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ORCIDMatthew J. Zahr
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2020 – today
- 2024
[j14]Charles J. Naudet, Matthew J. Zahr
:
A space-time high-order implicit shock tracking method for shock-dominated unsteady flows. J. Comput. Phys. 501: 112792 (2024)- [j13]Jakob Vandergrift, Matthew J. Zahr:
Preconditioned iterative solvers for constrained high-order implicit shock tracking methods. J. Comput. Phys. 514: 113234 (2024) - [i20]Julian M. Kaufmann, Matthew J. Zahr:
Symmetric, Optimization-based, Cross-element Compatible Nodal Distributions for High-order Finite Elements. CoRR abs/2401.13209 (2024) - [i19]Jakob Vandergrift, Matthew J. Zahr:
Preconditioned iterative solvers for constrained high-order implicit shock tracking methods. CoRR abs/2402.18403 (2024) - [i18]Tianshu Wen, Matthew J. Zahr:
An augmented Lagrangian trust-region method with inexact gradient evaluations to accelerate constrained optimization problems using model hyperreduction. CoRR abs/2405.14827 (2024) - 2023
- [j12]Marzieh Alireza Mirhoseini, Matthew J. Zahr:
Model reduction of convection-dominated partial differential equations via optimization-based implicit feature tracking. J. Comput. Phys. 473: 111739 (2023) - [j11]Tianshu Wen, Matthew J. Zahr:
A globally convergent method to accelerate large-scale optimization using on-the-fly model hyperreduction: Application to shape optimization. J. Comput. Phys. 484: 112082 (2023) - [j10]Tianci Huang, Charles J. Naudet, Matthew J. Zahr:
High-order implicit shock tracking boundary conditions for flows with parametrized shocks. J. Comput. Phys. 495: 112517 (2023) - [i17]Victor Zucatti, Matthew J. Zahr:
An adaptive, training-free reduced-order model for convection-dominated problems based on hybrid snapshots. CoRR abs/2301.01718 (2023) - [i16]Tianci Huang, Charles J. Naudet, Matthew J. Zahr:
High-order implicit shock tracking boundary conditions for flows with parametrized shocks. CoRR abs/2304.11427 (2023) - [i15]Marzieh Alireza Mirhoseini, Matthew J. Zahr:
Accelerated solutions of convection-dominated partial differential equations using implicit feature tracking and empirical quadrature. CoRR abs/2305.15661 (2023) - [i14]Charles J. Naudet, Matthew J. Zahr:
A space-time high-order implicit shock tracking method for shock-dominated unsteady flows. CoRR abs/2308.04065 (2023) - [i13]Han Gao, Matthew J. Zahr:
An adaptive model reduction method leveraging locally supported basis functions. CoRR abs/2310.05379 (2023) - 2022
- [j9]Charles J. Naudet, Johannes Töger, Matthew J. Zahr:
Accurate quantification of blood flow wall shear stress using simulation-based imaging: a synthetic, comparative study. Eng. Comput. 38(5): 3987-4003 (2022) - [j8]Andrew Shi, Per-Olof Persson, Matthew J. Zahr:
Implicit shock tracking for unsteady flows by the method of lines. J. Comput. Phys. 454: 110906 (2022) - [j7]Tianci Huang, Matthew J. Zahr:
A robust, high-order implicit shock tracking method for simulation of complex, high-speed flows. J. Comput. Phys. 454: 110981 (2022) - [i12]Tianshu Wen, Matthew J. Zahr:
A globally convergent method to accelerate large-scale optimization using on-the-fly model hyperreduction: application to shape optimization. CoRR abs/2206.09942 (2022) - 2021
- [i11]Andrew Shi, Per-Olof Persson, Matthew J. Zahr:
Implicit shock tracking for unsteady flows by the method of lines. CoRR abs/2101.08913 (2021) - [i10]Tianci Huang, Matthew J. Zahr:
A robust, high-order implicit shock tracking method for simulation of complex, high-speed flows. CoRR abs/2105.00139 (2021) - [i9]Han Gao, Matthew J. Zahr, Jian-Xun Wang:
Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems. CoRR abs/2107.12146 (2021) - [i8]Charles J. Naudet, Johannes Töger, Matthew J. Zahr:
Accurate quantification of blood flow wall shear stress using simulation-based imaging: a synthetic, comparative study. CoRR abs/2109.14650 (2021) - [i7]Marzieh Alireza Mirhoseini, Matthew J. Zahr:
Model reduction of convection-dominated partial differential equations via optimization-based implicit feature tracking. CoRR abs/2109.14694 (2021) - 2020
- [j6]Matthew J. Zahr, Andrew Shi, Per-Olof Persson:
Implicit shock tracking using an optimization-based high-order discontinuous Galerkin method. J. Comput. Phys. 410: 109385 (2020) - [j5]Daniel Zhengyu Huang, Will Pazner, Per-Olof Persson, Matthew J. Zahr:
High-order partitioned spectral deferred correction solvers for multiphysics problems. J. Comput. Phys. 412: 109441 (2020) - [i6]Masayuki Yano, Tianci Huang, Matthew J. Zahr:
A globally convergent method to accelerate topology optimization using on-the-fly model reduction. CoRR abs/2004.05756 (2020) - [i5]Alexander Schein, Kevin T. Carlberg, Matthew J. Zahr:
Preserving general physical properties in model reduction of dynamical systems via constrained-optimization projection. CoRR abs/2011.13998 (2020)
2010 – 2019
- 2019
- [j4]Matthew J. Zahr, Kevin T. Carlberg, Drew P. Kouri:
An Efficient, Globally Convergent Method for Optimization Under Uncertainty Using Adaptive Model Reduction and Sparse Grids. SIAM/ASA J. Uncertain. Quantification 7(3): 877-912 (2019) - [i4]Daniel Zhengyu Huang, Will Pazner, Per-Olof Persson, Matthew J. Zahr:
High-order partitioned spectral deferred correction solvers for multiphysics problems. CoRR abs/1909.01977 (2019) - [i3]Han Gao, Jian-Xun Wang, Matthew J. Zahr:
Non-intrusive model reduction of large-scale, nonlinear dynamical systems using deep learning. CoRR abs/1911.03808 (2019) - [i2]Matthew J. Zahr, Andrew Shi, Per-Olof Persson:
Implicit shock tracking using an optimization-based, r-adaptive, high-order discontinuous Galerkin method. CoRR abs/1912.11207 (2019) - 2018
- [j3]Matthew J. Zahr, Per-Olof Persson:
An optimization-based approach for high-order accurate discretization of conservation laws with discontinuous solutions. J. Comput. Phys. 365: 105-134 (2018) - 2016
- [j2]Matthew J. Zahr, Per-Olof Persson:
An adjoint method for a high-order discretization of deforming domain conservation laws for optimization of flow problems. J. Comput. Phys. 326: 516-543 (2016) - 2015
- [j1]David Amsallem, Matthew J. Zahr, Kyle Washabaugh:
Fast local reduced basis updates for the efficient reduction of nonlinear systems with hyper-reduction. Adv. Comput. Math. 41(5): 1187-1230 (2015) - 2014
- [i1]Matthew J. Zahr, Charbel Farhat:
Progressive construction of a parametric reduced-order model for PDE-constrained optimization. CoRR abs/1407.7618 (2014)
Coauthor Index
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