Thermoset polymers and composites are subject to several sources of uncertainty which can produce a range of cure outcomes. Recent research into stochastically modelled thermoset cure has indicated that accounting for raw material and process uncertainty can model this range of expected output parameters. However, the uncertainty quantification methods are highly test-intensive, and the results of the simulations have been validated with limited experimental data. This study proposes a simple approach to cure kinetics uncertainty quantification that can be applied to any cure kinetics model without the need for additional testing. Stochastic cure kinetics and temperature conditions for a popular out-of-autoclave carbon fibre/epoxy prepreg were used to produce output distribution functions for key cure events, and the results were validated using data from ten cure replicates. The quantified variation expected from the cure of this prepreg resulted in processing recommendations to ensure quality metrics are met during processing.
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Hall et al. (2024) studied this question.
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