预测聚合物的短期到长期循环变形行为和疲劳寿命
Thierry Barriere1, Stani Carbillet1, Xavier Gabrion2
1CNRS, Institute FEMTO-ST, University of Franche-Comté, F-25000 Besançon, France.
Polymers
|June 27, 2024
概括
这项研究提出了一种用于预测聚合物机械行为和疲劳寿命的新模型. 该方法结合了构成和疲劳模型,以准确估计材料性能,减少了对广泛测试的需求.
科学领域:
- 材料科学 材料科学 材料科学
- 机械工程 机械工程
- 聚合物科学 聚合物科学
背景情况:
- 预测机械行为和疲劳寿命对于材料设计和测试至关重要.
- 目前的方法可能是昂贵和耗时的.
- 在聚合物中,柔性疲劳的发展,其中微裂纹形成占主导地位,是常见的.
研究的目的:
- 开发一个组合的构成和疲劳模型来预测聚合物机械行为和疲劳寿命.
- 为了捕捉大变形并整合高和低周期疲劳.
- 提供一种基于既定模型估计疲劳参数的方法.
主要方法:
- 使用霍华德-塔克雷粘性塑料模型 (1968) 制定了一个构成模型.
- 整合了基于损伤演变和移动耐力表面的疲劳模型.
- 确保该模型适用于可塑性疲劳机制,控制高达90%的疲劳寿命.
主要成果:
- 拟议的模型捕捉了大变形,并整合了高和低周期疲劳.
- 损伤演变表现出低循环和高循环疲劳的明显异征,具有定义的过渡曲率.
- 模型参数与已建立的Basquin和Coffin-Manson参数保持一致,类似于金属.
结论:
- 开发的方法提供了一种可靠的方法来预测聚合物疲劳寿命和机械行为.
- 该模型通过避免循环计数方法来简化负载历史记录的跟踪.
- 这一框架促进了准确的材料设计,并减少了对具有延展性疲劳的聚合物依赖经验测试的依赖.
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