Polymer based composite materials have a great potential for applications in tribology as dry lubricants since the components comprising the composition may be chosen to fit to various tribological requirements. It is however well known that heat transfer and thermal effects are important for such systems. Systematic experimental studies of temperature effects are time consuming and expensive. In this work, we use a numerical homogenization approach in order to study the principal influence of key composite descriptors of fiber and particle reinforced PEEK on the homogenized heat conductivity. It turns out that the sensitivity of this key parameter on the descriptors can be nicely fitted to a regression model and thus allows for interpolation in the sense of a structure-property-relationship.

基于聚合物的复合材料具有作为干润滑剂在摩擦学中应用的巨大潜力，因为可以选择组成组合物的组分以适合各种摩擦学要求。然而，众所周知，传热和热效应对于这种系统很重要。温度效应的系统实验研究既耗时又昂贵。在这项工作中，我们使用数值均质化方法来研究纤维和颗粒增强PEEK的关键复合描述符对均质导热系数的主要影响。事实证明，此关键参数在描述符上的敏感度可以很好地拟合到回归模型，因此可以在结构属性关系的意义上进行内插。