Physics Guided Machine Learning for Variational Multiscale Reduced Order Modeling (Q6097872)

scientific article; zbMATH DE number 7693354

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English	Physics Guided Machine Learning for Variational Multiscale Reduced Order Modeling	scientific article; zbMATH DE number 7693354

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instance of

scholarly article

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title

Physics Guided Machine Learning for Variational Multiscale Reduced Order Modeling (English)

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SIAM Journal on Scientific Computing

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publication date

7 June 2023

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full work available at URL

https://arxiv.org/abs/2205.12419

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zbMATH Keywords

reduced order modeling

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variational multiscale method

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physics guided machine learning

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nonlinear proper orthogonal decomposition

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autoencoder

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Galerkin projection

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MaRDI publication profile

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cites work

A long short-term memory embedding for hybrid uplifted reduced order models

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On the stability and extension of reduced-order Galerkin models in incompressible flows. A numerical study of vortex shedding

0 references

Minimal subspace rotation on the Stiefel manifold for stabilization and enhancement of projection-based reduced order models for the compressible Navier-Stokes equations

0 references

Model Order Reduction for PDE Constrained Optimization

0 references

A model reduction approach for the variational estimation of vascular compliance by solving an inverse fluid–structure interaction problem

0 references

Goal-oriented, model-constrained optimization for reduction of large-scale systems

0 references

Galerkin v. least-squares Petrov-Galerkin projection in nonlinear model reduction

0 references

Stochastic Tools in Mathematics and Science

0 references

Optimal prediction and the Mori–Zwanzig representation of irreversible processes

0 references

Optimal prediction with memory

0 references

Interpolation among reduced‐order matrices to obtain parameterized models for design, optimization and probabilistic analysis

0 references

Comparative numerical analysis using reduced-order modeling strategies for nonlinear large-scale systems

0 references

The ROMES Method for Statistical Modeling of Reduced-Order-Model Error

0 references

Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations

0 references

Q4787388

0 references

A POD-Galerkin reduced order model for a LES filtering approach

0 references

<i>A priori</i> estimation of memory effects in reduced-order models of nonlinear systems using the Mori–Zwanzig formalism

0 references

Data-driven POD-Galerkin reduced order model for turbulent flows

0 references

Turbulence, Coherent Structures, Dynamical Systems and Symmetry

0 references

The variational multiscale method -- a paradigm for computational mechanics

0 references

Large eddy simulation and the variational multiscale method

0 references

Large eddy simulation of turbulent channel flows by the variational multiscale method

0 references

Variational multiscale proper orthogonal decomposition: Convection-dominated convection-diffusion-reaction equations

0 references

Variational multiscale proper orthogonal decomposition: Navier‐stokes equations

0 references

Nonlinear closure modeling in reduced order models for turbulent flows: a dynamical system approach

0 references

Stability properties of POD-Galerkin approximations for the compressible Navier-Stokes equations

0 references

A reduced-order method for simulation and control of fluid flows

0 references

Finite Element Methods for Incompressible Flow Problems

0 references

Verifiability of the data-driven variational multiscale reduced order model

0 references

Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders

0 references

Transport, Collective Motion, and Brownian Motion

0 references

Data-driven variational multiscale reduced order models

0 references

A hierarchy of low-dimensional models for the transient and post-transient cylinder wake

0 references

Reduced-order modelling for flow control. Papers based on the presentations at the course, Udine, Italy, September 2008

0 references

The need for a pressure-term representation in empirical Galerkin models of incompressible shear flows

0 references

Data-Driven Discovery of Closure Models

0 references

Time-series machine-learning error models for approximate solutions to parameterized dynamical systems

0 references

Breaking the Kolmogorov Barrier with Nonlinear Model Reduction

0 references

Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization

0 references

Reduced-order adaptive controllers for fluid flows using POD

0 references

Model Reduction for Flow Analysis and Control

0 references

POD-Galerkin approximations in PDE-constrained optimization

0 references

Q2815667

0 references

A stabilized proper orthogonal decomposition reduced-order model for large scale quasigeostrophic ocean circulation

0 references

Blending modified Gaussian closure and non-Gaussian reduced subspace methods for turbulent dynamical systems

0 references

New POD Error Expressions, Error Bounds, and Asymptotic Results for Reduced Order Models of Parabolic PDEs

0 references

Turbulence and the dynamics of coherent structures. I. Coherent structures

0 references

Renormalized Mori–Zwanzig-reduced models for systems without scale separation

0 references

Projection-based model reduction: formulations for physics-based machine learning

0 references

Recurrent neural network closure of parametric POD-Galerkin reduced-order models based on the Mori-Zwanzig formalism

0 references

Proper orthogonal decomposition closure models for turbulent flows: a numerical comparison

0 references

Data-Driven Filtered Reduced Order Modeling of Fluid Flows

0 references

Efficient estimation of cardiac conductivities via POD-DEIM model order reduction

0 references

Progressive construction of a parametric reduced‐order model for PDE‐constrained optimization

0 references

Q2839899

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mardi Publication:6097872