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.

中文翻译：

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不确定条件下非高压釜环氧复合材料固化周期的随机建模

热固性聚合物和复合材料受到多种不确定性的影响，这些不确定性可能会产生一系列的固化结果。最近对随机建模热固性固化的研究表明，考虑原材料和工艺的不确定性可以对这一范围的预期输出参数进行建模。然而，不确定性量化方法的测试密集度很高，并且模拟结果已通过有限的实验数据得到验证。这项研究提出了一种简单的固化动力学不确定性量化方法，可应用于任何固化动力学模型，无需额外的测试。使用流行的非高压釜碳纤维/环氧树脂预浸料的随机固化动力学和温度条件来生成关键固化事件的输出分布函数，并使用十次固化重复的数据验证结果。该预浸料固化过程中预期的量化变化产生了加工建议，以确保加工过程中满足质量指标。