Dynamic mode decomposition with core sketch
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POD/DEIM nonlinear model order reduction of an ADI implicit shallow water equations model
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Towards non-intrusive reduced order 3D free surface flow modelling
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Non-intrusive reduced order modelling of fluid–structure interactions
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Efficient non-linear model reduction via a least-squares Petrov-Galerkin projection and compressive tensor approximations
Carlberg, Kevin; Bou-Mosleh, Charbel; Farhat, Charbel
International Journal for Numerical Methods in Engineering, Vol. 86, Issue 2
https://doi.org/10.1002/nme.3050
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October 2010
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Nonlinear proper orthogonal decomposition for convection-dominated flows
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Nonlinear Principal Component Analysis by Neural Networks: Theory and Application to the Lorenz System
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Data-driven identification of dynamical models using adaptive parameter sets
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The GNAT method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows
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Extension of Dynamic Mode Decomposition for dynamic systems with incomplete information based on t-model of optimal prediction
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March 2023
Greedy Nonintrusive Reduced Order Model for Fluid Dynamics
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Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction
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September 2018
pyNIROM—A suite of python modules for non-intrusive reduced order modeling of time-dependent problems
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November 2021
Application of reduced-order models based on PCA & Kriging for the development of digital twins of reacting flow applications
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February 2019
Nonintrusive reduced order modeling framework for quasigeostrophic turbulence
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November 2019
Missing Point Estimation in Models Described by Proper Orthogonal Decomposition
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November 2008
Linearly Recurrent Autoencoder Networks for Learning Dynamics
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January 2019
Data-driven operator inference for nonintrusive projection-based model reduction
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July 2016
Nonlinear principal component analysis using autoassociative neural networks
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February 1991
The role of artificial intelligence in achieving the Sustainable Development Goals
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January 2020
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
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January 2020
An autoencoder‐based reduced‐order model for eigenvalue problems with application to neutron diffusion
Phillips, Toby R. F.; Heaney, Claire E.; Smith, Paul N.
International Journal for Numerical Methods in Engineering, Vol. 122, Issue 15
https://doi.org/10.1002/nme.6681
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May 2021
A perspective on machine learning methods in turbulence modeling
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March 2021
Machine Learning for Fluid Mechanics
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September 2019
Non-intrusive reduced order modelling of the Navier–Stokes equations
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August 2015
Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem
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May 2019
A non-intrusive reduced-order model for compressible fluid and fractured solid coupling and its application to blasting
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February 2017
Nonlinear principal component analysis of noisy data
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May 2007
Physics-Informed Probabilistic Learning of Linear Embeddings of Nonlinear Dynamics with Guaranteed Stability
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January 2020
A probabilistic graphical model foundation for enabling predictive digital twins at scale
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May 2021
Sparsity-promoting dynamic mode decomposition
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February 2014
Non-intrusive reduced-order modeling for fluid problems: A brief review
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December 2019
Principal interval decomposition framework for POD reduced-order modeling of convective Boussinesq flows: PRINCIPAL INTERVAL DECOMPOSITION MODEL REDUCTION FRAMEWORK
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February 2015
On closures for reduced order models—A spectrum of first-principle to machine-learned avenues
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September 2021
Breaking the Kolmogorov Barrier in Model Reduction of Fluid Flows
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February 2020
Automating turbulence modelling by multi-agent reinforcement learning
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January 2021
Sketching Methods for Dynamic Mode Decomposition in Spherical Shallow Water Equations
conference
December 2022
An ‘empirical interpolation’ method: application to efficient reduced-basis discretization of partial differential equations
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November 2004
Multiscale simulations of complex systems by learning their effective dynamics
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April 2022
Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning
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October 2019
Nonlinear Model Reduction via Discrete Empirical Interpolation
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January 2010
A parametric and feasibility study for data sampling of the dynamic mode decomposition: Spectral insights and further explorations
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March 2022
A stabilized proper orthogonal decomposition reduced-order model for large scale quasigeostrophic ocean circulation
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May 2015
A domain decomposition non-intrusive reduced order model for turbulent flows
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March 2019
On the stability of projection-based model order reduction for convection-dominated laminar and turbulent flows
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October 2020
Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space
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January 2008
An AI-based non-intrusive reduced-order model for extended domains applied to multiphase flow in pipes
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May 2022
Model order reduction for nonlinear dynamical systems based on trajectory piecewise-linear approximations
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June 2006
Efficient reduced-basis treatment of nonaffine and nonlinear partial differential equations
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May 2007
Non-linear model reduction for the Navier–Stokes equations using residual DEIM method
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April 2014
Non-intrusive reduced-order modelling of the Navier-Stokes equations based on RBF interpolation: Non-intrusive reduced-order modelling of the Navier-Stokes equations based on RBF interpolation
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July 2015
Deep Multilayer Convolution Frameworks for Data-Driven Learning of Fluid flow Dynamics
conference
June 2018
Modal Analysis of Fluid Flows: Applications and Outlook
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March 2020
Randomized dynamic mode decomposition for nonintrusive reduced order modelling: RANDOMIZED DYNAMIC MODE DECOMPOSITION FOR NIROM
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February 2017
Dynamic Mode Decomposition
book
January 2016
Dynamic mode decomposition as an analysis tool for time-dependent partial differential equations
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July 2022
A deep learning enabler for nonintrusive reduced order modeling of fluid flows
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August 2019
Certified Reduced Basis Methods for Parametrized Partial Differential Equations
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