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On the characterization of tensile creep resistance of polyamide 66 nanocomposites.Part II:Modeling and prediction of long-term performance

机译:聚酰胺66纳米复合材料拉伸抗蠕变性的表征。第二部分:长期性能的建模和预测

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The Part I of this study [Yang JL,Zhang Z,Schlarb AK,Friedrich K.Polymer 2006;47:2791-801] provided systematic experiments and general discussions on the creep resistance of polyamide 66 nanocomposites.To promote these works,here we present some modeling and prediction attempts in order to further understand the phenomena and mechanisms.Both a viscoelastic creep model named Burgers(or four-element model)and an empirical method called Findley power law are applied.The simulating results from both models agree quite well with the experimental data.An additional effort is conducted to understand the structure-property relationship based on the parameter analysis of the Burgers model,since the variations in the simulating parameters illustrate the influence of nanofillers on the creep performance of the bulk matrix.Moreover,the Eyring stress-activated process is taken into account by considering the activation volume.Furthermore,in order to predict the long-term behavior based on the short-term experimental data,both the Burgers and Findley models as well as the time-temperature superposition principle(TTSP)were employed.The predicting capability of these modeling approaches is compared and the Findley power law is preferred to be adopted.Master curves with extended time scale are constructed by applying TTSP to horizontally shift the short-time experimental data.The predicting results confirm the enhanced creep resistance of nanofillers even at extended long time scale.
机译:本研究的第一部分[Yang JL,Zhang Z,Schlarb AK,Friedrich K.Polymer 2006; 47:2791-801]对聚酰胺66纳米复合材料的抗蠕变性提供了系统的实验和一般性的讨论。为了进一步理解现象和机理,本文进行了一些建模和预测尝试。采用了名为Burgers的粘弹性蠕变模型(或四元模型)和称为Findley幂定律的经验方法,两种模型的仿真结果吻合得很好。基于Burgers模型的参数分析,由于模拟参数的变化说明了纳米填料对块体基体蠕变性能的影响,因此需要进行额外的工作以基于Burgers模型的参数分析来了解其结构与性质之间的关系。通过考虑激活量来考虑Eyring应力激活过程。此外,为了预测基于短期的长期行为长期实验数据,同时使用了Burgers模型和Findley模型以及时温叠加原理(TTSP)。比较了这些建模方法的预测能力,并优选采用Findley幂定律。通过应用TTSP对短时实验数据进行水平移动来构建时标,预测结果证实了即使在较长的时标下纳米填料的抗蠕变性也有所增强。

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