Abstract

Removal of surface material by action of impinging particle is known as erosion. Material removal mechanisms in ductile and brittle materials are completely different. Material removal in ductile material occurs primarily through cutting and deformation, whereas, formation of cracks and crack propagation are believed to be responsible for material removal in brittle materials. Based on the interaction between surface and particle, material is removed through a combination of cutting and deformation. Scanning electron Microscopes (SEM) are usually used for analysis of wear mechanisms responsible for material removal in any wear situations. Recognizing dominant wear mechanism as well as quantifying effects of individual impact can help in developing predictive models for specific application. Even though the SEM can clearly identify the wear mechanisms, the analysis is primarily qualitative in nature. As a result the application of the wear mechanisms into predictive models remains sensitive to the perception of the analyst. To overcome this limitation, a novel technique has been developed to analyse surface craters and to quantify the effects of cutting and deformation at the University of Newcastle using. Laser Scanning Confocal Microscope (LSCM) is a conventional microscope equipped with a laser light source, a laser scanning head and an automatic focusing stage. Through a special technique, called optical sectioning, three dimensional image of any surface feature can be developed using the LSCM. Single particle impact tests were conducted on a high pressure gas gun to study the effects of particle velocity and impact angles on ductile material. Impact tests on aluminium and mild steel surfaces with particle sizes from 50 to 200 μm and impact velocity of up to 200 m−1s have been conducted. Using specially developed software to work with the LSCM, the depth of crater and the crater volumes were determined. Particle impact parameters and displacement volumes are used to determine unit energy factors for material removal, a critical parameter in predictive models. Finally the advantages and limitations of using the technique have been discussed with future challenges to make the technique more effective.

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