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Structural and Multidisciplinary Optimization

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16-09-2019 | Research Paper

Discrete material selection and structural topology optimization of composite frames for maximum fundamental frequency with manufacturing constraints

Authors: Zunyi Duan, Jun Yan, Ikjin Lee, Erik Lund, Jingyuan Wang

Published in: Structural and Multidisciplinary Optimization | Issue 5/2019

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Abstract

This paper proposes a methodology for simultaneous optimization of composite frame topology and its material design considering specific manufacturing constraints for the maximum fundamental frequency with a bound formulation. The discrete material optimization (DMO) approach is employed to couple two geometrical scales: frame structural topology scale and microscopic composite material parameter scale. The simultaneous optimization of macroscopic size or topology of the frame and microscopic composite material design can be implemented within the DMO framework. Six types of manufacturing constraints are explicitly included in the optimization model as a series of linear inequality or equality constraints. Sensitivity analysis with respect to variables of the two geometrical scales is performed using the semi-analytical sensitivity analysis method. Corresponding optimization formulation and solution procedures are also developed and validated through numerical examples. Numerical study shows that the proposed simultaneous optimization model can effectively enhance the frame fundamental frequency while including specific manufacturing constraints that reduce the risk of local failure of the laminated composite. The proposed multi-scale optimization model for the maximum fundamental frequency is expected to provide a new choice for the design of composite frames in engineering applications.

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Title: Discrete material selection and structural topology optimization of composite frames for maximum fundamental frequency with manufacturing constraints
Authors: Zunyi Duan
Jun Yan
Ikjin Lee
Erik Lund
Jingyuan Wang
Publication date: 16-09-2019
Publisher: Springer Berlin Heidelberg
Published in: Structural and Multidisciplinary Optimization / Issue 5/2019
Print ISSN: 1615-147X
Electronic ISSN: 1615-1488
DOI: https://doi.org/10.1007/s00158-019-02397-2

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