Sensitivity Analysis and Multi-Objective Optimization Strategy of the Curing Profile for Autoclave Processed Thick...

Area of Science:

• Materials Science and Engineering
• Composite Materials Processing
• Manufacturing Process Optimization

Background:

• Autoclave processing of thick composite components faces challenges with manufacturing defects and curing efficiency.
• Accurate prediction and control of temperature profiles and degree of cure are critical for component quality.
• Existing methods may not sufficiently address the complexities of thick composite curing.

Purpose of the Study:

• To mitigate manufacturing defects and improve curing efficiency in autoclave-processed thick composite components.
• To conduct parameter sensitivity analysis and optimize the curing profile using advanced modeling techniques.
• To establish a validated finite element model for predicting thermal behavior and cure kinetics.

Main Methods:

• Development and validation of a finite element (FE) model incorporating heat transfer and cure kinetics modules.
• Application of Sobol sensitivity analysis to identify critical curing process parameters.
• Implementation of a multi-objective optimization strategy combining optimal Latin hypercube sampling, radial basis function (RBF), and non-dominated sorting genetic algorithm-II (NSGA-II).

Main Results:

• The FE model accurately predicted temperature and degree of cure (DoC) profiles.
• Laminate thickness significantly influenced maximum temperature (T) and temperature gradient (ΔT), while DoC was less affected.
• Mold material impacted temperature field uniformity, with aluminum exhibiting the highest ΔT.

Conclusions:

• Optimized curing profiles reduced maximum temperature by 2.2% and cycle time by 16.1%, maintaining a maximum DoC of 0.91.
• Dwell temperature and dwell time were identified as key parameters influencing T, ΔT, and DoC.
• This research provides valuable guidance for designing practical cure profiles for thick composite parts.