This study proposes a computational model based on the finite element method (FEM) to simulate the thermomechanical behavior of C-Mn steel under continuous cooling. Hot torsion tests were conducted at temperatures from 900 to 1100 °C, with strain rates of 0.1, 1.0, and 10 s−1, and a strain of <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$\varepsilon$</EquationSource> <EquationSource Format="MATHML"><math> <mi>ε</mi> </math></EquationSource> </InlineEquation> = 6.0, using an infrared radiation furnace, argon gas shielding, and a chromel–alumel K-type thermocouple. The experimental data were implemented in DEFORM™3D to formulate equations for dynamic recrystallization (<InlineEquation ID="IEq2"> <EquationSource Format="TEX">${\varepsilon}_{0.5}$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>ε</mi> <mrow> <mn>0.5</mn> </mrow> </msub> </math></EquationSource> </InlineEquation>, <InlineEquation ID="IEq3"> <EquationSource Format="TEX">${X}_{\text{D}\text{R}\text{X}}$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>X</mi> <mtext>DRX</mtext> </msub> </math></EquationSource> </InlineEquation>) and recrystallized grain size (<InlineEquation ID="IEq4"> <EquationSource Format="TEX">${d}_{\text{D}\text{R}\text{X}}$</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>d</mi> <mtext>DRX</mtext> </msub> </math></EquationSource> </InlineEquation>), yielding good agreement with DRX kinetic models and accurate numerical predictions. The results show that recrystallization time increases as temperature decreases, while strain-induced precipitation (SIP) begins after the seventh pass. Small variations in rolling temperature altered the microstructure and average grain size, emphasizing the need for strict process control. These findings confirm that controlled rolling is essential to prevent heterogeneous grain-size distributions that may impair mechanical performance. The main contribution of this study is the development of a thermomechanical computational model capable of evaluating a wide range of processing parameter combinations with high efficiency and reduced experimental effort, enabling accurate prediction of microstructural evolution during hot rolling.

Computational Modeling of Dynamic Recrystallization and Strain-Induced Precipitation in C-Mn Steels by Thermomechanical Processes

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2026年7月20日

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Marvin Barros de Miranda Sales,
Antonio Lourenço Batista de Souza,
Marcelly Cristiny Nunes de Carvalho,
João Marcos da Silva Nunes,
Jorge Luís Gomes Gonçalves,
Gedeon Silva Reis,
Samuel Filgueiras Rodrigues,
Rodrigo Bresciani Canto,
Eden Santos Silva

摘要

This study proposes a computational model based on the finite element method (FEM) to simulate the thermomechanical behavior of C-Mn steel under continuous cooling. Hot torsion tests were conducted at temperatures from 900 to 1100 °C, with strain rates of 0.1, 1.0, and 10 s⁻¹, and a strain of $\varepsilon$ $ε$ = 6.0, using an infrared radiation furnace, argon gas shielding, and a chromel–alumel K-type thermocouple. The experimental data were implemented in DEFORM™3D to formulate equations for dynamic recrystallization ( ${\varepsilon}_{0.5}$ $ε_{0.5}$ , ${X}_{\text{D}\text{R}\text{X}}$ $X_{DRX}$ ) and recrystallized grain size ( ${d}_{\text{D}\text{R}\text{X}}$ $d_{DRX}$ ), yielding good agreement with DRX kinetic models and accurate numerical predictions. The results show that recrystallization time increases as temperature decreases, while strain-induced precipitation (SIP) begins after the seventh pass. Small variations in rolling temperature altered the microstructure and average grain size, emphasizing the need for strict process control. These findings confirm that controlled rolling is essential to prevent heterogeneous grain-size distributions that may impair mechanical performance. The main contribution of this study is the development of a thermomechanical computational model capable of evaluating a wide range of processing parameter combinations with high efficiency and reduced experimental effort, enabling accurate prediction of microstructural evolution during hot rolling.