Constitutive Model and Cellular Automaton Simulation of the Dynamic Recrystallization of Railway EA4T‐Grade Steel

Herein, isothermal compression experiments are conducted on EA4T steel at 970–1170 °C, with strain rates of 0.01–1.0 s−1 and a strain of 0.2–0.8 s−1. Based on the experimental data, a high‐temperature constitutive model is developed for EA4T steel. The activation energy of dynamic recrystallization...

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Veröffentlicht in:Steel research international 2023-05, Vol.94 (5), p.n/a
Hauptverfasser: Ren, Xu, Huo, Yuan-Ming, He, Tao, Hosseini, Seyed Reza Elmi, Bian, Zhi-Yuan, Bai, Jie, Du, Xiang-Yang
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He, Tao
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Bai, Jie
Du, Xiang-Yang
description Herein, isothermal compression experiments are conducted on EA4T steel at 970–1170 °C, with strain rates of 0.01–1.0 s−1 and a strain of 0.2–0.8 s−1. Based on the experimental data, a high‐temperature constitutive model is developed for EA4T steel. The activation energy of dynamic recrystallization (DRX) is calculated to be 383 666 J mol−1, and the correlation coefficient and root mean square error between the results of the constitutive model and experimental results are 0.9943 and 4.6823, respectively. The average grain size for each deformation condition is determined using the linear‐intercept method. The grain growth model widely used in cellular automaton (CA) simulations is found unsuitable for EA4T steel. Therefore, a modified CA model of DRX behavior suitable for EA4T steel is developed. The nucleation rates and solute drag effect coefficients under different deformation conditions are determined. Furthermore, simulations are performed under other deformation conditions using the CA model. The simulated results for the average grain size, microstructure morphology, and DRX fraction agree well with the experimental results. The reason for the deviation between the observed and simulated DRX fractions is also explored. A high‐temperature constitutive model of EA4T steel has been established based on the results of isothermal compression experiments. A modified cellular automaton model of dynamic recrystallization (DRX) behavior suitable for EA4T steel is established. The average grain size, grain morphology, and DRX fraction obtained from the simulation are in good agreement with the experimental results.
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Based on the experimental data, a high‐temperature constitutive model is developed for EA4T steel. The activation energy of dynamic recrystallization (DRX) is calculated to be 383 666 J mol−1, and the correlation coefficient and root mean square error between the results of the constitutive model and experimental results are 0.9943 and 4.6823, respectively. The average grain size for each deformation condition is determined using the linear‐intercept method. The grain growth model widely used in cellular automaton (CA) simulations is found unsuitable for EA4T steel. Therefore, a modified CA model of DRX behavior suitable for EA4T steel is developed. The nucleation rates and solute drag effect coefficients under different deformation conditions are determined. Furthermore, simulations are performed under other deformation conditions using the CA model. The simulated results for the average grain size, microstructure morphology, and DRX fraction agree well with the experimental results. The reason for the deviation between the observed and simulated DRX fractions is also explored. A high‐temperature constitutive model of EA4T steel has been established based on the results of isothermal compression experiments. A modified cellular automaton model of dynamic recrystallization (DRX) behavior suitable for EA4T steel is established. 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Based on the experimental data, a high‐temperature constitutive model is developed for EA4T steel. The activation energy of dynamic recrystallization (DRX) is calculated to be 383 666 J mol−1, and the correlation coefficient and root mean square error between the results of the constitutive model and experimental results are 0.9943 and 4.6823, respectively. The average grain size for each deformation condition is determined using the linear‐intercept method. The grain growth model widely used in cellular automaton (CA) simulations is found unsuitable for EA4T steel. Therefore, a modified CA model of DRX behavior suitable for EA4T steel is developed. The nucleation rates and solute drag effect coefficients under different deformation conditions are determined. Furthermore, simulations are performed under other deformation conditions using the CA model. The simulated results for the average grain size, microstructure morphology, and DRX fraction agree well with the experimental results. The reason for the deviation between the observed and simulated DRX fractions is also explored. A high‐temperature constitutive model of EA4T steel has been established based on the results of isothermal compression experiments. A modified cellular automaton model of dynamic recrystallization (DRX) behavior suitable for EA4T steel is established. 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subjects Cellular automata
cellular automaton
constitutive model
Constitutive models
Correlation coefficients
Deformation effects
Dynamic recrystallization
EA4T steels
Grain growth
Grain size
Growth models
Low alloy steels
Mathematical models
microstructure morphology
Nucleation
Simulation
title Constitutive Model and Cellular Automaton Simulation of the Dynamic Recrystallization of Railway EA4T‐Grade Steel
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