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Eric J. Parish
Eric J. Parish
Verified email at sandia.gov - Homepage
Title
Cited by
Cited by
Year
A paradigm for data-driven predictive modeling using field inversion and machine learning
EJ Parish, K Duraisamy
Journal of computational physics 305, 758-774, 2016
5742016
A priori estimation of memory effects in reduced-order models of nonlinear systems using the Mori–Zwanzig formalism
A Gouasmi, EJ Parish, K Duraisamy
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2017
75*2017
Non-Markovian closure models for large eddy simulations using the Mori-Zwanzig formalism
EJ Parish, K Duraisamy
Phys. Rev. Fluids 2 (1), 014604, 2017
642017
A dynamic subgrid scale model for large eddy simulations based on the Mori–Zwanzig formalism
EJ Parish, K Duraisamy
Journal of Computational Physics 349, 154-175, 2017
622017
The Adjoint Petrov–Galerkin method for non-linear model reduction
EJ Parish, CR Wentland, K Duraisamy
Computer Methods in Applied Mechanics and Engineering 365, 112991, 2020
56*2020
Parameterized neural ordinary differential equations: Applications to computational physics problems
K Lee, EJ Parish
Proceedings of the Royal Society A 477 (2253), 20210162, 2021
522021
Time-series machine-learning error models for approximate solutions to parameterized dynamical systems
EJ Parish, KT Carlberg
Computer Methods in Applied Mechanics and Engineering 365, 112990, 2020
362020
A unified framework for multiscale modeling using the Mori-Zwanzig formalism and the variational multiscale method
EJ Parish, K Duraisamy
arXiv preprint arXiv:1712.09669, 2017
182017
Windowed least-squares model reduction for dynamical systems
EJ Parish, KT Carlberg
Journal of Computational Physics 426, 109939, 2021
172021
On the impact of dimensionally-consistent and physics-based inner products for POD-Galerkin and least-squares model reduction of compressible flows
EJ Parish, F Rizzi
Journal of Computational Physics 491, 112387, 2023
162023
Windowed space–time least-squares Petrov–Galerkin model order reduction for nonlinear dynamical systems
YS Shimizu, EJ Parish
Computer Methods in Applied Mechanics and Engineering 386, 114050, 2021
15*2021
Reduced order modeling of turbulent flows using statistical coarse-graining
E Parish, K Duraisamy
46th AIAA Fluid Dynamics Conference, 3640, 2016
152016
Quantification of turbulence modeling uncertainties using full field inversion
E Parish, K Duraisamy
22nd AIAA Computational Fluid Dynamics Conference, 2459, 2015
132015
Pressio: Enabling projection-based model reduction for large-scale nonlinear dynamical systems
F Rizzi, PJ Blonigan, EJ Parish, KT Carlberg
arXiv preprint arXiv:2003.07798, 2020
122020
Generalized Riemann problem-based upwind scheme for the vorticity transport equations
E Parish, K Duraisamy, P Chandrashekar
Computers & Fluids 132, 10-18, 2016
92016
Projection-based model reduction for coupled conduction—enclosure radiation systems
V Brunini, EJ Parish, J Tencer, F Rizzi
Journal of Heat Transfer 144 (6), 062101, 2022
52022
Turbulence modeling for compressible flows using discrepancy tensor-basis neural networks and extrapolation detection
E Parish, DS Ching, NE Miller, SJ Beresh, MF Barone
AIAA SciTech 2023 Forum, 2126, 2023
42023
Evaluation of dual-weighted residual and machine learning error estimation for projection-based reduced-order models of steady partial differential equations
PJ Blonigan, EJ Parish
Computer Methods in Applied Mechanics and Engineering 409, 115988, 2023
32023
Residual-based stabilized reduced-order models of the transient convection-diffusion-reaction equation obtained through discrete and continuous projection
E Parish, M Yano, I Tezaur, T Iliescu
arXiv preprint arXiv:2302.09355, 2023
32023
Uncertainty propagation of the negative Spallart–Allmaras turbulence model coefficients using projection-based reduced-order models
EH Krath, PJ Blonigan, E Parish
AIAA SCITECH 2023 Forum, 2041, 2023
32023
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