Eigensolution analysis of immersed boundary method based on volume penalization: Applications to high-order schemes

•Eigensolution analysis for volume penalization based on flux reconstruction.•Volume penalization imposes boundary conditions by adding additional dissipation.•Fully-discrete analysis directs the selection of penalization parameter.•Adding second-order term inside the solid is proposed for improved...

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Veröffentlicht in:Journal of computational physics 2022-01, Vol.449, p.110817, Article 110817
Hauptverfasser: Kou, Jiaqing, Hurtado-de-Mendoza, Aurelio, Joshi, Saumitra, Le Clainche, Soledad, Ferrer, Esteban
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container_start_page 110817
container_title Journal of computational physics
container_volume 449
creator Kou, Jiaqing
Hurtado-de-Mendoza, Aurelio
Joshi, Saumitra
Le Clainche, Soledad
Ferrer, Esteban
description •Eigensolution analysis for volume penalization based on flux reconstruction.•Volume penalization imposes boundary conditions by adding additional dissipation.•Fully-discrete analysis directs the selection of penalization parameter.•Adding second-order term inside the solid is proposed for improved performance.•Generalization to Navier-Stokes solver to simulate flow past a cylinder is reported. This paper presents eigensolution and non-modal analyses for immersed boundary methods (IBMs) based on volume penalization for the linear advection equation. This approach is used to analyze the behavior of flux reconstruction (FR) discretization, including the influence of polynomial order and penalization parameter on numerical errors and stability. Through a semi-discrete analysis, we find that the inclusion of IBM adds additional dissipation without changing significantly the dispersion of the original numerical discretization. This agrees with the physical intuition that in this type of approach, the solid wall is modelled as a porous medium with vanishing viscosity. From a stability point of view, the variation of penalty parameter can be analyzed based on a fully-discrete analysis, which leads to practical guidelines on the selection of penalization parameter. Numerical experiments indicate that the penalization term needs to be increased to damp oscillations inside the solid (i.e. porous region), which leads to undesirable time step restrictions. As an alternative, we propose to include a second-order term in the solid for the no-slip wall boundary condition. Results show that by adding a second-order term we improve the overall accuracy with relaxed time step restriction. This indicates that the optimal value of the penalization parameter and the second-order damping can be carefully chosen to obtain a more accurate scheme. Finally, the approximated relationship between these two parameters is obtained and used as a guideline to select the optimum penalty terms in a Navier-Stokes solver, to simulate flow past a cylinder.
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This paper presents eigensolution and non-modal analyses for immersed boundary methods (IBMs) based on volume penalization for the linear advection equation. This approach is used to analyze the behavior of flux reconstruction (FR) discretization, including the influence of polynomial order and penalization parameter on numerical errors and stability. Through a semi-discrete analysis, we find that the inclusion of IBM adds additional dissipation without changing significantly the dispersion of the original numerical discretization. This agrees with the physical intuition that in this type of approach, the solid wall is modelled as a porous medium with vanishing viscosity. From a stability point of view, the variation of penalty parameter can be analyzed based on a fully-discrete analysis, which leads to practical guidelines on the selection of penalization parameter. Numerical experiments indicate that the penalization term needs to be increased to damp oscillations inside the solid (i.e. porous region), which leads to undesirable time step restrictions. As an alternative, we propose to include a second-order term in the solid for the no-slip wall boundary condition. Results show that by adding a second-order term we improve the overall accuracy with relaxed time step restriction. This indicates that the optimal value of the penalization parameter and the second-order damping can be carefully chosen to obtain a more accurate scheme. 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This paper presents eigensolution and non-modal analyses for immersed boundary methods (IBMs) based on volume penalization for the linear advection equation. This approach is used to analyze the behavior of flux reconstruction (FR) discretization, including the influence of polynomial order and penalization parameter on numerical errors and stability. Through a semi-discrete analysis, we find that the inclusion of IBM adds additional dissipation without changing significantly the dispersion of the original numerical discretization. This agrees with the physical intuition that in this type of approach, the solid wall is modelled as a porous medium with vanishing viscosity. From a stability point of view, the variation of penalty parameter can be analyzed based on a fully-discrete analysis, which leads to practical guidelines on the selection of penalization parameter. 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Numerical experiments indicate that the penalization term needs to be increased to damp oscillations inside the solid (i.e. porous region), which leads to undesirable time step restrictions. As an alternative, we propose to include a second-order term in the solid for the no-slip wall boundary condition. Results show that by adding a second-order term we improve the overall accuracy with relaxed time step restriction. This indicates that the optimal value of the penalization parameter and the second-order damping can be carefully chosen to obtain a more accurate scheme. 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subjects Boundary conditions
Computational physics
Damping
Discretization
Eigensolution analysis
Flux reconstruction
High-order methods
Immersed boundary method
Non-modal analysis
Optimization
Parameters
Polynomials
Porous media
Stability analysis
Volume penalization
title Eigensolution analysis of immersed boundary method based on volume penalization: Applications to high-order schemes
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