Publications

Eric Parish, Kevin Carlberg (2020). Time-series machine-learning error models for approximate solutions to parameterized dynamical systems. Computer Methods in Applied Mechanics and Engineering, 365:112990, 2020..

Philip Etter, Kevin Carlberg (2020). Online adaptive basis refinement and compression for reduced-order models via vector-space sieving. Computer Methods in Applied Mechanics and Engineering, 364:112931, 2020.

Patrick Blonigan, Kevin Carlberg, Francesco Rizzi, Micah Howard, Jeff Fike (2020). Model reduction for hypersonic aerodynamics via conservative LSPG projection and hyper-reduction. AIAA Paper 2020-0104, AIAA Scitech 2020 Forum, Orlando, FL, January 6–10, 2020.

Kookjin Lee, Kevin Carlberg (2020). Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders. Journal of Computational Physics, Vol. 404, p. 108973 (2020).

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Eric Parish, Kevin Carlberg (2019). Windowed least-squares model reduction for dynamical systems.

Kookjin Lee, Kevin Carlberg (2019). Deep Conservation: A latent dynamics model for exact satisfaction of physical conservation laws.

Kevin Carlberg, Sofia Guzzetti, Mohammad Khalil, Khachik Sargsyan (2019). The network uncertainty quantification method for propagating uncertainties in component-based systems. Submitted to JUQ.

Matthew Zahr, Kevin Carlberg, Drew Kouri (2019). An efficient, globally convergent method for optimization under uncertainty using adaptive model reduction and sparse grids. SIAM/ASA Journal on Uncertainty Quantification, Vol. 7, No. 3, p.877–912 (2019).

Kevin Carlberg, Antony Jameson, Mykel Kochenderfer, Jeremy Morton, Liqian Peng, Freddie Witherden (2019). Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning. Journal of Computational Physics, Vol. 395, p. 105–124 (2019).

Kevin Carlberg, Lukas Brencher, Bernard Haasdonk, Andrea Barth (2019). Data-driven time parallelism via forecasting. SIAM Journal on Scientific Computing, 41(3):B466–B496, 2019.

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Brian Freno, Kevin Carlberg (2019). Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations. Computer Methods in Applied Mechanics and Engineering, Vol. 348, p.250–296 (2019).

Stefano Pagani, Andrea Manzoni, Kevin Carlberg (2019). Statistical closure modeling for reduced-order models of stationary systems by the ROMES method. Submitted to SIAM JUQ.

Youngsoo Choi, Kevin Carlberg (2019). Space–time least-squares Petrov–Galerkin projection for nonlinear model reduction. SIAM Journal on Scientific Computing, Vol. 41, No. 1, p. A26–A58 (2019).

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Kevin Carlberg, Youngsoo Choi, Syuzanna Sargsyan (2018). Conservative model reduction for finite-volume models. Journal of Computational Physics, Vol. 371, p. 280–314 (2018).

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Kookjin Lee, Kevin Carlberg, Howard Elman (2018). Stochastic least-squares Petrov–Galerkin method for parameterized linear systems. SIAM/ASA Journal on Uncertainty Quantification, Vol. 6, No. 1, p.374–396 (2018).

Kevin Carlberg, Virginia Forstall, Ray Tuminaro (2017). Krylov-subspace recycling via the POD-augmented conjugate-gradient method. SIAM Journal on Matrix Analysis and Applications, Vol. 37, No. 3, p.1304–1336 (2016).

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John Tencer, Kevin Carlberg, Marvin Larsen, Roy Hogan (2017). Accelerated solution of discrete ordinates approximation to the Boltzmann transport equation via model reduction. Journal of Heat Transfer, Vol. 139, No. 12, p.122701 (2017).

Sumeet Trehan, Kevin Carlberg, Louis Durlofsky (2017). Error modeling for surrogates of dynamical systems using machine learning. International Journal for Numerical Methods in Engineering, Vol. 112, No. 12, p. 1801–1827 (2017).

Liqian Peng, Kevin Carlberg (2017). Structure-preserving model reduction for marginally stable LTI systems. Preprint.

Kevin Carlberg, Matthew Barone, Harbir Antil (2017). Galerkin v. least-squares Petrov--Galerkin projection in nonlinear model reduction. Journal of Computational Physics, Vol. 330, p. 693–734 (2017).

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John Tencer, Kevin Carlberg, Marvin Larsen, Roy Hogan (2016). Reduced order modeling applied to the discrete ordinates method for radiation heat transfer in participating media. HT 2016-7010, ASME 2016 Summer Heat Transfer Conference, Washington, DC, July 10–14, 2016.

Kevin Carlberg, Jaideep Ray, Bart van Bloemen Waanders (2015). Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting. Computer Methods in Applied Mechanics and Engineering, Vol. 289, p.79–103 (2015).

Kevin Carlberg (2015). Adaptive $h$-refinement for reduced-order models. International Journal for Numerical Methods in Engineering, Vol. 102, No. 5, p.1192–1210 (2015).

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Kevin Carlberg, Ray Tuminaro, Paul Boggs (2015). Preserving Lagrangian structure in nonlinear model reduction with application to structural dynamics. SIAM Journal on Scientific Computing, Vol. 37, No. 2, p. B153–B184 (2015).

Martin Drohmann, Kevin Carlberg (2015). The ROMES method for statistical modeling of reduced-order-model error. SIAM/ASA Journal on Uncertainty Quantification, Vol. 3, No. 1, p.116–145 (2015).

Kevin Carlberg, Charbel Farhat, Julien Cortial, David Amsallem (2013). The GNAT method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows. Journal of Computational Physics, Vol. 242, p. 623–647 (2013).

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Kevin Carlberg, Ray Tuminaro, Paul Boggs (2012). Efficient structure-preserving model reduction for nonlinear mechanical systems with application to structural dynamics. AIAA Paper 2012-1969, 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Honolulu, Hawaii, April 23–26, 2012.

Kevin Carlberg, Julien Cortial, David Amsallem, Matthew Zahr, Charbel Farhat (2011). The GNAT nonlinear model reduction method and its application to fluid dynamics problems. AIAA Paper 2011-3112, 6th AIAA Theoretical Fluid Mechanics Conference, Honolulu, Hawaii, June 27–30, 2011.

Kevin Carlberg, Charbel Farhat (2011). A low-cost, goal-oriented ‘compact proper orthogonal decomposition’ basis for model reduction of static systems. International Journal for Numerical Methods in Engineering, Vol. 86, No. 3, p. 381–402 (2011).

Kevin Carlberg, Charbel Bou-Mosleh, Charbel Farhat (2011). Efficient non-linear model reduction via a least-squares Petrov–Galerkin projection and compressive tensor approximations. International Journal for Numerical Methods in Engineering, Vol. 86, No. 2, p. 155–181 (2011).

Robert Stephan, Kevin Carlberg (2010). Gappy data reconstruction and applications in archaeology. Proceedings of XXXVIII Conference on Computer Applications & Quantitative Methods in Archaeology, Granada, Spain, April 6–9, 2010.

David Amsallem, Julien Cortial, Kevin Carlberg, Charbel Farhat (2009). A method for interpolating on manifolds structural dynamics reduced-order models. International Journal for Numerical Methods in Engineering, Vol. 80, No. 9, p. 1241–1257 (2009).

Kevin Carlberg, Charbel Farhat (2009). An adaptive POD-Krylov reduced-order model for structural optimization. Proceedings of 8th World Congress on Structural and Multidisciplinary Optimization, Lisbon, Portugal, June 1–5, 2009.

Kevin Carlberg, Charbel Farhat (2008). A low-cost, goal-oriented ‘compact proper orthogonal decomposition’ basis for model reduction of static systems. AIAA Paper 2008-5964, 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Victoria, Canada, September 10–12, 2008.