A new mesh smoothing method based on a neural network
As an elementary mesh quality improvement technique, smoothing has been widely used in finite element (FE) analysis. Heuristic smoothing methods and optimization-based smoothing methods are the two main smoothing types. The former is efficient. However, it operates heuristically and may create low-q...
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Veröffentlicht in: | Computational mechanics 2022-02, Vol.69 (2), p.425-438 |
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Sprache: | eng |
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Zusammenfassung: | As an elementary mesh quality improvement technique, smoothing has been widely used in finite element (FE) analysis. Heuristic smoothing methods and optimization-based smoothing methods are the two main smoothing types. The former is efficient. However, it operates heuristically and may create low-quality elements. In contrast, optimization-based smoothing is very effective at improving mesh quality. However, it suffers from high computational cost since it calculates the optimal position of a free node iteratively. In this paper, we present a new smoothing method. The proposed method imitates the optimization-based smoothing based on a neural network, but it calculates the optimal position of a free node straightforwardly. Hence, the proposed method is more efficient than these optimization-based smoothing methods while being comparable in terms of mesh quality. We present various testing results to illustrate the effectiveness of the proposed method. |
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ISSN: | 0178-7675 1432-0924 |
DOI: | 10.1007/s00466-021-02097-z |