Data-driven correction reduced order models for the quasi-geostrophic equations: a numerical investigation

DOI10.1080/10618562.2020.1723556zbMath1483.76047arXiv1908.05297OpenAlexW3005845448MaRDI QIDQ5031600

David R. Wells, Changhong Mou, Traian Iliescu, Honghu Liu

Publication date: 16 February 2022

Published in: International Journal of Computational Fluid Dynamics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1908.05297

zbMATH Keywords

quasi-geostrophic equationsphysical constraintsdata-driven modelreduced order modelclosure modelling

Mathematics Subject Classification ID

Medical applications (general) (92C50) Variational methods applied to problems in fluid mechanics (76M30) Stokes and related (Oseen, etc.) flows (76D07) Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs (65M60) Physiological flows (76Z05)

Related Items (8)

An efficient data-driven multiscale stochastic reduced order modeling framework for complex systems ⋮ Adaptive POD-DEIM correction for Turing pattern approximation in reaction-diffusion PDE systems ⋮ Learning proper orthogonal decomposition of complex dynamics using heavy-ball neural ODEs ⋮ Data-driven closure of projection-based reduced order models for unsteady compressible flows ⋮ Operator inference of non-Markovian terms for learning reduced models from partially observed state trajectories ⋮ Intrusive and data-driven reduced order modelling of the rotating thermal shallow water equation ⋮ Verifiability of the data-driven variational multiscale reduced order model ⋮ A Fast Time-Stepping Strategy for Dynamical Systems Equipped with a Surrogate Model

Uses Software

• redbKIT
• SINDy

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Calibrated reduced-order POD-Galerkin system for fluid flow modelling
• Proper orthogonal decomposition closure models for turbulent flows: a numerical comparison
• Dynamically orthogonal field equations for continuous stochastic dynamical systems
• A stabilized proper orthogonal decomposition reduced-order model for large scale quasigeostrophic ocean circulation
• Error estimates of proper orthogonal decomposition eigenvectors and Galerkin projection for a general dynamical system arising in fluid models
• Enablers for robust POD models
• Higamod: a hierarchical isogeometric approach for model reduction in curved pipes
• Data-driven non-Markovian closure models
• Data-based stochastic model reduction for the Kuramoto-Sivashinsky equation
• Reduced-order subscales for POD models
• Neural network closures for nonlinear model order reduction
• The reduction of complex dynamical systems using principal interaction patterns
• Data-driven operator inference for nonintrusive projection-based model reduction
• Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD-Galerkin method and a vascular shape parametrization
• A stabilized POD model for turbulent flows over a range of Reynolds numbers: optimal parameter sampling and constrained projection
• On dynamic mode decomposition: theory and applications
• Stochastic Parameterizing Manifolds and Non-Markovian Reduced Equations
• An Ensemble-Proper Orthogonal Decomposition Method for the Nonstationary Navier--Stokes Equations
• Dynamic mode decomposition of numerical and experimental data
• Model Reduction for Parametrized Optimal Control Problems in Environmental Marine Sciences and Engineering
• Turbulence, Coherent Structures, Dynamical Systems and Symmetry
• Data-Driven Filtered Reduced Order Modeling of Fluid Flows
• On a Certified Smagorinsky Reduced Basis Turbulence Model
• Data-adaptive harmonic spectra and multilayer Stuart-Landau models
• Data-Driven Science and Engineering
• Low-order modelling of laminar flow regimes past a confined square cylinder
• The need for a pressure-term representation in empirical Galerkin models of incompressible shear flows
• Physics constrained nonlinear regression models for time series
• Constrained sparse Galerkin regression

This page was built for publication: Data-driven correction reduced order models for the quasi-geostrophic equations: a numerical investigation