Prediction of Mechanical Properties of to Heat Treatment by Artificial Neural Networks

Esmaeil Alibeiki, Jamal Rajabi and Javad Rajabi

Journal of Asian Scientific Research, 2012, vol. 2, issue 11, 742-746

Abstract: In such a study, for the analysis and simulation of the correlation between the mechanical properties and T6 heat treatment parameters of AL-357 alloy, an artificial neural network (ANN) model has been developed. The input parameters of the model are composed of T6 heat treatment parameters such as temperature and time of solution treatment, quench and artificial aging. The outputs of the ANN model consist of mechanical property parameters, that is the ultimate tensile strength, yield strength and elongation percentage. The model can be used to calculate the properties of AL-357 alloy as a function of T6 heat treatment variables. Using the model, the individual as well as the combined effect of inputs on mechanical properties of AL-357 alloy is simulated. The present study attained a good performance of the ANN model, and the results are consistent with experimental knowledge. Explanation of the achieved results from the materials science engineering point of view is attempted. The developed model can be utilized as a guideline for further heat treatment development.

Keywords: Artificial neural network; T6 Heat treatment; Al-357 alloy; Ultimate tensile strength; Yield strength; Elongation. (search for similar items in EconPapers)
Date: 2012
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