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Erschienen in: Structural and Multidisciplinary Optimization 2/2018

17.02.2018 | RESEARCH PAPER

Topology optimization of pressure structures based on regional contour tracking technology

verfasst von: Zhen-mian Li, Jianxing Yu, Yang Yu, LiXin Xu

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 2/2018

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Abstract

This article presents a new computational approach to solve the design-dependent loading problem in topology optimization of pressure structures. A simple algorithm based on digital image processing and regional contour tracking technology is proposed that generates the appropriate loading surface during the topology evolution. First, the topological layout produced during the optimization process is transformed into a compact image. Then, the regional contour tracking technology is used to represent the boundary of objects and extract pressure loading elements. At last, the pressures are transferred directly to corresponding element nodes. Due to the semi-automatically determined endpoints of the loading boundaries, the current scheme can deal with structures loaded by pressure from outside the domain, as well as pressure completely contained within the domain. Also, the calculation of the load sensitivities can be avoided in the current scheme. As a simple alternative computational strategy for compliance topology optimization of pressure structures, the current scheme is stable, flexible and efficient. Representative numerical examples are presented to show the validity and advantages of the proposed scheme. Especially, the design of closed containers and storage tanks indicates that it works well for the topology optimization of pressure structures.

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Metadaten
Titel
Topology optimization of pressure structures based on regional contour tracking technology
verfasst von
Zhen-mian Li
Jianxing Yu
Yang Yu
LiXin Xu
Publikationsdatum
17.02.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Structural and Multidisciplinary Optimization / Ausgabe 2/2018
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-018-1923-5

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