شماره ركورد كنفرانس :
4259
عنوان مقاله :
Prediction Micro-Hardness of Cu Nanocomposite by Using Artificial Neural Network with Characterization Effective Parameters in Mechanical Alloying
پديدآورندگان :
Mirahmadi Babaheydari Reza mirahamdireza@yahoo.com Master student, Material science and engineering, Shahid Bahonar University of kerman, Iran, , Akbari G.H ghh.akbari@gmail.com Associate Professor, Material science and engineering, Shahid Bahonar University of kerman, Iran , Mirabootalebi Seyed Oveis oweiys@gmail.com Master student, Material science and engineering, Shahid Bahonar University of kerman, Iran
كليدواژه :
Cu nanocomposite , artificial neural network , prediction microhardness , mechanical alloying
عنوان كنفرانس :
اولين كنفرانس ملي نانو ساختارها، علوم و مهندسي نانو
چكيده فارسي :
Cu nano-composites have different properties and therefore have various applications. Generally; reinforcement phase, specify most properties of nanocomposite, such as micro-hardness that is one of the essential parameter which determinate application of them. In this paper we predict micro-hardness of Cu nano-composite by Artificial Neural Network method. First determinate effective parameters on micro-hardness of Cu nano-composite which produced by mechanical alloying method and then; efficient factors such as: reinforcement hardness, sintering time and temperature; selected as input and micro-hardness of Cu nano-composite choice as output. Finally; effectiveness parameters on hardness calculated and predicted micro-hardness of Cu nano-composite with %6.2 mean percentage error. so by using this method with high approximation can prediction microhardness of Cu nano-composite without any experiments, as well as; specified level of effective parameters, by sensitivity analysis.
