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Michael Schneier
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年份
An ensemble-proper orthogonal decomposition method for the nonstationary Navier--Stokes equations
M Gunzburger, N Jiang, M Schneier
SIAM Journal on Numerical Analysis 55 (1), 286-304, 2017
842017
An artificial compression reduced order model
V DeCaria, T Iliescu, W Layton, M McLaughlin, M Schneier
SIAM Journal on Numerical Analysis 58 (1), 565-589, 2020
472020
Continuous data assimilation reduced order models of fluid flow
C Zerfas, LG Rebholz, M Schneier, T Iliescu
Computer Methods in Applied Mechanics and Engineering 357, 112596, 2019
472019
Error analysis of supremizer pressure recovery for POD based reduced-order models of the time-dependent Navier--Stokes equations
K Kean, M Schneier
SIAM Journal on Numerical Analysis 58 (4), 2235-2264, 2020
422020
A Leray regularized ensemble-proper orthogonal decomposition method for parameterized convection-dominated flows
M Gunzburger, T Iliescu, M Schneier
IMA Journal of Numerical Analysis 40 (2), 886-913, 2020
392020
A higher-order ensemble/proper orthogonal decomposition method for the nonstationary Navier-Stokes Equations
M Gunzburger, N Jiang, M Schneier
International Journal of Numerical Analysis and Modeling 15, 608-627, 2018
342018
An Evolve-Filter-Relax Stabilized Reduced Order Stochastic Collocation Method for the Time-Dependent Navier--Stokes Equations
M Gunzburger, T Iliescu, M Mohebujjaman, M Schneier
SIAM/ASA Journal on Uncertainty Quantification 7 (4), 1162-1184, 2019
302019
On optimal pointwise in time error bounds and difference quotients for the proper orthogonal decomposition
B Koc, S Rubino, M Schneier, J Singler, T Iliescu
SIAM Journal on Numerical Analysis 59 (4), 2163-2196, 2021
262021
An embedded variable step IMEX scheme for the incompressible Navier–Stokes equations
V DeCaria, M Schneier
Computer Methods in Applied Mechanics and Engineering 376, 113661, 2021
242021
An efficient, partitioned ensemble algorithm for simulating ensembles of evolutionary MHD flows at low magnetic Reynolds number
N Jiang, M Schneier
Numerical Methods for Partial Differential Equations 34 (6), 2129-2152, 2018
242018
The Scott-Vogelius Method for Stokes Problem on Anisotropic Meshes
K Kean, M Neilan, M Schneier
arXiv preprint arXiv:2109.14780, 2021
102021
Diagnostics for eddy viscosity models of turbulence including data-driven/neural network based parameterizations
W Layton, M Schneier
Results in Applied Mathematics 8, 100099, 2020
92020
On the Prandtl–Kolmogorov 1-equation model of turbulence
K Kean, W Layton, M Schneier
Philosophical Transactions of the Royal Society A 380 (2226), 20210054, 2022
72022
Clipping over dissipation in turbulence models
K Kean, W Layton, M Schneier
arXiv preprint arXiv:2109.12107, 2021
32021
Latent Neural PDE Solver: a reduced-order modelling framework for partial differential equations
Z Li, S Patil, F Ogoke, D Shu, W Zhen, M Schneier, JR Buchanan Jr, ...
arXiv preprint arXiv:2402.17853, 2024
12024
Numerical integration of rational bubble functions with multiple singularities
M Schneier
Involve, a Journal of Mathematics 8 (2), 233-251, 2015
12015
An improved discrete least-squares/reduced-basis method for parameterized elliptic PDEs
M Gunzburger, M Schneier, C Webster, G Zhang
Journal of Scientific Computing 81, 76-91, 2019
2019
Ensemble Proper Orthogonal Decomposition Algorithms for the Incompressible Navier-Stokes Equations
M Schneier
2018
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