Optimization strategy for curing ultra-thick composite laminates based on multi-objective genetic algorithm. (April 2022)

• Record Type: Journal Article
• Authors: Gao, Yan; Ye, Jing; Yuan, Zhenyi; Ling, Zihan; Zhou, Yanquan; Lin, Zequn; Dong, Jiale; Wang, Huan; Peng, Hua-Xin
• Is Part Of: Composites communications. Volume 31(2022)
• Publication Date: 2022-04
• Subjects: Multi-objective optimization -- Genetic algorithm -- Curing strategy -- Ultra-thick laminate
• DOI: 10.1016/j.coco.2022.101115
• Languages: English
• ISSNs: 2452-2139

Abstract

Abstract: Thermal gradient and temperature overshoot during the curing process of ultra-thick carbon fibre composite have a major impact on its properties. We present a strategy to optimize the curing process based on the surrogate model and genetic algorithm. Firstly, a FE model based on heat transfer was developed for curing a 30 mm thick laminate and validated by experimental data. Then a multi-objective optimization strategy was developed by combining the optimal Latin hypercube sampling method, elliptical basis function (EBF) neural network model and non-dominated sorting genetic algorithm-II (NSGA-II). It is found that the optimized cure cycle can effectively reduce the undesirable maximum DoC (Degree of cure) gradient and the temperature gradient leading to improved mechanical properties for the 30 mm thick laminate. Graphical abstract: Image 1 Highlights: A multi-objective optimization strategy has been developed for curing ultra-thick composite laminates based on optimal Latin hypercube sampling method, surrogate model and genetic algorithm. The proposed optimization method is simple, fast and of high accuracy. The strategy with verified feasibility is to promote the development of ultra-thick composites for engineering applications.