On the stability of projection-based model order reduction for convection-dominated laminar and turbulent flows
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Publication:2125450
DOI10.1016/j.jcp.2020.109681OpenAlexW3004113558MaRDI QIDQ2125450
Charbel Farhat, Sebastian Grimberg, Noah Youkilis
Publication date: 14 April 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2001.10110
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Cites Work
- Unnamed Item
- Unnamed Item
- Approximated Lax pairs for the reduced order integration of nonlinear evolution equations
- Reduced basis approximation and a posteriori error estimation for Stokes flows in parametrized geometries: roles of the inf-sup stability constants
- Nonlinear reduced basis approximation of parameterized evolution equations via the method of freezing
- The GNAT method for nonlinear model reduction: effective implementation and application to computational fluid dynamics and turbulent flows
- Proper orthogonal decomposition closure models for turbulent flows: a numerical comparison
- A low-diffusion MUSCL scheme for LES on unstructured grids
- Minimal subspace rotation on the Stiefel manifold for stabilization and enhancement of projection-based reduced order models for the compressible Navier-Stokes equations
- A new finite element formulation for computational fluid dynamics. VIII. The Galerkin/least-squares method for advective-diffusive equations
- Least-squares finite element methods
- Stable Galerkin reduced-order models for linearized compressible flow
- Enablers for robust POD models
- Efficient implementation of essentially nonoscillatory shock-capturing schemes
- Streamline upwind/Petrov-Galerkin formulations for convection dominated flows with particular emphasis on the incompressible Navier-Stokes equations
- On low-dimensional Galerkin models for fluid flow
- High performance python for direct numerical simulations of turbulent flows
- Stage-parallel fully implicit Runge-Kutta solvers for discontinuous Galerkin fluid simulations
- Galerkin v. least-squares Petrov-Galerkin projection in nonlinear model reduction
- Two-dimensional viscous flow computations on the Connection Machine: Unstructured meshes, upwind schemes and massively parallel computations
- Mixed-element-volume MUSCL methods with weak viscosity for steady and unsteady flow calculations
- Model reduction for compressible flows using POD and Galerkin projection
- An algebraic least squares reduced basis method for the solution of nonaffinely parametrized Stokes equations
- Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders
- Learning-based robust stabilization for reduced-order models of 2D and 3D Boussinesq equations
- A reduced order variational multiscale approach for turbulent flows
- Towards the ultimate conservative difference scheme. V. A second-order sequel to Godunov's method
- Efficient non-linear model reduction via a least-squares Petrov-Galerkin projection and compressive tensor approximations
- Nonlinear model order reduction based on local reduced-order bases
- Dimensional reduction of nonlinear finite element dynamic models with finite rotations and energy-based mesh sampling and weighting for computational efficiency
- Structure-preserving, stability, and accuracy properties of the energy-conserving sampling and weighting method for the hyper reduction of nonlinear finite element dynamic models
- Progressive construction of a parametric reduced‐order model for PDE‐constrained optimization
- Supremizer stabilization of POD-Galerkin approximation of parametrized steady incompressible Navier-Stokes equations
- Nonlinear Model Reduction via Discrete Empirical Interpolation
- An eddy-viscosity subgrid-scale model for turbulent shear flow: Algebraic theory and applications
- Model Reduction for Large-Scale Systems with High-Dimensional Parametric Input Space
- Iteratively reweighted least squares minimization for sparse recovery
- Recent progress in the development and understanding of SUPG methods with special reference to the compressible Euler and Navier-Stokes equations
- The dynamics of coherent structures in the wall region of a turbulent boundary layer
- Turbulence and the dynamics of coherent structures. I. Coherent structures
- Intermodal energy transfers in a proper orthogonal decomposition–Galerkin representation of a turbulent separated flow
- Turbulent Flows
- On a Certified Smagorinsky Reduced Basis Turbulence Model
- Stabilized Weighted Reduced Basis Methods for Parametrized Advection Dominated Problems with Random Inputs
- Stabilization of projection‐based reduced‐order models
- High‐order CFD methods: current status and perspective
- Low-dimensional modelling of high-Reynolds-number shear flows incorporating constraints from the Navier–Stokes equation
- Model Order Reduction for Problems with Large Convection Effects
- Reduced Basis Approximation of Parametrized Advection-Diffusion PDEs with High Péclet Number
- On the need for a nonlinear subscale turbulence term in POD models as exemplified for a high-Reynolds-number flow over an Ahmed body
- Variational multiscale proper orthogonal decomposition: Navier‐stokes equations
- Localized Discrete Empirical Interpolation Method
- A Method for the Numerical Calculation of Hydrodynamic Shocks
- Flux-corrected transport. I: SHASTA, a fluid transport algorithm that works