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Effect of Chromium on CCT Diagrams of Novel Air-Cooled Bainite Steels Analyzed by Neural Network 被引量:4
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作者 YOU Wei XU Wei-hong +2 位作者 LIU Ya-xiu BAI Bing-zhe FANG Hong-sheng 《Journal of Iron and Steel Research International》 SCIE EI CAS CSCD 2007年第4期39-42,共4页
The quantitative effects of chromium content on continuous cooling transformation (CCT) diagrams of novel air-cooled bainite steels were analyzed using artificial neural network models. The results showed that the c... The quantitative effects of chromium content on continuous cooling transformation (CCT) diagrams of novel air-cooled bainite steels were analyzed using artificial neural network models. The results showed that the chromium may retard the high and medium-temperature martensite transformation. 展开更多
关键词 novel air-cooled bainite steel CCT diagram artificial neural network chromium content quantitative effect
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Quantitative analysis of Ni effect on CCT diagrams of novel air-cooled bainite steels using artificial neural network models
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作者 Weihong Xu Wei You +2 位作者 Yaxiu Liu Bingzhe Bai Hongsheng Fang 《Journal of University of Science and Technology Beijing》 CSCD 2005年第5期410-415,共6页
The quantitative effect of Ni content on continuous cooling transformation (CCT) diagrams of novel air-cooled bainite steels was analyzed using artificial neural network models. The results showed that Ni may retard... The quantitative effect of Ni content on continuous cooling transformation (CCT) diagrams of novel air-cooled bainite steels was analyzed using artificial neural network models. The results showed that Ni may retard the high- and medium-temperature transformation and martensite transformation. The results conform to the materials science theories. 展开更多
关键词 novel air-cooled bainite steels NICKEL CCT diagrams artificial neural network
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Mn-Series Low-Carbon Air-Cooled Bainitic Steel Containing Niobium of 0.02% 被引量:4
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作者 FENG Chun FANG Hong-sheng ZHENG Yan-kang BAI Bing-zhe 《Journal of Iron and Steel Research International》 SCIE EI CAS CSCD 2010年第4期53-58,共6页
A new hot rolled low-carbon air-cooled bainitic steel containing Nb of 0.02% has been developed based on alloying design of the grain boundary allotriomorphic ferrite (FGBA)/granular bainite (BG) duplex steel. The... A new hot rolled low-carbon air-cooled bainitic steel containing Nb of 0.02% has been developed based on alloying design of the grain boundary allotriomorphic ferrite (FGBA)/granular bainite (BG) duplex steel. The as-rolled microstructure and mechanical properties of bainitie steel containing Nb of 0. 02% were investigated by tensile test, optical microscopy (OM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The results show that adding 0.02 % of Nb obviously improves the strength without sacrificing toughness of the FGBA/BG steel. Adding 0.02% of Nb not only refines the grain boundary allotriomorphic ferrite grains but also promotes the refinement of granular bainite including its bainitic ferrite and M/A island. Any Nb(C,N) has been hardly observed in the steel containing Nb of 0.02%. It is suggested that the strengthening mechanism of Nb of 0.02% can be mainly attributed to the effect of Nb in solution (solute drag-like effect) on the phase transformation rather than the precipitation strengthening of Nb(C, N) particles. 展开更多
关键词 low-carbon air-cooled bainitic steel NIOBIUM MICROSTRUCTURE mechanical property
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用人工神经网络分析Ni含量对新型空冷贝氏体钢CCT图的定量影响
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作者 刘亚秀 徐卫红 +2 位作者 由伟 白秉哲 方鸿生 《华北科技学院学报》 2007年第1期52-57,84,共7页
用人工神经网络模型分析了Ni含量对新型空冷贝氏体钢的连续冷却转变(CCT)图的定量影响。首先测试了神经网络模型的预测性能,对几种新型空冷贝氏体钢CCT图的预测结果和实测结果的比较说明我们设计的ANN模型具有较高的预测精度和可靠性。... 用人工神经网络模型分析了Ni含量对新型空冷贝氏体钢的连续冷却转变(CCT)图的定量影响。首先测试了神经网络模型的预测性能,对几种新型空冷贝氏体钢CCT图的预测结果和实测结果的比较说明我们设计的ANN模型具有较高的预测精度和可靠性。然后用人工神经网络模型分析了Ni含量对CCT图的定量影响。结果表明,Ni含量增加会使钢的奥氏体形成温度下降,推迟高温转变、中温转变和马氏体转变。人工神经网络模型的计算结果与材料科学理论相符。 展开更多
关键词 新型空冷贝氏体钢 CCT图 人工神经网络 Ni含量 定量影响
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