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• W4297029896 abstract "Mesh quality has a significant impact on the accuracy and efficiency of numerical computations. As geometric models and physics problems become more and more complex, the automatically generated initial mesh inevitably produces poor elements. In order to improve the mesh quality, a filtering-based mesh smoothing method is proposed in this paper. This method combines tensor voting and filtering algorithm. First, the mesh nodes are classified by the normal tensor voting theory, and then the improved bilateral filtering algorithm is used to combine the differential geometry information and distribution density information of the neighboring nodes to optimize and adjust the position of free nodes, so as to improve the mesh quality. The traditional Laplacian method is used to process all mesh nodes with a uniform smoothing method, resulting in a large shrinkage and can not better keeping the feature. The method in this paper not only remedies the disadvantage above but also avoids the generation of invalid elements. The experimental results show that the method can significantly improve the quality of the mesh, and ensure the small volume shrinkage of the mesh with better-preserved features." @default.
• W4297029896 created "2022-09-25" @default.
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• W4297029896 date "2022-01-01" @default.
• W4297029896 modified "2023-10-17" @default.
• W4297029896 title "A Smoothing Method of Triangular Surface Mesh Based on Filtering" @default.
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• W4297029896 doi "https://doi.org/10.1007/978-981-19-6226-4_27" @default.
• W4297029896 hasPublicationYear "2022" @default.
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