Size effect in curing optimization for thick composite laminates

The component size has a profound effect on curing optimization for thick composite laminates where the curing behavior is closely related to the thickness. The present study was set out to correlate the constraints, optimization objects and curing parameters with varying component size. The Pearson's correlation coefficient was adopted to illuminate the sensitivity of curing parameters to specimen's size. The results indicate that the increase of the first dwell temperature (CT1) and time (t1) can improve the curing quality and the increase of the first heating rate (r1) can significantly reduce the cure time. The selection criterion of the second dwell temperature (CT2) and heating rate (r2) depend heavily on two constraints and component size. It was found that the Pearson's correlation coefficient can qualitatively reflect the change of curing parameters and provide guidance for the optimization of curing process.

Automated summary

This study aimed to investigate the impact of component size on curing optimization for thick composite laminates, where the curing behavior is closely related to the thickness. The Pearson's correlation coefficient was used to examine the sensitivity of curing parameters to specimen size and establish the relationship between constraints, optimization objectives, and curing parameters. The results showed that increasing the first dwell temperature (CT1) and time (t1) improved curing quality, while increasing the first heating rate (r1) significantly reduced curing time. The selection criteria for the second dwell temperature (CT2) and heating rate (r2) heavily depended on two constraints and component size. The study found that the Pearson's correlation coefficient qualitatively reflected the changes in curing parameters and provided guidance for curing process optimization.