Prediction of mechanical properties of A357 alloy using artificial neural network

IMR OpenIR

	Prediction of mechanical properties of A357 alloy using artificial neural network
其他题名	Prediction of mechanical properties of A357 alloy using artificial neural network
	Yang Xiawei 1; Zhu Jingchuan 1; Nong Zhisheng 1; He Dong 1; Lai Zhonghong 1; Liu Ying 3; Liu Fawei 4
	2013
发表期刊	TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA
ISSN	1003-6326
卷号	23 期号:3 页码:788-795
摘要	The workpieces of A357 alloy were routinely heat treated to the T6 state in order to gain an adequate mechanical property. The mechanical properties of these workpieces depend mainly on solid-solution temperature, solid-solution time, artificial aging temperature and artificial aging time. An artificial neural network (ANN) model with a back-propagation (BP) algorithm was used to predict mechanical properties of A357 alloy, and the effects of heat treatment processes on mechanical behavior of this alloy were studied. The results show that this BP model is able to predict the mechanical properties with a high accuracy. This model was used to reflect the influence of heat treatments on the mechanical properties of A357 alloy. Isograms of ultimate tensile strength and elongation were drawn in the same picture, which are very helpful to understand the relationship among aging parameters, ultimate tensile strength and elongation.
其他摘要	The workpieces of A357 alloy were routinely heat treated to the T6 state in order to gain an adequate mechanical property. The mechanical properties of these workpieces depend mainly on solid-solution-temperature, solid-solution time, artificial aging temperature and artificial aging time. An artificial neural network (ANN) model with a back-propagation (BP) algorithm was used to predict mechanical properties of A357 alloy, and the effects of heat treatment processes on mechanical behavior of this alloy were studied. The results show that this BP model is able to predict the mechanical properties with a high accuracy. This model was used to reflect-the-influence-of heat treatments on-the-mechanical-properties of A357 alloy. Isograms of ultimate tensile strength and elongation were drawn in the same picture, which are very helpful to understand the relationship among aging parameters, ultimate tensile strength and elongation.
关键词	ALUMINUM-ALLOY PARAMETERS A357 alloy mechanical properties artificial neural network heat treatment parameters
收录类别	CSCD
语种	英语
CSCD记录号	CSCD:4809895
引用统计	被引频次：9[CSCD] [CSCD记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/146955
专题	中国科学院金属研究所
作者单位	1.Harbin Institute Technol, Natl Key Lab Precis Hot Proc Met, Harbin 150001, Peoples R China 2.Harbin Institute Technol, Sch Mat Sci & Engn, Harbin 150001, Peoples R China 3.Beijing Hangxing Machine Mfg Co, Beijing 100013, Peoples R China 4.中国科学院金属研究所
推荐引用方式 GB/T 7714	Yang Xiawei,Zhu Jingchuan,Nong Zhisheng,et al. Prediction of mechanical properties of A357 alloy using artificial neural network[J]. TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA,2013,23(3):788-795.
APA	Yang Xiawei.,Zhu Jingchuan.,Nong Zhisheng.,He Dong.,Lai Zhonghong.,...&Liu Fawei.(2013).Prediction of mechanical properties of A357 alloy using artificial neural network.TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA,23(3),788-795.
MLA	Yang Xiawei,et al."Prediction of mechanical properties of A357 alloy using artificial neural network".TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA 23.3(2013):788-795.