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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) https://doi.org/10.1016/j.cma.2019.112688
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
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
Reduced order modeling approach for parametrized thermal-hydraulics problems: inclusion of the energy equation in the POD-FV-ROM method
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
Model Reduction for Transport-Dominated Problems via Online Adaptive Bases and Adaptive Sampling
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
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
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
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
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
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
Data-driven POD-Galerkin reduced order model for turbulent flows
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
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
Error estimates for model order reduction of Burgers’ equation
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
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
Transformed Snapshot Interpolation with High Resolution Transforms
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 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
An adaptive reduced basis ANOVA method for high-dimensional Bayesian inverse problems
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) https://doi.org/10.1002/nme.5942
Multivariate predictions of local reduced‐order‐model errors and dimensions
Azam Moosavi, Răzvan Ştefănescu and Adrian Sandu International Journal for Numerical Methods in Engineering 113(3) 512 (2018) https://doi.org/10.1002/nme.5624
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) https://doi.org/10.1007/978-3-319-93891-2_9
Empirical Gramian-based spatial basis functions for model reduction of nonlinear distributed parameter systems
Reduced basis approximation of large scale parametric algebraic Riccati equations
Andreas Schmidt and Bernard Haasdonk ESAIM: Control, Optimisation and Calculus of Variations 24(1) 129 (2018) https://doi.org/10.1051/cocv/2017011
Model reduction using L1‐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) https://doi.org/10.1002/fld.4507
Reduced-Order Modeling (ROM) for Simulation and Optimization
Zeger Bontinck, Oliver Lass, Oliver Rain and Sebastian Schöps Reduced-Order Modeling (ROM) for Simulation and Optimization 121 (2018) https://doi.org/10.1007/978-3-319-75319-5_6
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) https://doi.org/10.1080/10618562.2018.1508657
A stabilized POD model for turbulent flows over a range of Reynolds numbers: Optimal parameter sampling and constrained projection
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) https://doi.org/10.1137/16M1062880
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) https://doi.org/10.1137/16M1094750
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) https://doi.org/10.1002/nme.5283
Interpolation of Functions with Parameter Dependent Jumps by Transformed Snapshots
Numerical Mathematics and Advanced Applications ENUMATH 2015
Laura Iapichino, Stefan Trenz and Stefan Volkwein Lecture Notes in Computational Science and Engineering, Numerical Mathematics and Advanced Applications ENUMATH 2015 112 389 (2016) https://doi.org/10.1007/978-3-319-39929-4_37
Numerical Mathematics and Advanced Applications ENUMATH 2015
Mario Ohlberger, Stephan Rave and Felix Schindler Lecture Notes in Computational Science and Engineering, Numerical Mathematics and Advanced Applications ENUMATH 2015 112 317 (2016) https://doi.org/10.1007/978-3-319-39929-4_31
Reduced‐order modelling for linear heat conduction with parametrised moving heat sources
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) https://doi.org/10.1186/s40323-016-0076-6
WITHDRAWN: An algorithm for the study of parameter dependence applied to hyperbolic systems
Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD–Galerkin method and a vascular shape parametrization
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) https://doi.org/10.1115/1.4031945
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) https://doi.org/10.1016/j.cma.2016.08.006