Abstract Based on the experimental results in [1,2], a semi-empirical low-cycle fatigue life prediction model is constructed for a polyamide-6 (PA6) polymer, in which the rate dependence of fatigue life and the effect of ratchetting strain on the life are considered. Since the fatigue damage in PA6 is not only loading-cycle-dependent but also time-dependent, a function to describe the complicate effect of stress rate on the fatigue life is obtained. In the proposed model, the detrimental effect of ratchetting strain on the fatigue life is characterized by introducing a function of mean stress. Comparison of the predicted and experimental results shows that the proposed model presents a good prediction. Furthermore, the neural network based method is also used to correlate the low-cycle fatigue data of PA6. The results show that the established neural network based approach achieves a better prediction to the fatigue life of PA6 with the occurrence of ratchetting than that by the proposed semi-empirical model, which demonstrates a possibility to apply the neural network based machine learning method to deal with the fatigue of polymer.

中文翻译：

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考虑棘轮效应的 PA6 聚合物速率相关低周疲劳寿命预测：半经验模型和基于神经网络的方法

摘要 基于文献[1,2]中的实验结果，构建了聚酰胺6（PA6）聚合物的半经验低周疲劳寿命预测模型，其中疲劳寿命的速率依赖性和棘轮应变的影响对生活的考虑。由于 PA6 的疲劳损伤不仅与加载周期有关，而且与时间有关，因此获得了描述应力率对疲劳寿命的复杂影响的函数。在所提出的模型中，棘轮应变对疲劳寿命的不利影响通过引入平均应力函数来表征。预测结果和实验结果的比较表明，所提出的模型具有良好的预测性。此外，还使用基于神经网络的方法关联 PA6 的低周疲劳数据。