Prediction of slurry erosive wear behaviour of Al6061 alloy using a fuzzy logic approach

Abstract

Slurry erosive wear as a failure mechanism has significance in terms of dictating the performance of marine components. Experimental determination of this wear phenomenon for various materials in current naval applications is tedious, expensive and, in the majority of cases, not reliable. The standard experimental procedures in assessing the slurry erosive wear do not simulate the actual operating conditions. Researchers have been focusing on predictions of wear behaviour based on several hypotheses and mathematical models as a response to overcome the above mentioned obstacles. The fuzzy logic approach is a highly reliable analytical technique and therefore widely accepted and used. This paper discusses a fuzzy logic model to predict the slurry erosive wear behavior of cast aluminum 6061 (Al 6061) alloy pre and post heat treatment. The adopted fuzzy model employs hybrid-learning techniques involving a combination of both back-propagation and least-square method. Sand concentration, test duration, slurry rotation speed and impinging particle sizes served as inputs while slurry erosive wear losses were the outputs. The predicted values have been compared with published experimental data under various operating conditions. The predicted values of slurry erosive wear loss of cast aluminum 6061 alloy pre and post heat treatment are in close agreement with the experimental results. © 2013 WIT Press.