Changhong Mou
Cited by
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Data-driven variational multiscale reduced order models
C Mou, B Koc, O San, LG Rebholz, T Iliescu
Computer Methods in Applied Mechanics and Engineering 373, 113470, 2021
A multifidelity ensemble Kalman filter with reduced order control variates
AA Popov, C Mou, A Sandu, T Iliescu
SIAM Journal on Scientific Computing 43 (2), A1134-A1162, 2021
Data-driven correction reduced order models for the quasi-geostrophic equations: A numerical investigation
C Mou, H Liu, DR Wells, T Iliescu
International Journal of Computational Fluid Dynamics 34 (2), 147-159, 2020
Reduced order models for the quasi-geostrophic equations: A brief survey
C Mou, Z Wang, DR Wells, X Xie, T Iliescu
Fluids 6 (1), 16, 2020
Commutation error in reduced order modeling of fluid flows
B Koc, M Mohebujjaman, C Mou, T Iliescu
Advances in Computational Mathematics 45, 2587-2621, 2019
Verifiability of the data-driven variational multiscale reduced order model
B Koc, C Mou, H Liu, Z Wang, G Rozza, T Iliescu
Journal of Scientific Computing 93 (2), 54, 2022
Reduced order model closures: A brief tutorial
W Snyder, C Mou, H Liu, O San, R DeVita, T Iliescu
Recent Advances in Mechanics and Fluid-Structure Interaction with …, 2022
Lagrangian reduced order modeling using finite time Lyapunov exponents
X Xie, PJ Nolan, SD Ross, C Mou, T Iliescu
Fluids 5 (4), 189, 2020
An energy-based lengthscale for reduced order models of turbulent flows
C Mou, E Merzari, O San, T Iliescu
Nuclear Engineering and Design 412, 112454, 2023
An efficient data-driven multiscale stochastic reduced order modeling framework for complex systems
C Mou, N Chen, T Iliescu
Journal of Computational Physics 493, 112450, 2023
Data‐driven variational multiscale reduced order modeling of vaginal tissue inflation
W Snyder, JA McGuire, C Mou, DA Dillard, T Iliescu, R De Vita
International Journal for Numerical Methods in Biomedical Engineering 39 (1 …, 2023
A numerical investigation of the lengthscale in the mixing-length reduced order model of the turbulent channel flow
C Mou, E Merzari, O San, T Iliescu
arXiv preprint arXiv:2108.02254, 2021
Combining Stochastic Parameterized Reduced‐Order Models With Machine Learning for Data Assimilation and Uncertainty Quantification With Partial Observations
C Mou, LM Smith, N Chen
Journal of Advances in Modeling Earth Systems 15 (10), e2022MS003597, 2023
Data-Driven Variational Multiscale Reduced Order Modeling of Turbulent Flows
C Mou
Virginia Tech, 2021
Cross-validation of data-driven correction reduced order modeling
C Mou
Virginia Tech, 2018
Stochastic data-driven variational multiscale reduced order models
F Lu, C Mou, H Liu, T Iliescu
arXiv preprint arXiv:2209.02739, 2022
A Hybrid Nonlinear Data Assimilation Method for Complex Fluid Systems with Partial Observations, with Applications to Precipitating Quasi-geostrophic Equations
C Mou, LM Smith, N Chen
AGU Fall Meeting Abstracts 2022, NG35B-0455, 2022
A Two-Level Galerkin Reduced Order Model for the Steady Navier-Stokes Equations
D Park, C Mou, H Liu, A Sandu, T Iliescu
arXiv preprint arXiv:2211.12968, 2022
Data-Driven Variational Multiscale Reduced Order Models for the Quasi-Geostrophic Equations
C Mou, T Iliescu, H Liu, D Wells
AGU Fall Meeting Abstracts 2021, NG15A-0418, 2021
Combining a Stochastic Parameterized Filter with Machine Learning to Assimilate Complex Turbulent Systems Using Partial Observations
N Chen, C Mou, L Smith
2022 Fall Western Sectional Meeting, 0
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