Assessment and improvement of mapping algorithms for non-matching meshes and geometries in computational FSI

Wang, Tianyang; Wüchner, Roland; Sicklinger, Stefan; Bletzinger, Kai‐Uwe

doi:10.1007/s00466-016-1262-6

Cited by 31 publications

(17 citation statements)

References 53 publications

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“…The first geometry processed is the one referred to as “the catenoid” shown in Figure . To take into account the case of a coarse‐to‐fine load transfer, the source mesh is composed of 338 triangular elements and 196 nodes, whereas the target one is finer, with 2738 elements and 1444 nodes.…”

Section: Implementation and Resultsmentioning

confidence: 99%

“…To take into account the case of a coarse‐to‐fine load transfer, the source mesh is composed of 338 triangular elements and 196 nodes, whereas the target one is finer, with 2738 elements and 1444 nodes. The traction field, whose contour on the source mesh is visible in Figure , is defined using trigonometric functions, as shown in the work of Wang et al…”

Section: Implementation and Resultsmentioning

confidence: 99%

“…This last task requires several attempts to be carried out, which is the most time‐consuming step. Furthermore, as stated in the work of Wang, the method of transferring loads based on shape functions and conservation of virtual work suffers when the target mesh is finer than the source one, since high oscillations affect the mapped field. Our method gives smooth results in both cases of transfer: coarse‐to‐fine and fine‐to‐coarse.…”

Section: Implementation and Resultsmentioning

confidence: 99%

“…There is wide literature available dealing with mapping methods. Remarkable and extensive reviews on the most important and common approaches were given by Smith et al, Wang et al, and Franke, among others.…”

Section: Introductionmentioning

confidence: 99%

“…This method is used by Farhat et al also for a transient problem. Wang et al in a dedicated paper provide a remarkable review of several mapping algorithms. The considered methods are nearest‐element interpolation, SMM, and the dual mortar method, which uses dual shape functions, as demonstrated by Puso; for the last two, an original enforcing consistency approach is proposed.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A balanced load mapping method based on radial basis functions and fuzzy sets

Biancolini

Chiappa

Giorgetti

et al. 2018

Numerical Meth Engineering

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A common issue in multiphysics analysis regards a reliable way for loose couplings, because the same object is modeled using different mesh refinements, each one suited for a proper field of physics. Output data originating from a simulation environment are transferred as input data to a different model to run a new analysis. It is strongly desirable that such information transfers in a conservative way in terms of general balance. This paper faces the problem of pressure mapping between widely dissimilar meshes. The proposed procedure yields two steps: pressure interpolation by means of radial basis functions and fuzzy subset correction. The first step is pointwise interpolation that exploits a series of basis functions. The second step applies to the outcome of the first one to reestablish load balance between the two models through the introduction of a smooth correction field. Practical tests from the aeronautical field allow validating the method.

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Section: Implementation and Resultsmentioning

confidence: 99%

Section: Implementation and Resultsmentioning

confidence: 99%

Section: Implementation and Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A balanced load mapping method based on radial basis functions and fuzzy sets

Biancolini

Chiappa

Giorgetti

et al. 2018

Numerical Meth Engineering

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Variational coupling of non‐matching discretizations across finitely deforming fluid–structure interfaces

Kang

Kwack

Masud

2022

Numerical Methods in Fluids

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This paper presents a stabilized monolithic method for coupling incompressible viscous fluids with finitely deforming elastic solids across non‐matching interfacial meshes. Governing equations for the solid are written in the finite deformation Lagrangian frame using velocity field as the primary unknown, while the governing equations for the fluid are written in an Arbitrary Lagrangian–Eulerian (ALE) frame to accommodate large motions of the fluid–solid interfaces. Interface coupling terms are derived by embedding Discontinuous Galerkin (DG) ideas in the Variational Multiscale (VMS) framework and locally resolving the fine‐scale variational equations from the fluid and the solid subdomains along the common interface. The unique attribute of the proposed Variational Multiscale Discontinuous Galerkin (VMDG) method is a systematic procedure for deriving analytical expression for the traction Lagrange multiplier at the fluid–solid interface. The structure of the interface stabilization tensor emerges naturally and is shown to be a function of the boundary operators that are associated with the domain interior operators from the fluid and the solid subdomains. The derived stabilization tensor possesses the features of area‐averaging and stress‐averaging and evolves spatially and temporally with the evolving nonlinear fields at the interface. An analysis of the mathematical properties of the interface stabilization tensor is presented and subsequently verified numerically. The method is implemented using four‐node tetrahedral elements for the fluid as well as the solid subdomains while employing equal‐order interpolations for the various interacting fields. Benchmark problems are presented for the verification of the method for finitely deforming fluid–structure interfaces.

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