4.6 Article

A multi-dwell temperature profile design for the cure of thick CFRP composite laminates

Journal

Publisher

SPRINGER LONDON LTD
DOI: 10.1007/s00170-021-07765-1

Keywords

CFRP; Cure process; Multi-objective optimization; Genetic algorithm; Finite element method

Funding

  1. National Natural Science Foundation of China [11872310]

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This paper presents a multi-objective optimization method for the cure of thick composite laminates, which successfully reduces cure time and maximum temperature overshoot, especially for ultra-thick laminates. The four-dwell cure profile is more effective than the two-dwell profile in significantly reducing cure time and maximum temperature overshoot.
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.

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