| Prediction of mechanical properties of A357 alloy using artificial neural network | |
| Alternative Title | Prediction of mechanical properties of A357 alloy using artificial neural network |
| Yang Xiawei1; Zhu Jingchuan1; Nong Zhisheng1; He Dong1; Lai Zhonghong1; Liu Ying3; Liu Fawei4 | |
| 2013 | |
| Source Publication | TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA
 |
| ISSN | 1003-6326 |
| Volume | 23Issue:3Pages:788-795 |
| Abstract | 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. |
| Other Abstract | 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. |
| Keyword | ALUMINUM-ALLOY PARAMETERS A357 alloy mechanical properties artificial neural network heat treatment parameters |
| Indexed By | CSCD |
| Language | 英语 |
| CSCD ID | CSCD:4809895 |
| Citation statistics |
Cited Times:9[CSCD]
[CSCD Record]
|
| Document Type | 期刊论文 |
| Identifier | http://ir.imr.ac.cn/handle/321006/146957 |
| Collection | 中国科学院金属研究所 |
| Affiliation | 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 |
| Recommended Citation 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. |
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