Optimization of the Micro-Hardness as nano-structureCu-Cr alloysby the mechanical alloying process with using artificial neural networks and genetic algorithm
Publish place: The 6th International Conference on Exhibitiion on Metallurgy and Materials Engineering
Publish Year: 1396
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
IMES11_229
تاریخ نمایه سازی: 7 اسفند 1396
Abstract:
A nano structural solid solution of Cu–Cr was prepared by mechanical alloying process. Artificial neural networks (ANNs) program was developed in MATLAB software to establish the relationship between the mechanical alloying input parameters, i.e. weight percentage of Cu and Cr, milling times, ball milling speed and sintering temperature and the Micro-Hardness of products as output. The established model of ANN was employed to optimize the process parameters in genetic algorithm (GA) and confirmation experiments were conducted to validate the optimized parameters that obtained from GA. the optimal condition of nanostructures alloy preparation with the highest micro hardness had been proposed with the mean prediction percentage error was lower than 4.41%.
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Authors
Amine Torabi
Master Student of Nanotechnology-Nanomaterials, Department of Materials Science and Engineering, ShahidBahonar University of Kerman, Kerman, Iran.
Malihe Zeraati
Master Student of Nanotechnology-Nanomaterials Department of Materials Science and Engineering, ShahidBahonar University of Kerman, Kerman, Iran.
Gholam Hossein Akbari
Associate professor,Material science and engineering, Department of Materials Science and Engineering, ShahidBahonar University of Kerman, Kerman, Iran.