Development of Constitutive Relationships Using Compression Testing of a Medium Carbon Steel

1992 ◽  
Vol 114 (1) ◽  
pp. 116-123 ◽  
Author(s):  
K. P. Rao ◽  
E. B. Hawbolt
Keyword(s):  
Flow Stress ◽  
Carbon Steel ◽  
Strain Rate ◽  
Hot Deformation ◽  
Activation Parameters ◽  
Medium Carbon Steel ◽  
Power Relationship ◽  
Process Variables ◽  
Element Analysis ◽  
Medium Carbon

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.

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 ◽  
...  
Keyword(s):  
Flow Stress ◽  
Carbon Steel ◽  
Strain Rate ◽  
Peak Stress ◽  
Medium Carbon Steel ◽  
Warm Deformation ◽  
Medium Carbon ◽  
Stress Curve ◽  
Flow Stress Curve ◽  
Gleeble 3500

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.

Back Propagation Artificial Neural Network Approach to Predict the Flow Stress in Isothermal Tensile Test of Medium Carbon Steel Material

2020 ◽  
Vol 977 ◽  
pp. 163-168
Author(s):  
Mohanraj Murugesan ◽  
Dong Won Jung
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Flow Stress ◽  
Carbon Steel ◽  
Back Propagation ◽  
Medium Carbon Steel ◽  
Ann Model ◽  
Medium Carbon ◽  
Average Absolute Relative Error ◽  
Steel Material

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.

Modeling of AGS and recrystallized fraction of microalloyed medium carbon steel during hot deformation

2003 ◽  
Vol 355 (1-2) ◽  
pp. 384-393 ◽  
Author(s):  
Sung-Il Kim ◽  
Youngseog Lee ◽  
Duk-Lak Lee ◽  
Yeon-Chul Yoo
Keyword(s):  
Carbon Steel ◽  
Hot Deformation ◽  
Medium Carbon Steel ◽  
Medium Carbon
Sign in / Sign up

Export Citation Format

Share Document