Abstract
This paper develops a multi-objective optimization method for the cure of thick composite laminates. The purpose is to minimize the cure time and maximum temperature overshoot in the cure process by designing the cure temperature profile. This method combines the finite element–based thermo-chemical coupled cure simulation with the non-dominated sorting genetic algorithm-II (NSGA-II). In order to investigate the influence of the number of dwells on the optimization result, four-dwell and two-dwell temperature profiles are selected for the design variables. The optimization method obtains successfully the Pareto optimal front of the multi-objective problem in thick and ultra-thick laminates. The result shows that the cure time and maximum temperature overshoot are both reduced significantly. The optimization result further illustrates that the four-dwell cure profile is more effective than the two-dwell, especially for the ultra-thick laminates. Through the optimization of the four-dwell profile, the cure time is reduced by 51.0% (thick case) and 30.3% (ultra-thick case) and the maximum temperature overshoot is reduced by 66.9% (thick case) and 73.1% (ultra-thick case) compared with the recommended cure profile. In addition, self-organizing map (SOM) is employed to visualize the relationships between the design variables with respect to the optimization result.
Highlights
With the increasing demand for high performance and weight reduction in various fields such as aerospace, navigation and automotive, etc., carbon fiber reinforced polymer (CFRP) composites have been widely used due to their high specific stiffness and strength
The efficiency and reliability of the algorithm were tested with 9 classical calculation examples and the results proved that non-dominated sorting genetic algorithm-II (NSGA-II) is able to approximate the Pareto-optimal front quickly [34]
Based on the finite element analysis, thermo-chemical coupled cure simulation is performed to evaluate the evolutions of temperature and degree of cure of the composites
Summary
With the increasing demand for high performance and weight reduction in various fields such as aerospace, navigation and automotive, etc., carbon fiber reinforced polymer (CFRP) composites have been widely used due to their high specific stiffness and strength. The risks associated with temperature overshoots in thick composite parts are dealt with by adopting conservative cure cycles or trial and error method This lead to long processing times and high manufacturing costs. Struzziero combined the finite element method with a multi-objective genetic algorithm to minimize the cure time and maximum temperature overshoot [20]. Shah used the multi-objective genetic algorithm to optimize the cure temperature profile to minimize residual stresses and the total cure time of asymmetric laminates cured by autoclave [21]. Jahromi used a trained dynamic ANN instead of finite element calculation and the non-linear programming algorithm to design multi-dwell temperature profile with the objective to minimize the maximum temperature difference during the curing [25]. The optimization result shows the cure time and temperature overshoot are effectively decreased by the multi-dwell temperature profile design
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