scholarly journals Constitutive Models for the Prediction of the Hot Deformation Behavior of the 10%Cr Steel Alloy

Materials ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 2873 ◽  
Author(s):  
Abdallah Shokry ◽  
Samer Gowid ◽  
Ghias Kharmanda ◽  
Elsadig Mahdi
Keyword(s):  
Relative Error ◽  
Hot Deformation ◽  
Mean Squared Error ◽  
Flow Behavior ◽  
Constitutive Models ◽  
Superior Performance ◽  
Steel Alloy ◽  
Statistical Parameters ◽  
Average Absolute Relative Error ◽  
Ann Models

The aim of this paper is to establish a reliable model that provides the best fit to the specific behavior of the flow stresses of the 10%Cr steel alloy at the time of hot deformation. Modified Johnson–Cook and strain-compensated Arrhenius-type (phenomenological models), in addition to two Artificial Neural Network (ANN) models were established with the view toward investigating their stress prediction performances. The ANN models were trained using Scaled Conjugate Gradient (SCG) and Levenberg–Marquardt (LM) algorithms. The prediction accuracy of the established models was evaluated using the following well-known statistical parameters: (a) correlation coefficient (R), (b) Average Absolute Relative Error (AARE), (c) Root Mean Squared Error (RMSE), and Relative Error (RE). The results showed that both of the modified Johnson–Cook and strain-compensated Arrhenius models could not competently predict the flow behavior. On the contrary, the results indicated that the two proposed ANN models precisely predicted the flow stress values and that the LM-trained ANN provided a superior performance over the SCG-trained model, as it yielded an RMSE of as low as 0.441 MPa.

scholarly journals A Comparative Study on Johnson–Cook, Modified Johnson–Cook, Modified Zerilli–Armstrong and Arrhenius-Type Constitutive Models to Predict Hot Deformation Behavior of TA2

2019 ◽  
Vol 38 (2019) ◽  
pp. 699-714 ◽  
Author(s):  
Bing Zhang ◽  
Xiaodi Shang ◽  
Su Yao ◽  
Qiuyu Wang ◽  
Zhijuan Zhang ◽  
...  
Keyword(s):  
Deformation Behavior ◽  
Flow Behavior ◽  
True Strain ◽  
Constitutive Models ◽  
Type Model ◽  
Compression Tests ◽  
Absolute Relative Error ◽  
Average Absolute Relative Error ◽  
Wide Range ◽  
Jc Model

AbstractThe true strain data and true stress data are obtained from the isothermal compression tests under a wide range of strain rates (0.1–20 s−1) and temperatures (933–1,133 K) over the Gleeble-3500 thermomechanical simulator. The data are employed to generate the constitutive equations according to four constitutive models, respectively, the strain-compensated Arrhenius-type model, the modified Zerilli–Armstrong (ZA) model, the modified Johnson–Cook (JC) model and the JC model. In the meanwhile, a comparative research was made over the capacities of these four models and hence to represent the elevated temperature flow behavior of TA2. Besides, a comparison of the accuracy of the predictions of average absolute relative error, correlation coefficient (R) and the deformation behavior was made to test the sustainability level of these four models. It is shown from these results that the JC model is not suitable for the description of flow behavior of TA2 alloy in α+β phase domain, while the predicted values of modified JC model, modified ZA model and the strain-compensated Arrhenius-type model could be consistent well with the experimental values except under some deformation conditions. Moreover, the strain-compensated Arrhenius-type model can be also used to track the deformation behavior more precisely in comparison with other models.

scholarly journals Constitutive Model and Flow Behavior of B1500HS High-Strength Steel During the Hot Deformation Process

Metals ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 64 ◽  
Author(s):  
Li ◽  
Duan ◽  
Yao ◽  
Guan ◽  
Yang
Keyword(s):  
Flow Stress ◽  
Constitutive Model ◽  
Hot Deformation ◽  
High Strength Steel ◽  
Deformation Behavior ◽  
Flow Behavior ◽  
Constitutive Models ◽  
High Strength ◽  
Stress Strain ◽  
Comparison Results

Hot compression tests were carried out on a Gleeble-3800 thermal mechanical simulator in the temperature range from 700 to 900 °C and strain rate range from 0.005 to 10 s−1 to investigate the hot deformation behavior of B1500HS high-strength steel. Softening mechanisms of B1500HS high-strength steel under different deformation conditions were analyzed according to the characteristics of flow stress–strain curves. By analyzing and processing the experimental data, the values of steady flow stress, saturated stress, dynamic recovery (DRV) softening coefficient, and other factors were solved and these parameters were expressed as functions of Zener–Hollomon factors. Based on the dislocation density theory and the kinetic model of dynamic recrystallization (DRX), constitutive models corresponding to different softening mechanisms were established. The flow stress–strain curves of B1500HS predicted by a constitutive model are in good agreement with the experimental results and the correlation coefficient is . The comparison results indicate that the constitutive models can accurately reflect the deformation behavior of B1500HS high-strength steel under different conditions.

scholarly journals Constitutive Modeling of the Flow Stress Behavior for the Hot Deformation of Cu-15Ni-8Sn Alloys

2020 ◽  
Vol 7 ◽  
Author(s):  
Dongxin Niu ◽  
Chao Zhao ◽  
Daoxi Li ◽  
Zhi Wang ◽  
Zongqiang Luo ◽  
...  
Keyword(s):  
Flow Stress ◽  
Relative Error ◽  
Hot Deformation ◽  
Hot Extrusion ◽  
Compression Tests ◽  
Arrhenius Model ◽  
Stress Behavior ◽  
Flow Stress Behavior ◽  
Average Absolute Relative Error ◽  
Jc Model

Three constitutive models, strain-compensated Arrhenius model, modified Johnson–Cook (JC) model, and modified Zerilli–Armstrong (ZA) model, were established for the hot-deformed Cu-15Ni-8Sn alloy based on hot compression tests. By introducing average absolute relative error (AARE), correlation coefficient (R), and relative error, the prediction accuracy of these three models was assessed. The results indicate that strain-compensated Arrhenius model has the highest accuracy at describing the flow stress behavior of the studied alloy, followed by modified JC model and modified ZA model. Moreover, the strain-compensated Arrhenius model established in this work has a great practicability in the hot-extrusion simulation of Cu-15Ni-8Sn alloys. This article provides a theoretical basis for optimizing hot deformation parameters in industrial production of the Cu-15Ni-8Sn alloys.

scholarly journals Application of the Strain Compensation Model and Processing Maps for Description of Hot Deformation Behavior of Metastable β Titanium Alloy

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2021
Author(s):  
Oleksandr Lypchanskyi ◽  
Tomasz Śleboda ◽  
Aneta Łukaszek-Sołek ◽  
Krystian Zyguła ◽  
Marek Wojtaszek
Keyword(s):  
Titanium Alloy ◽  
Strain Rate ◽  
Flow Behavior ◽  
Microstructural Analysis ◽  
Calculated Data ◽  
Processing Temperature ◽  
Processing Maps ◽  
Compression Tests ◽  
Strain And Strain Rate ◽  
Average Absolute Relative Error

The flow behavior of metastable β titanium alloy was investigated basing on isothermal hot compression tests performed on Gleeble 3800 thermomechanical simulator at near and above β transus temperatures. The flow stress curves were obtained for deformation temperature range of 800–1100 °C and strain rate range of 0.01–100 s−1. The strain compensated constitutive model was developed using the Arrhenius-type equation. The high correlation coefficient (R) as well as low average absolute relative error (AARE) between the experimental and the calculated data confirmed a high accuracy of the developed model. The dynamic material modeling in combination with the Prasad stability criterion made it possible to generate processing maps for the investigated processing temperature, strain and strain rate ranges. The high material flow stability under investigated deformation conditions was revealed. The microstructural analysis provided additional information regarding the flow behavior and predominant deformation mechanism. It was found that dynamic recovery (DRV) was the main mechanism operating during the deformation of the investigated β titanium alloy.

The Constitutive Model for High Temperature Flow Behavior of SiC/6168Al Composite

2015 ◽  
Vol 1089 ◽  
pp. 37-41
Author(s):  
Jiang Wang ◽  
Sheng Li Guo ◽  
Sheng Pu Liu ◽  
Cheng Liu ◽  
Qi Fei Zheng
Keyword(s):  
Constitutive Model ◽  
Hot Deformation ◽  
Flow Behavior ◽  
Type Equation ◽  
Strain Rate Range ◽  
Compression Tests ◽  
Stress Strain ◽  
Hollomon Parameter ◽  
Proposed Model ◽  
Relationship Of

The hot deformation behavior of SiC/6168Al composite was studied by means of hot compression tests in the temperature range of 300-450 °C and strain rate range of 0.01-10 s-1. The constitutive model was developed to predict the stress-strain curves of this composite during hot deformation. This model was established by considering the effect of the strain on material constants calculated by using the Zenter-Hollomon parameter in the hyperbolic Arrhenius-type equation. It was found that the relationship of n, α, Q, lnA and ε could be expressed by a five-order polynomial. The stress-strain curves obtained by this model showed a good agreement with experimental results. The proposed model can accurately describe the hot flow behavior of SiC/6168Al composite, and can be used to numerically analyze the hot forming processes.

Constitutive Modeling for Flow Stress Behavior of Nimonic 80A Superalloy During Hot Deformation Process

2016 ◽  
Vol 35 (3) ◽  
pp. 327-336 ◽  
Author(s):  
Sendong Gu ◽  
Liwen Zhang ◽  
Chi Zhang ◽  
Wenfei Shen
Keyword(s):  
Flow Stress ◽  
Constitutive Model ◽  
Hot Deformation ◽  
Critical Strain ◽  
Volume Fraction ◽  
Constitutive Models ◽  
Avrami Equation ◽  
Peak Strain ◽  
Compression Tests ◽  
Nimonic 80A

AbstractThe hot deformation characteristics of nickel-based alloy Nimonic 80A were investigated by isothermal compression tests conducted in the temperature range of 1,000–1,200°C and the strain rate range of 0.01—5 s–1on a Gleeble-1500 thermomechanical simulator. In order to establish the constitutive models for dynamic recrystallization (DRX) behavior and flow stress of Nimonic 80A, the material constantsα,nand DRX activation energyQin the constitutive models were calculated by the regression analysis of the experimental data. The dependences of initial stress, saturation stress, steady-state stress, dynamic recovery (DRV) parameter, peak strain, critical strain and DRX grain size on deformation parameters were obtained. Then, the Avrami equation including the critical strain for DRX and the peak strain as a function of strain was established to describe the DRX volume fraction. Finally, the constitutive model for flow stress of Nimonic 80A was developed in DRV region and DRX region, respectively. The flow stress values predicted by the constitutive model are in good agreement with the experimental ones, which indicates that the constitutive model can give an accurate estimate for the flow stress of Nimonic 80A under the deformation conditions.

Constitutive Equation for 3104 Alloy at High Temperatures in Consideration of Strain

2016 ◽  
Vol 35 (6) ◽  
pp. 599-605 ◽  
Author(s):  
Fuqiang Zhen ◽  
Jianlin Sun ◽  
Jian Li
Keyword(s):  
Hot Deformation ◽  
Flow Behavior ◽  
Temperature Correction ◽  
Strain Rates ◽  
Compression Tests ◽  
Hot Deformation Behavior ◽  
Element Analysis ◽  
Hollomon Parameter ◽  
The Finite Element Analysis ◽  
Effects Of Temperature

AbstractThe flow behavior of 3104 aluminum alloy was investigated at temperatures ranging from 250°C to 500°C, and strain rates from 0.01 to 10 s−1 by isothermal compression tests. The true stress–strain curves were obtained from the measured load–stroke data and then modified by friction and temperature correction. The effects of temperature and strain rate on hot deformation behavior were represented by Zener–Hollomon parameter including Arrhenius term. Additionally, the influence of strain was incorporated considering the effect of strain on material constants. The derived constitution equation was applied to the finite element analysis of hot compression. The results show that the simulated force is consistent with the measured one. Consequently, the developed constitution equation is valid and feasible for numerical simulation in hot deformation process of 3104 alloy.

Microstructure Integrated Modeling of Multiscan Laser Forming

2002 ◽  
Vol 124 (2) ◽  
pp. 379-388 ◽  
Author(s):  
Jin Cheng ◽  
Y. Lawrence Yao
Keyword(s):  
Flow Stress ◽  
Numerical Models ◽  
Flow Behavior ◽  
Fem Simulation ◽  
Constitutive Models ◽  
Low Carbon Steel ◽  
Laser Forming ◽  
Low Carbon ◽  
Forming Process ◽  
Heating And Cooling

Laser forming of steel is a hot forming process with high heating and cooling rate, during which strain hardening, dynamic recrystallization, and phase transformation take place. Numerical models considering strain rate and temperature effects only usually give unsatisfactory results when applied to multiscan laser forming operations. This is mainly due to the inadequate constitutive models employed to describe the hot flow behavior. In this work, this limitation is overcome by considering the effects of microstructure change on the flow stress in laser forming processes of low carbon steel. The incorporation of such flow stress models with thermal mechanical FEM simulation increases numerical model accuracy in predicting geometry change and mechanical properties.

scholarly journals Forecasting Wind Power Generation Using Artificial Neural Network: “Pawan Danawi”—A Case Study from Sri Lanka

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Amila T. Peiris ◽  
Jeevani Jayasinghe ◽  
Upaka Rathnayake
Keyword(s):  
Neural Network ◽  
Power Generation ◽  
Wind Power ◽  
Wind Farm ◽  
Mean Squared Error ◽  
Wind Power Generation ◽  
Training Algorithms ◽  
Training Algorithm ◽  
Squared Error ◽  
Ann Models

Wind power, as a renewable energy resource, has taken much attention of the energy authorities in many countries, as it is used as one of the major energy sources to satisfy the ever-increasing energy demand. However, careful attention is needed in identifying the wind power potential in a particular area due to climate changes. In this sense, forecasting both wind power generation and wind power potential is essential. This paper develops artificial neural network (ANN) models to forecast wind power generation in “Pawan Danawi”, a functioning wind farm in Sri Lanka. Wind speed, wind direction, and ambient temperature of the area were used as the independent variable matrices of the developed ANN models, while the generated wind power was used as the dependent variable. The models were tested with three training algorithms, namely, Levenberg-Marquardt (LM), Scaled Conjugate Gradient (SCG), and Bayesian Regularization (BR) training algorithms. In addition, the model was calibrated for five validation percentages (5% to 25% in 5% intervals) under each algorithm to identify the best training algorithm with the most suitable training and validation percentages. Mean squared error (MSE), coefficient of correlation (R), root mean squared error ratio (RSR), Nash number, and BIAS were used to evaluate the performance of the developed ANN models. Results revealed that all three training algorithms produce acceptable predictions for the power generation in the Pawan Danawi wind farm with R > 0.91, MSE < 0.22, and BIAS < 1. Among them, the LM training algorithm at 70% of training and 5% of validation percentages produces the best forecasting results. The developed models can be effectively used in the prediction of wind power at the Pawan Danawi wind farm. In addition, the models can be used with the projected climatic scenarios in predicting the future wind power harvest. Furthermore, the models can acceptably be used in similar environmental and climatic conditions to identify the wind power potential of the area.

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