Finite volume POD-Galerkin stabilised reduced order methods for the parametrised incompressible Navier–Stokes equations
@article{Stabile2017FiniteVP, title={Finite volume POD-Galerkin stabilised reduced order methods for the parametrised incompressible Navier–Stokes equations}, author={Giovanni Stabile and Gianluigi Rozza}, journal={Computers \& Fluids}, year={2017} }
126 Citations
POD model order reduction with space-adapted snapshots for incompressible flows
- Computer ScienceAdvances in Computational Mathematics
- 2019
Two approaches of deriving stable POD-Galerkin reduced-order models for unsteady incompressible Navier-Stokes problems are proposed and it is shown how suitable lifting functions can be obtained from standard adaptive finite element computations.
A Reduced-Order Shifted Boundary Method for Parametrized incompressible Navier-Stokes equations
- MathematicsArXiv
- 2019
A POD-Galerkin reduced order model for the Navier-Stokes equations in stream function-vorticity formulation
- Computer ScienceComputers & Fluids
- 2022
Data-Driven POD-Galerkin Reduced Order Model for Turbulent Flows
- Computer Science, EngineeringJ. Comput. Phys.
- 2020
POD-Galerkin reduced order methods for combined Navier-Stokes transport equations based on a hybrid FV-FE solver
- MathematicsComput. Math. Appl.
- 2020
Parametric POD-Galerkin Model Order Reduction for Unsteady-State Heat Transfer Problems
- Engineering, PhysicsCommunications in Computational Physics
- 2020
A parametric reduced order model based on proper orthogonal decomposition with Galerkin projection has been developed and applied for the modeling of heat transport in T-junction pipes which are…
A Reduced Order Cut Finite Element method for geometrically parameterized steady and unsteady Navier-Stokes problems
- MathematicsComput. Math. Appl.
- 2022
Efficient geometrical parametrization for finite‐volume‐based reduced order methods
- MathematicsInternational Journal for Numerical Methods in Engineering
- 2020
This work presents an approach for the efficient treatment of parametrized geometries in the context of POD-Galerkin reduced order methods based on Finite Volume full order approximations, which relies on basis functions defined on an average deformed configuration and makes use of the Discrete Empirical Interpolation Method (D-EIM).
The Effort of Increasing Reynolds Number in Projection-Based Reduced Order Methods: From Laminar to Turbulent Flows
- PhysicsLecture Notes in Computational Science and Engineering
- 2020
We present in this double contribution two different reduced order strategies for incompressible parameterized Navier-Stokes equations characterized by varying Reynolds numbers. The first strategy…
POD‐identification reduced order model of linear transport equations for control purposes
- MathematicsInternational Journal for Numerical Methods in Fluids
- 2019
Intrusive reduced order modeling techniques require access to the solver's discretization and solution algorithm, which are not available for most computational fluid dynamics codes. Therefore, a…
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