Influence of Filler Induced Cracks on the Statistical Lifetime of Rubber: A Review

Abstract

A concept for the estimation of lifetime cycles is discussed assuming non-dispersed filler particles as origins of initial cracks which propagate under dynamic load according to fatigue crack growth (FCG) characteristics until failure occurs. Reference EPDM compounds with glass spheres of well defined size show strong correlation of the fatigue to failure analysis (FFA) behavior of dumbbells with largest incorporated particles, but dependence on polymer filler interaction, too. For NR and EPDM compounds, the occurrence of incorporated large particles is investigated by computed tomography and evaluated to a flaw size statistic. Based on the assumption of initial crack sizes matching the flaw diameters and together with the characteristic material parameters from FCG analysis, a statistical concept for the prediction of FFA lifetime analysis is presented. Predictions for near-homogeneously deforming dumbbell samples with carbon black (CB) reinforced NR display a particle size distribution which in combination with FCG results allows to calculate quantitative lifetime accordant to experimental findings, i.e. compounding dependency by shorter lifetime for worse dispersion and geometry dependency by longer lifetime for smaller specimens. An extension of the prediction concept for non-homogeneous deformation states is shown through a Monte Carlo simulation varying the positions of flaws inside the sample together with a Finite Element Analysis based calculation of the accordant local J-integral value. The simulations of lifetime statistics for rotational-parabolic buffer samples made of CB filled NR or EPDM show significant effects in average value and distribution width similarly found in experiment. This lifetime prediction concept has the unique capability to take into account not only recipe controlled matrix properties as cyclic crack propagation resistivity but volume dependency and processing related dispersion state, too in a quantitative manner.