Kevin Carlberg
Title
Cited by
Cited by
Year
Efficient non‐linear model reduction via a least‐squares Petrov–Galerkin projection and compressive tensor approximations
K Carlberg, C Bou‐Mosleh, C Farhat
International Journal for Numerical Methods in Engineering 86 (2), 155–181, 2011
5292011
The GNAT method for nonlinear model reduction: effective implementation and application to computational fluid dynamics and turbulent flows
K Carlberg, C Farhat, J Cortial, D Amsallem
Journal of Computational Physics 242, 623–647, 2013
4772013
A method for interpolating on manifolds structural dynamics reduced‐order models
D Amsallem, J Cortial, K Carlberg, C Farhat
International Journal for Numerical Methods in Engineering 80 (9), 1241–1258, 2009
2442009
Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders
K Lee, KT Carlberg
Journal of Computational Physics 404, 108973, 2020
2342020
Galerkin v. least-squares Petrov–Galerkin projection in nonlinear model reduction
K Carlberg, M Barone, H Antil
Journal of Computational Physics 330, 693–734, 2017
1772017
A low‐cost, goal‐oriented ‘compact proper orthogonal decomposition’ basis for model reduction of static systems
K Carlberg, C Farhat
International Journal for Numerical Methods in Engineering 86 (3), 381–402, 2011
1132011
Adaptive h-refinement for reduced-order models
K Carlberg
International Journal for Numerical Methods in Engineering 102 (5), 1192–1210, 2015
1032015
Preserving Lagrangian structure in nonlinear model reduction with application to structural dynamics
K Carlberg, R Tuminaro, P Boggs
SIAM Journal on Scientific Computing 37 (2), B153–B184, 2015
842015
The ROMES method for statistical modeling of reduced-order-model error
M Drohmann, K Carlberg
SIAM/ASA Journal on Uncertainty Quantification 3 (1), 116–145, 2015
702015
A compact proper orthogonal decomposition basis for optimization-oriented reduced-order models
K Carlberg, C Farhat
AIAA Paper 5964, 10–12, 2008
572008
Error modeling for surrogates of dynamical systems using machine learning
S Trehan, KT Carlberg, LJ Durlofsky
International Journal for Numerical Methods in Engineering 112 (12), 1801-1827, 2017
552017
Conservative model reduction for finite-volume models
K Carlberg, Y Choi, S Sargsyan
Journal of Computational Physics 371, 280-314, 2018
532018
Space--time least-squares Petrov--Galerkin projection for nonlinear model reduction
Y Choi, K Carlberg
SIAM Journal on Scientific Computing 41 (1), A26-A58, 2019
422019
Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning
KT Carlberg, A Jameson, MJ Kochenderfer, J Morton, L Peng, ...
Journal of Computational Physics 395, 105-124, 2019
342019
An adaptive POD–Krylov reduced-order model for structural optimization
K Carlberg, C Farhat
The Eighth World Congress on Structural and Multidisciplinary Optimization …, 2009
282009
Model reduction of nonlinear mechanical systems via optimal projection and tensor approximation
KT Carlberg
Stanford University, 2011
272011
The GNAT nonlinear model reduction method and its application to fluid dynamics problems
K Carlberg, J Cortial, D Amsallem, M Zahr, C Farhat
6th AIAA Theoretical Fluid Mechanics Conference, Honolulu, Hawaii, June 2730 …, 2011
262011
An efficient, globally convergent method for optimization under uncertainty using adaptive model reduction and sparse grids
MJ Zahr, KT Carlberg, DP Kouri
SIAM/ASA Journal on Uncertainty Quantification 7 (3), 877-912, 2019
242019
Krylov-subspace recycling via the POD-augmented conjugate-gradient method
K Carlberg, V Forstall, R Tuminaro
SIAM Journal on Matrix Analysis and Applications 37 (3), 1304–1336, 2016
242016
Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting
K Carlberg, J Ray, BB Waanders
Computer Methods in Applied Mechanics and Engineering 289, 79–103, 2015
242015
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