...
首页> 外文期刊>Neural computing & applications >An artificial neural-network model for impact properties in X70 pipeline steels
【24h】

An artificial neural-network model for impact properties in X70 pipeline steels

机译:X70管线钢冲击性能的人工神经网络模型

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

An artificial neural-network (ANN) model has been developed for the analysis and simulation of the correlation between the mechanical properties and composition and thermomechanical treatment parameters of high strength, low alloy steels. The input parameters of the model consist of alloy compositions (C, Si, Mn, P, S, Cu, Ni, Cr, Mo, Ti, V, Nb, Ca, Al, B) and tensile test results (yield strength, ultimate tensile strength, percentage elongation). The outputs of the ANN model include impact energy (-10℃). The model can be used to calculate the properties of low alloy steels as a function of alloy composition and thermomechanical treatment variables. The current study achieved a good performance of the ANN model, and the results are in agreement with experimental knowledge.
机译:已经开发了一种人工神经网络(ANN)模型,用于分析和模拟高强度低合金钢的力学性能,成分和热机械处理参数之间的相关性。模型的输入参数包括合金成分(C,Si,Mn,P,S,Cu,Ni,Cr,Mo,Ti,V,Nb,Ca,Al,B)和拉伸试验结果(屈服强度,极限强度)。抗拉强度,伸长率百分比)。 ANN模型的输出包括冲击能量(-10℃)。该模型可用于根据合金成分和热机械处理变量来计算低合金钢的性能。本研究取得了良好的神经网络模型性能,其结果与实验知识相吻合。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号