董彦，龚志翔，肖国华
钢铁研究学报
以指导无取向电工钢热轧工艺为目的，采用Gleeble 1500热模拟试验机进行高温等温压缩，在应变速率为0.01~10s-1和变形温度500~1200℃条件下，对试样进行试验研究。结果表明：随着变形温度的升高，在回复与再结晶过程中发生α-Fe向γ-Fe相的?洌贾挛忍鞅溆αΤ氏帧耙斐！北浠２捎肁rrhenius关系模型，模型参数能很好的与试验结果相吻合。利用模型分别计算得500~800℃时，应力水平因子α=0.0390MPa-1，应力指数n=7.93，结构因子A=1.9×1018 s-1，热变形激活能Q=334.8kJ/mol；1050~1200℃时，应力水平因子α=0.1258MPa-1，应力指数n=5.29，结构因子A=1.0×1028 s-1，热变形激活能Q=769.9kJ/mol。
关键词:
无取向
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electrical steel
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high temperature
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plastic deformation
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flow stress
张志正
,
王春旭
,
黄顺喆
,
厉勇
,
刘宪民
,
周晓龙
机械工程材料
采用Gleeble-3800型热模拟试验机在温度1 173～1 473 K、应变速率0.01～10 s-1的条件下,对镍微合金化9310钢的高温热变形前行为进行了研究,得到了试验钢的高温流变曲线,并用光学显微镜观察了试验钢变形前后的显微组织.结果表明:镍微合金化9310钢的流变应力和峰值应变随着变形温度的升高和应变速率的降低而减小;试验钢在真应变为0.9,应变速率为0.01～10 s-1的条件下,随着应变速率的提高,其发生完全动态再结晶的温度也逐渐升高;测得试验钢的热变形激活能Q值为362.649 kJ·mol-1,并建立了其热变形方程以及动态再结晶条件下峰值应变σp与Zener-Hollomon因子的关系式.
关键词:
镍微合金化
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9310钢
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流变应力
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热变形激活能
,
热变形行为
关小军
,
付杰
,
禹宝军
,
王丽君
材料热处理学报
为了改善动态再结晶恒形核率模型的模拟精度,基于动态再结晶模拟理论和闭环控制原理,提出了一种采用实验与模拟的流变应力差的闭环控制和黄金搜索法来确定真实瞬态形核率的方法,通过HPS485wf钢动态再结晶过程的元胞自动机仿真研究检验了它的合理性和应用效果.结果表明,这一方法合理、可行,可有效确定瞬态形核率,使得动态再结晶流变应力的模拟精度及其稳定性显著改善,并有益于提高其面积分数的模拟精度.
关键词:
动态再结晶
,
形核率
,
元胞自动机
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模拟
,
流变应力
JIANG Zhonghao
,
GUAN Zhenzhong
,
ZHANG ZuomeiChangchun Institute of Optics and Fine Mechanics
,
Chinese Academy of Sciences
,
Changchun
,
ChinaLIA N JiansheJilin University of Technology
,
Changchun
,
China
金属学报(英文版)
Bused on the deformation model of dual phase steels, an expression for the stress of martensite in dual phase steels is derived, it predictes that the onset of plastic deformation of martensite (transition strain) depends on the strain hardening of ferrite and on the strength of martensile. The relationship between the flow stress and microstructural parameters of a 0.12C-0.9Mn dual phase steel was investigated using the expression for the flow stress of dual phase steel[1] . By calculating the stress ratio and the stress-strain partition coefficient, the loud transition and the stress-strain partition between two phases are studied. It shows that the deformation of dual phase steel lies between the isostress and isostrain states and the stress-strain pratition changes continuously during the deloramtion.
关键词:
dual phase steel
,
null
,
null
,
null
J. T. Liu
,
H.B. Chang
,
R.H. Wu
,
T. Y. Hsu(Xu Zuyao) and X.R. Ruan( 1)Department of Plasticity Technology
,
Shanghai Jiao Tong University
,
Shanghai 200030
,
China 2)School of Materials Science and Engineering
,
Shanghai Jiao Tong University
,
Shanghai 200030
,
China)
金属学报(英文版)
The hot deformation behavior of TI (18W-4Cr-1V) high-speed steel was investigated by means of continuous compression tests performed on Gleeble 1500 thermomechan- ical simulator in a wide range of tempemtures (950℃-1150℃) with strain rotes of 0.001s-1-10s-1 and true strains of 0-0. 7. The flow stress at the above hot defor- mation conditions is predicted by using BP artificial neural network. The architecture of network includes there are three input parameters:strain rate,temperature T and true strain , and just one output parameter, the flow stress ,2 hidden layers are adopted, the first hidden layer includes 9 neurons and second 10 negroes. It has been verified that BP artificial neural network with 3-9-10-1 architecture can predict flow stress of high-speed steel during hot deformation very well. Compared with the prediction method of flow stress by using Zaped-Holloman parumeter and hyperbolic sine stress function, the prediction method by using BP artificial neurul network has higher efficiency and accuracy.
关键词:
T1 high-speed steel
,
null
,
null
,
null
,
null
J. T.Niu
,
L.J.Sun and P.Karjalainen 1) Harbin Institute of Technology
,
Harbin 150001
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China 2) University of Oulu
,
FIN-90571
,
Oulu
,
Finland
金属学报(英文版)
For the great significance of the prediction of control parameters selected for hot-rolling and the evaluation of hot-rolling quality for the analysis of prod uction problems and production management, the selection of hot-rolling control parameters was studied for microalloy steel by following the neural network principle. An experimental scheme was first worked out for acquisition of sample data, in which a gleeble-1500 thermal simolator was used to obtain rolling temperature, strain, stain rate, and stress-strain curves. And consequently the aust enite grain sizes was obtained through microscopic observation. The experimental data was then processed through regression. By using the training network of BP algorithm, the mapping relationship between the hotrooling control parameters (rolling temperature, stain, and strain rate) and the microstructural paramete rs (austenite grain in size and flow stress) of microalloy steel was function appro ached for the establishment of a neural network-based model of the austeuite grain size and flow stress of microalloy steel. From the results of estimation made with the neural network based model, the hot-rolling control parameters can be effectively predicted.
关键词:
microalloy steel
,
null
,
null
,
null
,
null
,
null
J.M. Zhang
,
L.Z. Ma
,
J. Y. Zhuang
,
Q. Deng
,
J.H Du and Z. Y Zhong(Department of Superalloys
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Central Iron & Steel Research Institute
,
Beijing 100081
,
China)P. Janschek(Thyssen Umformtechnik GMBH
,
42859 Remscheid
,
Germany Manuscript received 26 August 1996)
金属学报(英文版)
Isothermal constant speed compression tests of superalloy IN718 were conducted using a computer-controlled MTS machine at temperatures from 960 to 1040℃, with initial strain rates from 0.001 s~(1) to 1.0 s~(1) and engineering strain from 0.1 to 0. 7.The variations of flow stress with deformation temperature, initial strain rate and engineering strain were analyzed in the paper. It was found that there was an obvious power-law relationship between flow stress and initial strain rate, which showed the behavior of strain rate hardening of superalloy IN718 at elevated temperatures.The relationship between flow stress and temperature could be described by an inverse trigonometric function.And the turning point on the curve may be related to the behavior of δ phase at 1000℃. Meanwhile, it was found that there was a complicated relationship between flow stress and strain,which was indicative of the comprehensive effect of work hardening and dynamic softening on flow stress during hot deformation. From the results of these tests, a constitutive equation of superalloy IN718 was developed.
关键词:
: constitutive relationship
,
null
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null
