Reinforcement Design for Composite Laminate with Large Cutout by a Genetic Algorithm Method

Zhong Lei Sun; Mei Ying Zhao; Li Long Luo

doi:10.4028/www.scientific.net/AMR.631-632.754

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 631-632Reinforcement Design for Composite Laminate with...

Reinforcement Design for Composite Laminate with Large Cutout by a Genetic Algorithm Method

Abstract:

A dual-zone reinforcement ply stacking sequence optimization method used for comosite laminate with large cutout is present. The optimization method utilized a new Genetic Algorithm. The new Genetic Algorithm introduced a new strategy which can improve the efficiency of the traditional Genetic Algorithm and overcome the shortages of the worse convergency and prematurity of the Simple Genetic Algorithm. In the new Genetic Algorithm, the selection probability and the mutation probability are self-adaptive. Compared with the Simple Genetic Algorithm, the new Genetic Algorithm method shows good consistency, fast convergency and practical feasibility. By using the new Genetic Algorithm, the reinforcement ply stacking sequence optimization method got reasonable symmetric and balance stacking sequence which could meet the design requirements.

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Periodical:

Advanced Materials Research (Volumes 631-632)

Pages:

754-758

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.631-632.754

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Online since:

January 2013

Authors:

Zhong Lei Sun, Mei Ying Zhao, Li Long Luo

Keywords:

Composite, Cutout, Genetic Algorithm (GA), Python, Self-Adaptive

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References

[1] Nan Chang, The optimization of ply reinforced composite laminates and stability. Master thesis design. Northwestern Polytechnical University, (2007).

Google Scholar

[2] Xiaole Li, Experimental study on reinforcement design for composite laminate with a large cutout. Harbin Institute of Technology, (2011).

Google Scholar

[3] Wenyan Tang, The research and application of the genetic algorithm in the structure optimization. PhD thesis. Dalian University of Technology Journal, 2001. 12.

Google Scholar

[4] Dawei Lu, Li Shu, The application of the immune genetic algorithm in the optimization of the laminates stacking sequence. Journals of Beijing University of Aeronautics and Astronautics, 2005. 2.

Google Scholar

[5] Wei Zhou, Jie Zong, The development technology of Python. Beijing: Machinery Industry Press, (2009).

Google Scholar

[6] Yingshu Xiu, Degang Cui, The optimization of the layer in composite laminates stability, Engineering Mechanics, 2005, 22(6): 212~216.

Google Scholar