Wear has a vast technological and economic significance because of the manner in which is alters the shape and performance of all things subjected to it. To attempt to predict the magnitude of wear via computational methods, investigations of the wear characteristics surrounding a specific system is essential. Choosing a specific system minimises the permissible variables, keeping this previously undeveloped area of research from being overly complex.
A collection of related information was gathered to better define and understand the system chosen for this research. This system was the second coal reject drain-rinse screen at the Ebenezer coal preparation washplant. The wear occurring here was caused by the reject material abrading the surface of the polyurethane screen.
Literature describing the computer modelling of such large dynamic systems was scarce. All the information found, however suggested that specific properties of the materials which make up the system was required in order for it to be properly simulated. Particle Flow Code (PFC), which was the programming code used in the modelling component of this research, was no different. On a global scale, wear itself is well-recognised and is typically defined by a wear rate equation. This equation illustrates that wear rates are related to the hardness of the contacted surface, sliding velocity, object interface pressure and an intrinsic wear coefficient. Finding these and other parameters required testwork to be conducted.
The results obtained through the completion of experimental procedures demonstrated that the wear experienced upon the screen was measurable. Visual inspections of the system after several weeks of operation also provided evidence of this. Other features of the system which required clarification for use in the computer
model was the reject material and polyurethanes bulk and shear moduli and frictional properties. These values were of particular interest as wear is related to friction, and interface pressure is related to the materials moduli.
Wear characteristics and other wear criteria were defined and determined. These values were then implemented in a two dimensional model using PFC, which can in future be utilised to predict the wear rates of similar wearing systems.