Abstract
With the increasing demand for light-weight materials in the emerging industrial applications, fabrication of aluminium matrix composites is necessary. In this context, Aluminium Alloy (AA 1100) alloys reinforced with 6% of RHAp, BAp, CSAp, ZnOp, ESp matrix composites were fabricated by liquid metallurgy technique. Aluminium 1100 alloys series unalloyed (pure) composition was used primarily in the automobile, electrical and chemical industries. The composites were characterized by a hardness test, tensile test, and wear test. With 6% of various reinforced materials added, the density of the composites decreased, whereas the hardness increased. It is observed that wear loss of Aluminium Matrix Composites (AMC) reduced while sliding speed, load, sliding time increased, compared to pure aluminium 1100 alloy. This work aims to predict experimentally the parameters affecting the brinell hardness number, tensile strength, and wear loss rise due to friction. Artificial Neural Network (ANN) model was developed using the MATLAB 10 program for predicting the wear loss and coefficient of friction. The ANN model was successful, which shows that there is a high ability to predict the wear loss as well as the results of the model corresponding with the experimental results.
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Nagaraj, A., Gopalakrishnan, S. A Study on Mechanical and Tribological Properties of Aluminium 1100 Alloys 6% of RHAp, BAp, CSAp, ZnOp and Egg Shellp Composites by ANN. Silicon 13, 3367–3376 (2021). https://doi.org/10.1007/s12633-020-00731-8
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DOI: https://doi.org/10.1007/s12633-020-00731-8