EDP Sciences logo
Subscriber Authentication Point
Search
Menu
All issues ESAIM: M2AN, 42 2 (2008) 277-302 Article references

Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

Hybrid data-driven closure strategies for reduced order modeling

Anna Ivagnes, Giovanni Stabile, Andrea Mola, Traian Iliescu and Gianluigi Rozza
Applied Mathematics and Computation 448 127920 (2023)
https://doi.org/10.1016/j.amc.2023.127920

No pressure? Energy-consistent ROMs for the incompressible Navier-Stokes equations with time-dependent boundary conditions

H. Rosenberger and B. Sanderse
Journal of Computational Physics 491 112405 (2023)
https://doi.org/10.1016/j.jcp.2023.112405

An h-Adaptive Poly-Sinc-Based Local Discontinuous Galerkin Method for Elliptic Partial Differential Equations

Omar A. Khalil and Gerd Baumann
Axioms 12 (3) 227 (2023)
https://doi.org/10.3390/axioms12030227

Optimal control of parameterized stationary Maxwell's system: Reduced basis, convergence analysis, and a posteriori error estimates

Mathematical Control and Related Fields 13 (1) 431 (2023)
https://doi.org/10.3934/mcrf.2022003

Reduced order modeling for parametrized generalized Newtonian fluid flows

R. Reyes, O. Ruz, C. Bayona-Roa, E. Castillo and A. Tello
Journal of Computational Physics 484 112086 (2023)
https://doi.org/10.1016/j.jcp.2023.112086

Multi‐fidelity error estimation accelerates greedy model reduction of complex dynamical systems

Lihong Feng, Luigi Lombardi, Giulio Antonini and Peter Benner
International Journal for Numerical Methods in Engineering 124 (23) 5312 (2023)
https://doi.org/10.1002/nme.7348

A reduced basis ensemble Kalman method

Francesco A. B. Silva, Cecilia Pagliantini, Martin Grepl and Karen Veroy
GEM - International Journal on Geomathematics 14 (1) (2023)
https://doi.org/10.1007/s13137-023-00235-8

A New Certified Hierarchical and Adaptive RB-ML-ROM Surrogate Model for Parametrized PDEs

Bernard Haasdonk, Hendrik Kleikamp, Mario Ohlberger, Felix Schindler and Tizian Wenzel
SIAM Journal on Scientific Computing 45 (3) A1039 (2023)
https://doi.org/10.1137/22M1493318

Model order reduction for deforming domain problems in a time‐continuous space‐time setting

Fabian Key, Max von Danwitz, Francesco Ballarin and Gianluigi Rozza
International Journal for Numerical Methods in Engineering 124 (23) 5125 (2023)
https://doi.org/10.1002/nme.7342

A reduced order model for the finite element approximation of eigenvalue problems

Fleurianne Bertrand, Daniele Boffi and Abdul Halim
Computer Methods in Applied Mechanics and Engineering 404 115696 (2023)
https://doi.org/10.1016/j.cma.2022.115696

Numerical Analysis of Transient State Heat Transfer by Spectral Method Based on POD Reduced-Order Extrapolation Algorithm

Zhenggang Ba and Ye Wang
Applied Sciences 13 (11) 6665 (2023)
https://doi.org/10.3390/app13116665

A reduced order modeling approach with Petrov–Galerkin projection based on hybrid snapshot simulation in Semilinear-PDEs

Feng Bai
Journal of Computational Science 67 101969 (2023)
https://doi.org/10.1016/j.jocs.2023.101969

Model-order reduction for hyperbolic relaxation systems

Sara Grundel and Michael Herty
International Journal of Nonlinear Sciences and Numerical Simulation 24 (7) 2763 (2023)
https://doi.org/10.1515/ijnsns-2021-0192

Adaptive piecewise Poly-Sinc methods for function approximation

Omar A. Khalil, Hany A. El-Sharkawy, Maha Youssef and Gerd Baumann
Applied Numerical Mathematics 186 1 (2023)
https://doi.org/10.1016/j.apnum.2022.12.016

Parametric energy conserving sampling and weighting for the thermal analysis of Selective Laser Melting

Mohamed Amine Ben Yahmed and Frank Naets
Computational Mechanics (2023)
https://doi.org/10.1007/s00466-023-02416-6

A projection‐based reduced‐order model for parametric quasi‐static nonlinear mechanics using an open‐source industrial code

Eki Agouzal, Jean‐Philippe Argaud, Michel Bergmann, Guilhem Ferté and Tommaso Taddei
International Journal for Numerical Methods in Engineering (2023)
https://doi.org/10.1002/nme.7385

Projection-Based Dimensional Reduction of Adaptively Refined Nonlinear Models

Clayton Little and Charbel Farhat
Communications on Applied Mathematics and Computation (2023)
https://doi.org/10.1007/s42967-023-00308-3

An Efficient Chorin–Temam Projection Proper Orthogonal Decomposition Based Reduced-Order Model for Nonstationary Stokes Equations

Xi Li, Yan Luo and Minfu Feng
Journal of Scientific Computing 93 (3) (2022)
https://doi.org/10.1007/s10915-022-02032-1

A modelling framework for efficient reduced order simulations of parametrised lithium-ion battery cells

M. Landstorfer, M. Ohlberger, S. Rave and M. Tacke
European Journal of Applied Mathematics 1 (2022)
https://doi.org/10.1017/S0956792522000353

Metamodeling techniques for CPU-intensive simulation-based design optimization: a survey

Hanane Khatouri, Tariq Benamara, Piotr Breitkopf and Jean Demange
Advanced Modeling and Simulation in Engineering Sciences 9 (1) (2022)
https://doi.org/10.1186/s40323-022-00214-y

Model order reduction for compressible flows solved using the discontinuous Galerkin methods

Jian Yu and Jan S. Hesthaven
Journal of Computational Physics 468 111452 (2022)
https://doi.org/10.1016/j.jcp.2022.111452

An adaptive projection‐based model reduction method for nonlinear mechanics with internal variables: Application to thermo‐hydro‐mechanical systems

Angelo Iollo, Giulia Sambataro and Tommaso Taddei
International Journal for Numerical Methods in Engineering 123 (12) 2894 (2022)
https://doi.org/10.1002/nme.6964

An Efficient QSC Approximation of Variable-Order Time-Fractional Mobile-Immobile Diffusion Equations with Variably Diffusive Coefficients

Jun Liu and Hongfei Fu
Journal of Scientific Computing 93 (2) (2022)
https://doi.org/10.1007/s10915-022-02007-2

MicroROM: An efficient and accurate reduced order method to solve many-query problems in micro-motility

Nicola Giuliani, Martin W. Hess, Antonio DeSimone and Gianluigi Rozza
ESAIM: Mathematical Modelling and Numerical Analysis 56 (4) 1151 (2022)
https://doi.org/10.1051/m2an/2022038

Adaptive Piecewise Poly-Sinc Methods for Ordinary Differential Equations

Omar Khalil, Hany El-Sharkawy, Maha Youssef and Gerd Baumann
Algorithms 15 (9) 320 (2022)
https://doi.org/10.3390/a15090320

Error analysis of a stable reduced order model based on the proper orthogonal decomposition method for the Allen–Cahn–Navier–Stokes system

Dongqin Chen, Qiuqi Li and Huailing Song
Computer Methods in Applied Mechanics and Engineering 401 115661 (2022)
https://doi.org/10.1016/j.cma.2022.115661

Goal-oriented model reduction for parametrized time-dependent nonlinear partial differential equations

Michael K. Sleeman and Masayuki Yano
Computer Methods in Applied Mechanics and Engineering 388 114206 (2022)
https://doi.org/10.1016/j.cma.2021.114206

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)
https://doi.org/10.1007/s10596-021-10048-z

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 93 (8) 2694 (2021)
https://doi.org/10.1002/fld.4994

An EIM-degradation free reduced basis method via over collocation and residual hyper reduction-based error estimation

Yanlai Chen, Sigal Gottlieb, Lijie Ji and Yvon Maday
Journal of Computational Physics 444 110545 (2021)
https://doi.org/10.1016/j.jcp.2021.110545

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)
https://doi.org/10.1051/m2an/2021010

Reducing sensors for transient heat transfer problems by means of variational data assimilation

Amina Benaceur
The SMAI journal of computational mathematics 7 1 (2021)
https://doi.org/10.5802/smai-jcm.68

A Reduced Order Model for a Stable Embedded Boundary Parametrized Cahn–Hilliard Phase-Field System Based on Cut Finite Elements

Efthymios N. Karatzas and Gianluigi Rozza
Journal of Scientific Computing 89 (1) (2021)
https://doi.org/10.1007/s10915-021-01623-8

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)
https://doi.org/10.1007/s10915-021-01416-z

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)
https://doi.org/10.1002/fld.4892

A space-time certified reduced basis method for quasilinear parabolic partial differential equations

Michael Hinze and Denis Korolev
Advances in Computational Mathematics 47 (3) (2021)
https://doi.org/10.1007/s10444-021-09860-z

Parametric Model Order Reduction of Guided Ultrasonic Wave Propagation in Fiber Metal Laminates with Damage

Nanda Kishore Bellam Muralidhar, Natalie Rauter, Andrey Mikhaylenko, Rolf Lammering and Dirk A. Lorenz
Modelling 2 (4) 591 (2021)
https://doi.org/10.3390/modelling2040031

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)
https://doi.org/10.1016/j.jcp.2021.110336

Greedy maximin distance sampling based model order reduction of prestressed and parametrized abdominal aortic aneurysms

Alexander Schein and Michael W. Gee
Advanced Modeling and Simulation in Engineering Sciences 8 (1) (2021)
https://doi.org/10.1186/s40323-021-00203-7

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 358 (15) 7674 (2021)
https://doi.org/10.1016/j.jfranklin.2021.04.002

A Monolithic and a Partitioned, Reduced Basis Method for Fluid–Structure Interaction Problems

Monica Nonino, Francesco Ballarin and Gianluigi Rozza
Fluids 6 (6) 229 (2021)
https://doi.org/10.3390/fluids6060229

Quantification of Uncertainty: Improving Efficiency and Technology

Saddam Hijazi, Giovanni Stabile, Andrea Mola and Gianluigi Rozza
Lecture Notes in Computational Science and Engineering, Quantification of Uncertainty: Improving Efficiency and Technology 137 217 (2020)
https://doi.org/10.1007/978-3-030-48721-8_10

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)
https://doi.org/10.1051/m2an/2020046

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)
https://doi.org/10.1016/j.jcp.2020.109513

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)
https://doi.org/10.1016/j.jcp.2020.109787

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 van de Wouw
International Journal for Numerical Methods in Engineering 121 (23) 5178 (2020)
https://doi.org/10.1002/nme.6362

Quantification of Uncertainty: Improving Efficiency and Technology

Fabrizio Garotta, Nicola Demo, Marco Tezzele, et al.
Lecture Notes in Computational Science and Engineering, Quantification of Uncertainty: Improving Efficiency and Technology 137 153 (2020)
https://doi.org/10.1007/978-3-030-48721-8_7

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)
https://doi.org/10.1002/nme.6324

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)
https://doi.org/10.1016/j.cpc.2019.107013

IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018

Efthymios N. Karatzas, Giovanni Stabile, Nabil Atallah, Guglielmo Scovazzi and Gianluigi Rozza
IUTAM Bookseries, IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018 36 111 (2020)
https://doi.org/10.1007/978-3-030-21013-7_8

IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018

Ashish Bhatt, Jörg Fehr, Dennis Grunert and Bernard Haasdonk
IUTAM Bookseries, IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018 36 95 (2020)
https://doi.org/10.1007/978-3-030-21013-7_7

Transformed Snapshot Interpolation with High Resolution Transforms

G. Welper
SIAM Journal on Scientific Computing 42 (4) A2037 (2020)
https://doi.org/10.1137/19M126356X

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)
https://doi.org/10.1137/19M1246444

Model Reduction for Transport-Dominated Problems via Online Adaptive Bases and Adaptive Sampling

Benjamin Peherstorfer
SIAM Journal on Scientific Computing 42 (5) A2803 (2020)
https://doi.org/10.1137/19M1257275

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)
https://doi.org/10.1002/nme.6365

Parametrized reduced order modeling for cracked solids

Konstantinos Agathos, Stéphane P. A. Bordas and Eleni Chatzi
International Journal for Numerical Methods in Engineering 121 (20) 4537 (2020)
https://doi.org/10.1002/nme.6447

Reduced order modeling approach for parametrized thermal-hydraulics problems: inclusion of the energy equation in the POD-FV-ROM method

Lorenzo Vergari, Antonio Cammi and Stefano Lorenzi
Progress in Nuclear Energy 118 103071 (2020)
https://doi.org/10.1016/j.pnucene.2019.103071

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)
https://doi.org/10.1007/s00466-020-01865-7

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)
https://doi.org/10.1016/j.cma.2019.112688

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)
https://doi.org/10.1002/oca.2610

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)
https://doi.org/10.1002/nme.6462

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) (2020)
https://doi.org/10.1002/zamm.201900186

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)
https://doi.org/10.1007/s10915-019-00976-5

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)
https://doi.org/10.1016/j.jcp.2019.01.031

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)
https://doi.org/10.1016/j.cam.2018.09.043

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)
https://doi.org/10.1137/18M120364X

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)
https://doi.org/10.1007/s41980-019-00210-w

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)
https://doi.org/10.1029/2018WR023954

Reduced Basis Method Applied to Eigenvalue Problems from Convection

Francisco Pla and Henar Herrero
International Journal of Bifurcation and Chaos 29 (03) 1950028 (2019)
https://doi.org/10.1142/S0218127419500287

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)
https://doi.org/10.1007/s10444-018-9653-1

Reduced Basis Methods for Fractional Laplace Equations via Extension

Harbir Antil, Yanlai Chen and Akil Narayan
SIAM Journal on Scientific Computing 41 (6) A3552 (2019)
https://doi.org/10.1137/18M1204802

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)
https://doi.org/10.1016/j.cam.2018.09.018

Adaptive non-intrusive reduced order modeling for compressible flows

Jian Yu, Chao Yan, Zhenhua Jiang, Wu Yuan and Shusheng Chen
Journal of Computational Physics 397 108855 (2019)
https://doi.org/10.1016/j.jcp.2019.07.053

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)
https://doi.org/10.1137/18M1165840

A New Error Estimator for Reduced-Order Modeling of Linear Parametric Systems

Lihong Feng and Peter Benner
IEEE Transactions on Microwave Theory and Techniques 67 (12) 4848 (2019)
https://doi.org/10.1109/TMTT.2019.2948858

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)
https://doi.org/10.3390/ma12111858

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)
https://doi.org/10.1016/j.cma.2018.10.029

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)
https://doi.org/10.1007/978-3-030-27550-1_51

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)
https://doi.org/10.1016/j.jcp.2018.05.027