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- 电子邮箱：masoudinejad@uestc.edu.cn
- 入职时间：2019-07-03
- 所在单位：机械与电气工程学院
- 学历：博士研究生毕业
- 办公地点：Room 313, KeYanLou A, Qingshuihe Campus
- 性别：男
- 联系方式：(+86)19141004306
- 学位：工学博士学位
- 在职信息：博士后出站
- 主要任职：Postdoctoral Research Fellow
- 毕业院校：马什哈德菲尔多西大学
- 曾获荣誉：-International Postdoctoral Exchange Fellowship, Office of China Postdoc Council (OCPC), China, Summer 2019.
-Distinguished researcher selected by University of Electronic Science and Technology of China-Postdoctoral fellowship, Summer 2019.
论文成果
Optimization of fatigue life of pearlitic Grade 900A steel based on the combination of genetic algorithm and artificial neural network
- 点击次数：
- 所属单位：University of Electronic Science and Technology of China
- 刊物所在地：International Journal of Fatigue
- 关键字：Artificial neural network; Fatigue life; Genetic algorithm; Railway rail; Stress intensity factor
- 摘要：In this paper, the fatigue life of pearlitic Grade 900A steel used in railway applications is investigated. To predict the fatigue life of pearlitic Grade 900A steel based on the number of cycles of the particular stress level in the load block, occurrence ratio and overload ratio, a feed-forward neural network is designed. The results of this artificial neural network are compared to the surface fitting method. Then sensitivity analysis is applied to the obtained artificial neural network values to measure the effect of each input parameter on the fatigue life. Finally, the genetic...
- 全部作者：,,,,
- 论文类型：Journal Paper
- 论文编号：106975
- 学科门类：工学
- 一级学科：机械工程
- 卷号：162
- 页面范围：106975
- ISSN号：0142-1123
- 是否译文：否
- 发表时间：2022-05-06