Equations

G. Rozza, D. B. P. Huynh and A. T. Patera
Archives of Computational Methods in Engineering 15 (3) 229 (2008)
DOI: 10.1007/s11831-008-9019-9
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Reduced basis approximation and a posteriori error estimation for the time-dependent viscous Burgers’ equation

Ngoc-Cuong Nguyen, Gianluigi Rozza and Anthony T. Patera
Calcolo 46 (3) 157 (2009)
DOI: 10.1007/s10092-009-0005-x
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Nonintrusive proper generalised decomposition for parametrised incompressible flow problems in OpenFOAM

Vasileios Tsiolakis, Matteo Giacomini, Ruben Sevilla, Carsten Othmer and Antonio Huerta
Computer Physics Communications 249 107013 (2020)
DOI: 10.1016/j.cpc.2019.107013
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A generic interface for parallel and adaptive discretization schemes: abstraction principles and the Dune-Fem module

Andreas Dedner, Robert Klöfkorn, Martin Nolte and Mario Ohlberger
Computing 90 (3-4) 165 (2010)
DOI: 10.1007/s00607-010-0110-3
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Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem

Qian Wang, Jan S. Hesthaven and Deep Ray
Journal of Computational Physics 384 289 (2019)
DOI: 10.1016/j.jcp.2019.01.031
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POD-Galerkin method for finite volume approximation of Navier–Stokes and RANS equations

Stefano Lorenzi, Antonio Cammi, Lelio Luzzi and Gianluigi Rozza
Computer Methods in Applied Mechanics and Engineering 311 151 (2016)
DOI: 10.1016/j.cma.2016.08.006
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Spectral and High Order Methods for Partial Differential Equations

Jens L. Eftang, Anthony T. Patera and Einar M. Rønquist
Lecture Notes in Computational Science and Engineering, Spectral and High Order Methods for Partial Differential Equations 76 179 (2011)
DOI: 10.1007/978-3-642-15337-2_15
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Reduced Basis Approaches in Time-Dependent Non-Coercive Settings for Modelling the Movement of Nuclear Reactor Control Rods

Alberto Sartori, Antonio Cammi, Lelio Luzzi and Gianluigi Rozza
Communications in Computational Physics 20 (1) 23 (2016)
DOI: 10.4208/cicp.120914.021115a
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Randomized Residual-Based Error Estimators for Parametrized Equations

Kathrin Smetana, Olivier Zahm and Anthony T. Patera
SIAM Journal on Scientific Computing 41 (2) A900 (2019)
DOI: 10.1137/18M120364X
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A multi-physics reduced order model for the analysis of Lead Fast Reactor single channel

Alberto Sartori, Antonio Cammi, Lelio Luzzi and Gianluigi Rozza
Annals of Nuclear Energy 87 198 (2016)
DOI: 10.1016/j.anucene.2015.09.002
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POD-DEIM reduction of computational EMG models

M. Mordhorst, T. Strecker, D. Wirtz, T. Heidlauf and O. Röhrle
Journal of Computational Science 19 86 (2017)
DOI: 10.1016/j.jocs.2017.01.009
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Advances in DUNE

Martin Drohmann, Bernard Haasdonk, Sven Kaulmann and Mario Ohlberger
Advances in DUNE 77 (2012)
DOI: 10.1007/978-3-642-28589-9_6
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The reduced basis method applied to transport equations of a lithium-ion battery

Stefan Volkwein, Prof. Oszkár Bíró, Prof. David A. Lowther and Andrea Wesche
COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 32 (5) 1760 (2013)
DOI: 10.1108/COMPEL-04-2013-0115
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Progress in Industrial Mathematics at ECMI 2018

Markus Rein, Jan Mohring, Tobias Damm and Axel Klar
Mathematics in Industry, Progress in Industrial Mathematics at ECMI 2018 30 405 (2019)
DOI: 10.1007/978-3-030-27550-1_51
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DEIM reduced order model constructed by hybrid snapshot simulation

Feng Bai and Yi Wang
SN Applied Sciences 2 (12) (2020)
DOI: 10.1007/s42452-020-03958-7
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Kolmogorov n-widths for linear dynamical systems

Benjamin Unger and Serkan Gugercin
Advances in Computational Mathematics 45 (5-6) 2273 (2019)
DOI: 10.1007/s10444-019-09701-0
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Error estimation in reduced basis method for systems with time-varying and nonlinear boundary conditions

M.H. Abbasi, L. Iapichino, B. Besselink, W.H.A. Schilders and N. van de Wouw
Computer Methods in Applied Mechanics and Engineering 360 112688 (2020)
DOI: 10.1016/j.cma.2019.112688
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A certified model reduction approach for robust parameter optimization with PDE constraints

Alessandro Alla, Michael Hinze, Philip Kolvenbach, Oliver Lass and Stefan Ulbrich
Advances in Computational Mathematics 45 (3) 1221 (2019)
DOI: 10.1007/s10444-018-9653-1
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A Reduced Generalized Multiscale Basis Method for Parametrized Groundwater Flow Problems in Heterogeneous Porous Media

Xinguang He, Qiuqi Li and Lijian Jiang
Water Resources Research 55 (3) 2390 (2019)
DOI: 10.1029/2018WR023954
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An Artificial Compression Reduced Order Model

Victor DeCaria, Traian Iliescu, William Layton, Michael McLaughlin and Michael Schneier
SIAM Journal on Numerical Analysis 58 (1) 565 (2020)
DOI: 10.1137/19M1246444
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Reduced Collocation Method for Time-Dependent Parametrized Partial Differential Equations

Rezvan Ghaffari and Farideh Ghoreishi
Bulletin of the Iranian Mathematical Society 45 (5) 1487 (2019)
DOI: 10.1007/s41980-019-00210-w
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Efficient model reduction of parametrized systems by matrix discrete empirical interpolation

Federico Negri, Andrea Manzoni and David Amsallem
Journal of Computational Physics 303 431 (2015)
DOI: 10.1016/j.jcp.2015.09.046
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Reduced basis method for managed pressure drilling based on a model with local nonlinearities

Mohammad Hossein Abbasi, Laura Iapichino, Sajad Naderi Lordejani, Wil Schilders and Nathan Wouw
International Journal for Numerical Methods in Engineering 121 (23) 5178 (2020)
DOI: 10.1002/nme.6362
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Efficient geometrical parametrization for finite‐volume‐based reduced order methods

Giovanni Stabile, Matteo Zancanaro and Gianluigi Rozza
International Journal for Numerical Methods in Engineering 121 (12) 2655 (2020)
DOI: 10.1002/nme.6324
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Optimal control of district heating networks using a reduced order model

Markus Rein, Jan Mohring, Tobias Damm and Axel Klar
Optimal Control Applications and Methods 41 (4) 1352 (2020)
DOI: 10.1002/oca.2610
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Adaptive reduced order modeling for nonlinear dynamical systems through a new a posteriori error estimator: Application to uncertainty quantification

Md. Nurtaj Hossain and Debraj Ghosh
International Journal for Numerical Methods in Engineering 121 (15) 3417 (2020)
DOI: 10.1002/nme.6365
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Certified Offline-Free Reduced Basis (COFRB) Methods for Stochastic Differential Equations Driven by Arbitrary Types of Noise

Yong Liu, Tianheng Chen, Yanlai Chen and Chi-Wang Shu
Journal of Scientific Computing 81 (3) 1210 (2019)
DOI: 10.1007/s10915-019-00976-5
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A reduced basis method for the wave equation

Silke Glas, Anthony T. Patera and Karsten Urban
International Journal of Computational Fluid Dynamics 34 (2) 139 (2020)
DOI: 10.1080/10618562.2019.1686486
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Data-driven POD-Galerkin reduced order model for turbulent flows

Saddam Hijazi, Giovanni Stabile, Andrea Mola and Gianluigi Rozza
Journal of Computational Physics 416 109513 (2020)
DOI: 10.1016/j.jcp.2020.109513
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Well‐scaled, a‐posteriori error estimation for model order reduction of large second‐order mechanical systems

Dennis Grunert, Jörg Fehr and Bernard Haasdonk
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik 100 (8) e201900186 (2020)
DOI: 10.1002/zamm.201900186
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Gradient-based constrained optimization using a database of linear reduced-order models

Youngsoo Choi, Gabriele Boncoraglio, Spenser Anderson, David Amsallem and Charbel Farhat
Journal of Computational Physics 423 109787 (2020)
DOI: 10.1016/j.jcp.2020.109787
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Application of adaptive ANOVA and reduced basis methods to the stochastic Stokes-Brinkman problem

Kevin Williamson, Heyrim Cho and Bedřich Sousedík
Computational Geosciences 25 (3) 1191 (2021)
DOI: 10.1007/s10596-021-10048-z
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Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

Qifeng Liao and Guang Lin
Journal of Computational Physics 317 148 (2016)
DOI: 10.1016/j.jcp.2016.04.029
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Conservative model reduction for finite-volume models

Kevin Carlberg, Youngsoo Choi and Syuzanna Sargsyan
Journal of Computational Physics 371 280 (2018)
DOI: 10.1016/j.jcp.2018.05.019
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A stabilized POD model for turbulent flows over a range of Reynolds numbers: Optimal parameter sampling and constrained projection

Lambert Fick, Yvon Maday, Anthony T. Patera and Tommaso Taddei
Journal of Computational Physics 371 214 (2018)
DOI: 10.1016/j.jcp.2018.05.027
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Error estimates for model order reduction of Burgers’ equation

M.H. Abbasi, L. Iapichino, B. Besselink, W. Schilders and N. van de Wouw
IFAC-PapersOnLine 53 (2) 5609 (2020)
DOI: 10.1016/j.ifacol.2020.12.1575
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Parametric domain decomposition for accurate reduced order models: Applications of MP-LROM methodology

Razvan Stefanescu, Azam Moosavi and Adrian Sandu
Journal of Computational and Applied Mathematics 340 629 (2018)
DOI: 10.1016/j.cam.2017.11.018
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A multiscale method for model order reduction in PDE parameter estimation

Samy Wu Fung and Lars Ruthotto
Journal of Computational and Applied Mathematics 350 19 (2019)
DOI: 10.1016/j.cam.2018.09.043
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Probabilistic error estimation for non-intrusive reduced models learned from data of systems governed by linear parabolic partial differential equations

Wayne Isaac Tan Uy and Benjamin Peherstorfer
ESAIM: Mathematical Modelling and Numerical Analysis 55 (3) 735 (2021)
DOI: 10.1051/m2an/2021010
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The DGDD method for reduced-order modeling of conservation laws

Sébastien Riffaud, Michel Bergmann, Charbel Farhat, Sebastian Grimberg and Angelo Iollo
Journal of Computational Physics 437 110336 (2021)
DOI: 10.1016/j.jcp.2021.110336
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Model order reduction of hyperbolic systems focusing on district heating networks

Markus Rein, Jan Mohring, Tobias Damm and Axel Klar
Journal of the Franklin Institute (2021)
DOI: 10.1016/j.jfranklin.2021.04.002
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L1-Based Reduced Over Collocation and Hyper Reduction for Steady State and Time-Dependent Nonlinear Equations

Yanlai Chen, Lijie Ji, Akil Narayan and Zhenli Xu
Journal of Scientific Computing 87 (1) (2021)
DOI: 10.1007/s10915-021-01416-z
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Reduced order models for the incompressible Navier‐Stokes equations on collocated grids using a ‘discretize‐then‐project’ approach

Sabrina Kelbij Star, Benjamin Sanderse, Giovanni Stabile, Gianluigi Rozza and Joris Degroote
International Journal for Numerical Methods in Fluids (2021)
DOI: 10.1002/fld.4994
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Limited‐memory adaptive snapshot selection for proper orthogonal decomposition

Geoffrey M. Oxberry, Tanya Kostova‐Vassilevska, William Arrighi and Kyle Chand
International Journal for Numerical Methods in Engineering 109 (2) 198 (2017)
DOI: 10.1002/nme.5283
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N. H. Nguyen, T. H. H. Le and B. C. Khoo
105 (2015)
DOI: 10.1109/ATC.2015.7388300
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Mesh-Based and Meshfree Reduced Order Phase-Field Models for Brittle Fracture: One Dimensional Problems

Ngoc-Hien Nguyen, Vinh Phu Nguyen, Jian-Ying Wu, Thi-Hong-Hieu Le and Yan Ding
Materials 12 (11) 1858 (2019)
DOI: 10.3390/ma12111858
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Chen Wang, Junqiang Bai and Jan S. Hesthaven
(2017)
DOI: 10.2514/6.2017-2348
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Pawan Goyal, Mian Ilyas Ahmad and Peter Benner
1177 (2015)
DOI: 10.1109/ECC.2015.7330699
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Building a certified reduced basis for coupled thermo-hydro-mechanical systems with goal-oriented error estimation

Ygee Larion, Sergio Zlotnik, Thierry J. Massart and Pedro Díez
Computational Mechanics 66 (3) 559 (2020)
DOI: 10.1007/s00466-020-01865-7
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