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Optimal curing for thermoset matrix composites: Thermochemical and consolidation considerations
Author(s) -
Li Min,
Tucker Charles L.
Publication year - 2002
Publication title -
polymer composites
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.577
H-Index - 82
eISSN - 1548-0569
pISSN - 0272-8397
DOI - 10.1002/pc.10473
Subject(s) - thermosetting polymer , materials science , curing (chemistry) , composite material , epoxy , consolidation (business) , finite element method , transfer molding , optimal design , composite number , volume fraction , computer science , structural engineering , mold , accounting , machine learning , engineering , business
A design sensitivity method is used to find optimal autoclave temperature and pressure histories for curing of thermoset‐matrix composite laminates. The method uses a finite element simulation of the heat transfer, curing reaction, and consolidation in the laminate. Analytical sensitivities, based on the direct differentiation method, are used within the finite element simulation to find the design sensitivities, i.e., the derivatives of the objectives function and the constraints with respect to the design variables. Standard gradient‐based optimization techniques are then used to systematically improve the design, until an optimal process design is reached. In this study the objective is to minimize the total time of the cure cycle, while the constraints include a maximum temperature in the laminate (to avoid thermal degradation) and a maximum deviation of the final fiber volume fraction from its target value (to achieve proper consolidation). The simulations of curing process are performed for EPON 862/W epoxy under a conventional cure cycle, for both thin and thick parts. Time‐optimal cure cycles are found using the optimization program. Simulations of fast‐curing cycles are also examined. The optimal cycles are similar in form to conventional cure cycles, but give substantially shorter cure times. The entire scheme works automatically and efficiently, simultaneously adjusting multiple design variables at each iteration.