Reduced basis modelling of turbulence with well-developed inertial range

DOI10.1016/j.cma.2023.116683MaRDI QIDQ6185245

Tómas Chacón-Rebollo, Alejandro Bandera Moreno, Enrique Delgado Ávila, Macarena Gómez-Mármol, Cristina Caravaca García

Publication date: 29 January 2024

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

zbMATH Keywords

large eddy simulationgreedy algorithmreduced basis methodreduced order modellingKolmogorov energy cascade

Mathematics Subject Classification ID

Fluid mechanics (76-XX) Statistical mechanics, structure of matter (82-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Reduced basis approximation of parametrized optimal flow control problems for the Stokes equations
• Proper orthogonal decomposition closure models for turbulent flows: a numerical comparison
• Data-driven POD-Galerkin reduced order model for turbulent flows
• Reduced basis method for multi-parameter-dependent steady Navier-Stokes equations: applications to natural convection in a cavity
• Finite dimensional approximation of nonlinear problems. I: Branches of nonsingular solutions
• Finite volume POD-Galerkin stabilised reduced order methods for the parametrised incompressible Navier-Stokes equations
• An `empirical interpolation' method: Application to efficient reduced-basis discretization of partial differential equations
• Incremental unknowns, multilevel methods and the numerical simulation of turbulence
• POD-Galerkin reduced order methods for combined Navier-Stokes transport equations based on a hybrid FV-FE solver
• A novel large eddy simulation model for the quasi-geostrophic equations in a finite volume setting
• Certified reduced basis VMS-Smagorinsky model for natural convection flow in a cavity with variable height
• Stabilized reduced basis methods for parametrized steady Stokes and Navier-Stokes equations
• A stabilized POD model for turbulent flows over a range of Reynolds numbers: optimal parameter sampling and constrained projection
• Mathematical and numerical foundations of turbulence models and applications
• A general multipurpose interpolation procedure: The magic points
• An efficient computational framework for reduced basis approximation anda posteriorierror estimation of parametrized Navier–Stokes flows
• Supremizer stabilization of POD-Galerkin approximation of parametrized steady incompressible Navier-Stokes equations
• Reduced Basis Error Bound Computation of Parameter-Dependent Navier–Stokes Equations by the Natural Norm Approach
• Efficient reduced-basis treatment of nonaffine and nonlinear partial differential equations
• Turbulence, Coherent Structures, Dynamical Systems and Symmetry
• Intermodal energy transfers in a proper orthogonal decomposition–Galerkin representation of a turbulent separated flow
• On a Certified Smagorinsky Reduced Basis Turbulence Model
• Hierarchical Approximate Proper Orthogonal Decomposition
• Galerkin Proper Orthogonal Decomposition Methods for a General Equation in Fluid Dynamics
• Convergence Rates of the POD–Greedy Method
• Variational multiscale proper orthogonal decomposition: Navier‐stokes equations
• Physics Guided Machine Learning for Variational Multiscale Reduced Order Modeling
• On a certified VMS-Smagorinsky reduced basis model with LPS pressure stabilisation