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基于PSO-BP神经网络模型的654SMO热变形行为预测
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作者 张博文 闫德安 +3 位作者 和鹏越 管煜 陈锐 刘元铭 《钢铁研究学报》 CAS CSCD 北大核心 2024年第3期368-377,共10页
针对654SMO超级奥氏体不锈钢的热变形行为进行研究,采用Arrhenius模型与粒子群算法优化的BP神经网络模型(PSO-BP神经网络)对654SMO超级奥氏体不锈钢热变形行为进行预测,将其结果进行对比获得最优模型。通过实验获得变形温度在1 000~1 20... 针对654SMO超级奥氏体不锈钢的热变形行为进行研究,采用Arrhenius模型与粒子群算法优化的BP神经网络模型(PSO-BP神经网络)对654SMO超级奥氏体不锈钢热变形行为进行预测,将其结果进行对比获得最优模型。通过实验获得变形温度在1 000~1 200℃、应变速率为0.1~10 s^(-1)条件下的真应力,并采用考虑应变修正的Arrhenius模型和PSO-BP神经网络模型对实验数据进行训练,通过计算均方相关系数(R^(2))、均方根误差(RMSE)和平均相对误差(AARE),对预测结果量化并且进行比较。最后基于实验实测数据和PSO-BP模型的预测数据得到应变为0.3和0.6的热加工图。结果表明:相比于传统的Arrhenius模型,PSO-BP神经网络模型具有更高的准确性和适用性,为654SMO的热加工工艺提供理论指导。 展开更多
关键词 654smo超级奥氏体不锈钢 热变形预测 Arrhenius本构方程 PSO-BP神经网络
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Optimization of Hot Workability in Superaustenitic Stainless Steel 654SMO 被引量:3
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作者 En-xiang PU Wen-jie ZHENG +2 位作者 Zhi-gang SONG Jin-zhong XIANG Xian-ping WEI 《Journal of Iron and Steel Research(International)》 SCIE EI CAS CSCD 2014年第10期975-982,共8页
Hot compression tests were conducted on a Gleeble-3800 machine in a temperature range of 950 to 1200 ℃ and a strain rate range of 0. 001 to 10 s-1 in order to study the hot deformation behaviour of superaustenitic st... Hot compression tests were conducted on a Gleeble-3800 machine in a temperature range of 950 to 1200 ℃ and a strain rate range of 0. 001 to 10 s-1 in order to study the hot deformation behaviour of superaustenitic stainless steel 654SMO. The results show that peak stress increases with decreasing temperature and increasing strain rate, and the apparent activation energy of this alloy was determined to be about 494 kJ/mol. The constitutive equation which can be used to relate the peak stress to the absolute temperature and strain rate was obtained. The processing maps for hot working developed on the basis of flow stress data and the dynamic materials model were adopted to op- timize the hot workability. It is found that the features of the maps obtained in the strain range of 0.2 to 1.0 are fun- damentally similar, indicating that the strain does not have a substantial influence on processing map. The combina- tion of processing map and mierostructural observations indicates that the favorable hot deformation conditions are located in two domains of processing map. The first domain occurs in the temperature range of 980 to 1035 ℃ and strain rate range of 0. 001 to 0.01 s-1 with a peak efficiency of 55%. The second domain appears in the temperature range of 1 120 to 1 180 ℃ and strain rate range of 0.3 to 3 s-1 with peak efficiency of 35%. Compared to other stable domains, the specimens deformed in these two domains exhibit full dynamic recrystallization grains with finer and more uniform sizes. An instability domain occurs at temperatures below 1 100 ℃ and strain rate above 0.1 s-1 , and flow instability is manifested in the form of flow localization. 展开更多
关键词 654smo steel superaustenitic stainless steell processing mapl hot deformationl dynamic recrystallization
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Precipitated phases of superaustenitic stainless steel 654SMO 被引量:6
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作者 Zhi-gang Song En-xiang Pu 《Journal of Iron and Steel Research(International)》 SCIE EI CAS CSCD 2017年第7期743-749,共7页
The phase diagram of superaustenitic stainless steel 654SMO was calculated by thermodynamic software and the precipitated phases in the specimens aged at 800-1100°C for 1hwere studied by methods of physicochemica... The phase diagram of superaustenitic stainless steel 654SMO was calculated by thermodynamic software and the precipitated phases in the specimens aged at 800-1100°C for 1hwere studied by methods of physicochemical phase analysis,scanning electron microscopy and transmission electron microscopy.The results showed that the size of precipitated particles increased with increasing the temperature.The amount of second phases reached the maximum value at 900°C,but decreased above 900°C.There were about eight kinds of precipitated phases in 654SMO includingσphase,Cr_2N,μphase,χphase,Laves phase,M_(23)C_6,M_6C and M_3C,in which theσphase and Cr_2N were the dominant precipitated phases. 展开更多
关键词 654smo Precipitation Superaustenitic stainless steel Precipitated phase Second phase
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