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Erschienen in: Structural and Multidisciplinary Optimization 1/2013

01.07.2013 | Research Paper

Simultaneous shape and topology optimization of shell structures

verfasst von: Behrooz Hassani, Seyed Mehdi Tavakkoli, Hossein Ghasemnejad

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 1/2013

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Abstract

In this research, Method of Moving Asymptotes (MMA) is utilized for simultaneous shape and topology optimization of shell structures. It is shown that this approach is well matched with the large number of topology and shape design variables. The currently practiced technology for optimization is to find the topology first and then to refine the shape of structure. In this paper, the design parameters of shape and topology are optimized simultaneously in one go. In order to model and control the shape of free form shells, the NURBS (Non Uniform Rational B-Spline) technology is used. The optimization problem is considered as the minimization of mean compliance with the total material volume as active constraint and taking the shape and topology parameters as design variables. The material model employed for topology optimization is assumed to be the Solid Isotropic Material with Penalization (SIMP). Since the MMA optimization method requires derivatives of the objective function and the volume constraint with respect to the design variables, a sensitivity analysis is performed. Also, for alleviation of the instabilities such as mesh dependency and checkerboarding the convolution noise cleaning technique is employed. Finally, few examples taken from literature are presented to demonstrate the performance of the method and to study the effect of the proposed concurrent approach on the optimal design in comparison to the sequential topology and shape optimization methods.

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Metadaten
Titel
Simultaneous shape and topology optimization of shell structures
verfasst von
Behrooz Hassani
Seyed Mehdi Tavakkoli
Hossein Ghasemnejad
Publikationsdatum
01.07.2013
Verlag
Springer-Verlag
Erschienen in
Structural and Multidisciplinary Optimization / Ausgabe 1/2013
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-013-0894-9

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