An Efficient Optimization Method for Stacking Sequence of Composite Pressure Vessels Based on Artificial Neural Network and Genetic Algorithm

Liang, Jianguo; Ning, Zemin; Li, Yinhui; Gao, Haifeng; Liu, Jianglin; Tian, Wang; Zhao, Xiaodong; Jia, Zhaotun; Xue, Yuqin; Miao, Chunxiang

doi:10.1007/s10443-024-10201-8

Appl Compos Mater

2024

DOI: 10.1007/s10443-024-10201-8

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An Efficient Optimization Method for Stacking Sequence of Composite Pressure Vessels Based on Artificial Neural Network and Genetic Algorithm

Jianguo Liang,

Zemin Ning,

Yinhui Li

et al.

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Structural hierarchical optimisation of composite pressure vessel lining design based on FEA-RSM-PSO approach

Liu,

Guo,

et al. 2024

Journal of Reinforced Plastics and Composites

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The weight and functionality of the composite pressure vessel is greatly affected by the liner construction, which is currently determined only by theoretical formulas and engineering experience, and there are often problems such as vessel failure and excessive weight. Here, the design of composite pressure vessel lining structures is optimised by the implementation of a hierarchical technique. In the first stage, the maximum form factor is utilised to optimise the dome’s shape, and the shape factors of domes that are often employed are compared. In the second level, a procedure combining Finite Element Analysis (FEA), Response Surface Methodology (RSM) and Particle Swarm Algorithm (PSO) is proposed to optimise the design of the liner’s spout and barrel structure to explore the lightweight requirements guided by the DOT-CFFC standard. In such, the goal and constraint values are computed using the finite element method, to cut down on time spent on computation, the response surface model is built rather than reusing the finite element computations, and to determine the best parameter combinations for the design variables, the particle swarm algorithm’s update of location and speed is used. The method can provide an important reference for designing complex lining structures with many variables.

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Structural hierarchical optimisation of composite pressure vessel lining design based on FEA-RSM-PSO approach

Liu,

Guo,

et al. 2024

Journal of Reinforced Plastics and Composites

View full text Add to dashboard Cite

show abstract

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An Efficient Optimization Method for Stacking Sequence of Composite Pressure Vessels Based on Artificial Neural Network and Genetic Algorithm

Cited by 1 publication

References 68 publications

Structural hierarchical optimisation of composite pressure vessel lining design based on FEA-RSM-PSO approach

Structural hierarchical optimisation of composite pressure vessel lining design based on FEA-RSM-PSO approach

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