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A nodal-based optimization method for the design of continuous fiber-reinforced structures

journal contribution
posted on 2024-11-03, 11:06 authored by Xuyu Zhang, Yimin Xie, Qing Li, Cong Wang, Zicheng Zhuang, He LiHe Li, Shiwei ZhouShiwei Zhou
The mechanical performance of fiber-reinforced structures highly relies on fibers' paths in the matrix material. Unlike the level set method that offsets the zero-level contours of a higher-dimensional function, this work shifts the nodes of a truss network within an optimization framework to design individual paths specifically. All intersection manners of a single fiber with the rectangular continuum element are considered in the finite analysis to retrieve mechanical responses within an acceptable error margin numerically. The design variables, namely node coordinates, are updated via the method of moving asymptotes under the guide of the sensitivity of the objective function, which is smoothed using a radial basis function. After each optimization iteration, the paths are slightly adjusted to avoid twisting problems and control fiber gaps using a polynomial interpolation scheme. Numerical examples illustrate that the proposed method can generate elegant fiber paths within a few steps. In the meantime, the optimization efficiency is improved as the design variables are significantly reduced. Compared with existing methods, we found that lower objective values can be achieved as allowing nodes to move freely in the design domain guarantees a global minimum theoretically.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1016/j.compstruct.2023.117455
  2. 2.
    ISSN - Is published in 02638223

Journal

Composite Structures

Volume

323

Number

117455

Start page

1

End page

18

Total pages

18

Publisher

Elsevier

Place published

United Kingdom

Language

English

Copyright

© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Former Identifier

2006125591

Esploro creation date

2023-09-21

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