Study on the Flow Stress Curve of the Warm Deformation of Medium Carbon Steel

2012 ◽  
Vol 535-537 ◽  
pp. 517-520 ◽  
Author(s):  
Zhi Jie Li ◽  
Yan Peng ◽  
Hong Min Liu ◽  
Li Zi Xiao ◽  
Su Fen Wang ◽  
...  

The warm compression experiment of medium carbon steel was conducted using the Gleeble-3500 thermal/mechanical simulator system. By the experiment, the warm deformation of medium carbon steel was studied within the temperature (500~700°C) and the strain rate (0.001~10s-1). The results indicate that the flow stress was increasing with the lowering temperature and the higher strain rate. And the stress-strain curves could be divided into four parts, including four stage of the Strain-Hardening, the First Softening, the Strong Softening, and the Steady Deformation. Dynamic recovery softening has little effect on the flow stress. The peak stress was caused by kink and fracture of the lamellar cementite. Strong softening stage was longer than other one, while its softening influence was stronger compared with hot deformation.

Metals ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 77
Author(s):  
Hong-Bin Li ◽  
Lifeng Fan ◽  
Lian-Sheng Chen

Influence of temperature scheme on the microstructure and properties variation of medium carbon steel warm deformation was studied with testing equipment of Gleeble-3500, SEM, TEM, EBSD, and φ350 reversal rolling mill. The results show that the temperature of 650 facilitates the formation of ultrafine homogeneous microstructure. The microstructure formed during temperature range of 650–700 °C is relative homogeneous and fine. The mechanical properties of warm rolling are influenced by the cooling modes. The lower cooling rate is benefit to the combination of strength and ductility.


1992 ◽  
Vol 114 (1) ◽  
pp. 116-123 ◽  
Author(s):  
K. P. Rao ◽  
E. B. Hawbolt

Empirical or semi-empirical stress-strain relationships are of limited applicability because (i) they require a large number of constants to represent the effect of process variables, (ii) they are not able to adequately describe the typical hot deformation characteristics i.e., strain hardening at lower strains and steady state flow stress at higher strains, and (iii) they are not able to provide reliable extrapolation. In the present study, flow curves for hot deformation of a medium carbon steel in compression were obtained using a computer controlled thermo-mechanical simulator. The flow stress data were analyzed using three Arrhenius-type equations, each representing the flow stress in terms of strain rate and temperature at different strain levels. It was found that the hyperbolic-sine equation represented the data very well; each of the different activation parameters of this equation varied systematically with strain, and could be satisfactorily described using a power relationship. Using these proposed relationships the flow stress can be described in terms of the process variables—strain, strain rate and temperature—in an explicit fashion of use in finite-element analysis of hot deformation processes.


2020 ◽  
Vol 977 ◽  
pp. 163-168
Author(s):  
Mohanraj Murugesan ◽  
Dong Won Jung

Isothermal tensile test of medium carbon steel material was conducted on a computer controlled servo-hydraulic testing machine at the deformation temperatures (923 to 1223 K) and the strain rates (0.05 to 1.0 s-1). Using the experimental data, the artificial neural network (ANN) model with a back-propagation (BP) algorithm was proposed to predict the hot deformation behavior of medium carbon steel material. For the model training and testing purpose, deformation temperature, strain rate and strain data were considered as inputs and in addition, the flow stress data were used a targets. Before running the neural network, the test data were normalized to effectively run the problem and after solving the problem, the obtained results were again converted in order to achieve the actual data. According to the predicted results, the coefficient of determination (R2) and the average absolute relative error between the predicted flow stress and the experimental data were determined as 0.997 and 0.913%, respectively. In addition, by evaluating each test conditions, it was found that the average absolute relative error based on an ANN model varied from 0.55% to 1.36% and moreover, the results showed the better predictability compared with the measured data. Overall, the trained BP-ANN model is found to be much more efficient and accurate by means of flow stress prediction with respect to the experimental data for an entire tested conditions.


2006 ◽  
Vol 510-511 ◽  
pp. 518-521 ◽  
Author(s):  
Jae-Young An ◽  
Young Jae Kwon ◽  
S.I. Kim ◽  
Duk Lak Lee ◽  
Yeon Chul Yoo

The relationships between flow stress curve and microstructure evolution in strain induced dynamic phase transformation (SIDT) of low carbon steel (0.22wt.%) were quantitatively investigated. The deformation was carried out at just above Ar3 temperature (710°C) as a function of strain rate (0.01-5/sec). The softening process of SIDT was well agreed with calculated result derived from Avrami’s and constitutive equation at higher strain rate than 0.5/sec. However, the calculated results differed from the experimental curve at strain rate of less than 0.2/sec. This is due to fact that the dynamic transformation from austenite to ferrite can not be completed owing to less stored energy during hot deformation.


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