School of Engineering and Materials Science
Research Student Awards
PhD Thesis: Stiffness and fatigue failure prediction of bonded elastomer components (MPhil)
Author: NG, Wei Hann
Supervisor(s): James Busfield
Finite element analysis is used with increasing regularity as a design tool to predict the performance of elastomer components. This thesis aims to provide a fundamental evaluation of the reliability of the technique. The first part of the thesis considers the stiffness predictions of elastomer components. The appropriate choice of elements densities and stored energy functions are both considered. For the stiffness investigation a cylindrical shear mounting and a bonded elastomer bush are evaluated both experimentally and analytically using a finite element analysis technique. This thesis demonstrates that the FEA can be used to highlight some of the experimental difficulties that may be encountered when measuring component stiffness values.
Component life prediction has become an increasingly important design parameter, therefore the second part of the thesis concentrates on the prediction of fatigue failure in elastomers. A relationship exists between the magnitude of the stored energy release rate available to drive a crack and the resultant cyclic crack growth rate. It is this characteristic of the elastomer materials which allows a FEA based fracture mechanics approach to work with fracture problems of more complex three-dimensional geometries. The technique is used to calculate the relationships between the stored energy release rate for a known crack size subjected to a specified cyclic fatigue loading in a simple compression mount. Comparison is then made with crack growth rate versus stored energy release rate relationship measured on a test sample, thus allowing estimates of component lifetimes to be made.
The final part of the thesis investigates the technique of mesh rezoning which could eventually be used to resolve the problems associated with modelling the large strains at the tip of a crack in a fatigue model.