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2010•Transactions of Beijing Institute of TechnologyRequires access

One Mesh Smoothing Algorithm Combining Laplacian and Local Optimization-Based Mesh Smoothing Techniques

Shudao Zhang

Open publisher page 2 citations

Abstract

A new objective function is defined for two and three dimensions.In numerical simulation,if the mesh quality cannot be improved by constrained Laplacian smoothing,local optimization-based smoothing algorithm is used.Thus none mesh gets worse while optimization-based smoothing applied only to limited number of meshes and efficiency of optimization is highly improved.Numerical result indicated that however applied in mixed grids the new objective function is effective.

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What this paper is about

A new objective function is defined for two and three dimensions.In numerical simulation,if the mesh quality cannot be improved by constrained Laplacian smoothing,local optimization-based smoothing algorithm is used.Thus none mesh gets worse while optimization-based smoothing applied only to limited number of meshes and efficiency of optimization is highly improved.Numerical result indicated that however applied in mixed grids the new objective function is effective.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

A new objective function is defined for two and three dimensions.In numerical simulation,if the mesh quality cannot be improved by constrained Laplacian smoothing,local optimization-based smoothing algorithm is used.Thus none mesh gets worse while optimization-based smoothing applied only to limited number of meshes and efficiency of optimization is highly improved.Numerical result indicated that however applied in mixed grids the new objective function is effective.

Key concepts: Laplacian smoothing, Smoothing, Polygon mesh, Mathematical optimization, Computer science, Algorithm, Function (biology), Laplace operator

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