FEM-Validated Optimal Design of Laminate Process Parameters Based on Improved Genetic Algorithm

Author:

Mou Xing,Shen Zhiqiang,Liu Honghao,Xv Hui,Xia Xianzhao,Chen ShijunORCID

Abstract

In tape placement process, the laying angle and laying sequence of laminates have proven their significant effects on the mechanical properties of carbon fibre reinforced composite material, specifically, laminates. In order to optimise these process parameters, an optimisation algorithm is developed based on the principles of genetic algorithms for improving the precision of traditional genetic algorithms and resolving the premature phenomenon in the optimisation process. Taking multi-layer symmetrically laid carbon fibre laminates as the research object, this algorithm adopts binary coding to conduct the optimisation of process parameters and mechanical analysis with the laying angle as the design variable and the strength ratio R as the response variable. A case study was conducted and its results were validated by the finite element analyses. The results show that the stresses before and after optimisation are 116.0 MPa and 100.9 MPa, respectively, with a decrease of strength ratio by 13.02%. The results comparison indicates that, in the iterative process, the search range is reduced by determining the code and location of important genes, thereby reducing the computational workload by 21.03% in terms of time consumed. Through multiple calculations, it validates that “gene mutation” is an indispensable part of the genetic algorithm in the iterative process.

Funder

Fundamental Research Funds for the Central Universities

Publisher

MDPI AG

Subject

Engineering (miscellaneous),Ceramics and Composites

Reference25 articles.

1. Influence of Failure Criteria and Intralaminar Damage Progression Numerical Models on the Prediction of the Mechanical Behavior of Composite Laminates

2. Optimal Design of Automobile Battery Shell Made of Carbon Fiber Reinforced Composites;Hu;Mach. Des. Manuf.,2017

3. Innovation in Automotive Engineering:A look into the future;Wallentowitz;J. Automot. Saf. Energy,2013

4. Review of parallel genetic algorithm;Feng;Comput. Appl. Softw.,2018

5. Design optimization of CFRP stacking sequence using a multi-island genetic algorithms under low-velocity impact loads

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