Fracture in metal matrix composites

• Main Author: Ganguly, Partha
• Format: Others
• Language: English
• Published: 2009
• Online Access: http://hdl.handle.net/2429/12984

Particulate metal matrix composites (MMCs) offer a number of property incentives over metallic alloys. However, their applicability as engineering materials is limited by their low ductility. Experimentally, the MMC ductility has been observed to be affected by the spatial distribution of the reinforcements, particularly by the presence of regions of high reinforcement density or clusters. The goal of the present work was to develop a predictive understanding of the effect of reinforcement distribution on the MMC failure mechanism, through a combination of numerical simulations and model experiments. Numerical models (including finite element models) were constructed to study the effect of distribution (both random and clustered) on the reinforcement stress in undamaged and damaged composites. The models were verified by experimental measurement of the reinforcement stress and the composite stress in AA6O6I - AI₂O₃ and Cu-W composites. The models showed that proximity of the reinforcements along the line of loading may enhance reinforcement stress in an undamaged composite, and cause premature damage nucleation. On the other hand, proximity to a damaged reinforcement along a direction perpendicular to the line of loading was observed to enhance the stress in the neighboring particles, and may lead to their failure. Thus, the overall MMC failure mechanism may be affected by reinforcement proximity in all directions. A suitable parameter proposed for characterizing such dependence is the local reinforcement area-fraction. The local area-fraction maps were constructed for various computer generated microstructures, using a Voronoi tessellation algorithm. The maps were able to distinguish between the various patterns, and determine important cluster characteristics, like the cluster shape, size and position. These maps are expected to aid microstructure-property correlation in MMCs, and develop an 'intelligent' framework for microstructural engineering of these materials for ductility enhancement. === Applied Science, Faculty of === Materials Engineering, Department of === Graduate