Mesh Deformation Approaches – A Survey

Mm, Selim; Rp, Koomullil

doi:10.4172/2090-0902.1000181

Cited by 15 publications

(3 citation statements)

References 49 publications

(71 reference statements)

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“…This interpolation is performed using a Radial Basis Function (RBF) as described in [11]. This choice is motivated by the simplicity of this meshless method and by the quality of the resulting deformed elements [39].…”

Section: Interpolation Of the Surfacesmentioning

confidence: 99%

Two-level substructuring and parallel mesh generation for domain decomposition methods

Gharbi

Parret-Fréaud

Bovet

et al. 2021

Finite Elements in Analysis and Design

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This paper presents a new parallel mesh generation method leading to subdomains of shape well-suited to Schur based domain decomposition methods such as the FETI and BDD solvers. Starting from a coarse mesh, subdomains meshes are created in parallel through hierarchical mesh refinement and morphing techniques. The proposed methodology aims at limiting the occurrence of known pathological situations (jagged interfaces, misplaced heterogeneity with respect to the interfaces, . . . ) that penalize the convergence of the solver. Furthermore, it enables to distribute and parallelize the mesh generation step in the early phases of the whole analysis. Besides its good behavior towards convergence, the mesh generation is thus distributed. The method is assessed, on several academical and industrial test cases, for both its parallel efficiency when creating the mesh and its capability to generate decomposition resulting in less FETI iterations.

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Section: Interpolation Of the Surfacesmentioning

confidence: 99%

Two-level substructuring and parallel mesh generation for domain decomposition methods

Gharbi

Parret-Fréaud

Bovet

et al. 2021

Finite Elements in Analysis and Design

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“…Mesh deformation due to geometry displacements during numerical simulations can be accomplished using a body-fitted approach [8], Chimera/overset methods [9], immersed/embedded boundary methods [10], and interpolation methods [11]. Each of them has its own strengths and weaknesses.…”

Section: Introductionmentioning

confidence: 99%

Numerical Modelling of Static Aeroelastic Deformations of Slender Wing in Aerodynamic Design

Bugała,

Sznajder,

Sieradzki

2023

Transactions on Aerospace Research

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The article presents the validation of two methods for analyzing the aerodynamic properties of the aircraft wing concerning aeroelastic effects. The first method is based on low-cost computational models (Euler–Bernoulli Beam Model and Vortex Lattice Method [VLM]). Its primary objective is to estimate the wing’s deformation early in the design stages and during the automatic optimization process. The second one is a method that uses solutions of unsteady Navier–Stokes equations (URANS). This method suits early design, particularly for unconventional designs or flight conditions exceeding lowfidelity method limits. The coupling of the flow and structural models was done by Radial Basis Functions implemented as a user-defined module in the ANSYS Fluent solver. The structural model has variants for linear and nonlinear wing deformations. Features enhancing applicability for real-life applications, such as the definition of deformable and nondeformable mesh zones with smooth transition between them, have been included in this method. A rectangular wing of a high-altitude long-endurance (HALE) aeroplane, built based on the NACA 0012 profile, was used to validate both methods. The resulting deflections and twists of the wing have been compared with reference data for the linear and nonlinear variants of the model.

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confidence: 99%

Efficient mesh deformation based on randomized RBF solvers

Bader,

Parret-Freaud,

Da Veiga

et al.

Proceedings of the Seventh International Conference on Parallel, Distributed, GPU and Cloud Computing for Engineering

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Mesh deformation methods [7] have been widely used for the past decades in various fields such as fluid-structure interaction, aerodynamic shape optimization, unsteady and aeroelastic computational fluid dynamics. Such methods are particularly interesting in order to update meshes during a simulation without the need to perform an (often expensive) full regeneration of the mesh, e.g. when facing moving boundaries or geometry update during a structural optimization loop.Among the numerous existing methods, radial basis functions interpolation (RBF) [1] is particularly suitable for unstructured mesh applications due to its simplicity and the high quality of the resulting mesh. One key aspect of RBF-based mesh deformation is the resolution of a dense linear system, which tends to be computationally expensive and high memory demanding when dealing with large-scale meshes [2, 3], thus being a major drawback of the method. This could be mitigated using an iterative solver instead of a direct one during the resolution step, thus saving the memory needed to store the factorization. However, some radial basis functions lead to ill-conditioned systems, requiring the use of an efficient preconditioner which tends to complexify the problem.

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Mesh Deformation Approaches – A Survey

Cited by 15 publications

References 49 publications

Two-level substructuring and parallel mesh generation for domain decomposition methods

Two-level substructuring and parallel mesh generation for domain decomposition methods

Numerical Modelling of Static Aeroelastic Deformations of Slender Wing in Aerodynamic Design

Efficient mesh deformation based on randomized RBF solvers

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