A Kinetic Model for Phase Transformations of Low Carbon Steels during Continuous Cooling

Suehiro, Masayoshi; Senuma, Takehide; Yada, Hiroshi; Matsumura, Yoshikazu; Ariyoshi, Toshihiko

doi:10.2355/tetsutohagane1955.73.8_1026

Cited by 27 publications

(16 citation statements)

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“…(1) where k i is the coefficient for the alloying element i (°C/wt%), x i is the amount of alloying element i (wt%), and B s,0 is the B s temperature of pure iron. Several empirical equations to predict the B s temperature have been proposed by multiple investigators [3][4][5][6][7][8][9][10][11][12] and are summarized in Table 2. While Eq.…”

mentioning

confidence: 99%

“…Some empirical equations have been proposed to predict the effect of adding alloying elements to carbon and alloy steels on Bs temperature. [3][4][5][6][7][8][9][10][11][12] Prior austenite grain size (PAGS) can also affect the Bs temperature. Lee et al 13) reported that Bs temperature decreased with decreasing PAGS.…”

mentioning

confidence: 99%

“…The effects of alloying elements on B s temperature prediction are generally expressed by a linear type relationship as follows: [3][4][5][6]8,10) . (1) where k i is the coefficient for the alloying element i (°C/wt%), x i is the amount of alloying element i (wt%), and B s,0 is the B s temperature of pure iron.…”

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Prediction of Bainite Start Temperature in Alloy Steels with Different Grain Sizes

2014

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KEY WORDS: bainite start (Bs) temperature; alloying element; prior austenite grain size (PAGS); alloy steels.Bainite microstructure in alloy steels yields materials with an excellent combination of mechanical properties such as high strength and toughness, resistance to creep and fatigue, and hydrogen embrittlement.1,2) During cooling, bainite transformation is initiated at the bainite start (Bs) temperature, which is the highest isothermal temperature at which upper bainite is observed, and ceases when the temperature reaches the martensite start (Ms) temperature. Addition of alloying elements mostly lowers the Bs temperature. Especially, carbon and manganese known as strong austenite stabilizing elements effectively decrease the Bs temperature. Several quantitative investigations have been performed to determine the relationship between the addition of alloying elements and Bs temperature variations in alloy steels. Some empirical equations have been proposed to predict the effect of adding alloying elements to carbon and alloy steels on Bs temperature. [3][4][5][6][7][8][9][10][11][12] Prior austenite grain size (PAGS) can also affect the Bs temperature. Lee et al. 13) reported that Bs temperature decreased with decreasing PAGS. Bs temperature variations due to the decrease in PAGS simultaneously influenced bainite transformation kinetics. [13][14][15] However, few researchers have attempted to develop the equations for Bs temperature by considering both chemical composition and PAGS effects. Therefore, in the present study, we developed a simple empirical equation for Bs temperature prediction that includes both the alloying element effect and the PAGS effect based on experimental data obtained from the literature. We compared the accuracy of our empirical equation with existing equations and verified the performance of our equation using experimental data.Experimental Bs temperature data for carbon and alloy steels were extracted from published time-temperaturetransformation (TTT) diagrams.16) Both chemical composition and PAGS were used to evaluate existing equations and to derive a new equation. We selected the following alloying elements in the present work: C, Mn, Si, Ni, Cr, and Mo.Data for other alloying elements were excluded. The chemical composition range of the selected steels was limited to that of low alloy steels, thus high alloyed steels such as a stainless steel was excluded. Ranges of chemical composition, PAGS, and B s temperature used for equation derivation are summarized in Table 1. The total number of B s data points used in the present work was 97.

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Prediction of Bainite Start Temperature in Alloy Steels with Different Grain Sizes

2014

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“…Transition in dislocation density at each point was continuously traced from forming stage to cooling stage to reflect the effect of hot forming on the accelerated nucleation at the beginning of transformation. 16) Material parameters for phase transformation of Suehiro's model 18) were used in the analysis.…”

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confidence: 99%

Three-dimensional Numerical Analysis of Microstructural Evolution in and after Bar and Shape Rolling Processes.

Liu

2002

ISIJ International

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An integrated numerical model predicting microstructural evolution, three-dimensional plastic deformation and temperature changes has been applied to industrial hot bar rolling and H-beam rolling. This model enables us to predict three-dimensional metal flow and temperature changes as well as transient in grain size change and dislocation density distribution in and after hot rolling. To demonstrate the successfulness of the proposed model, it was applied to the analysis of two different industrial bar rolling schedules, in which total number of passes and caliber systems were different with each other. It was also applied to the analysis of the H-beam rolling sequences with different heat treatment conditions. Microstructural evolution starting from deformed austenite to ferrite/pearlite/bainite after phase transformation was successfully simulated. Microstructural evolution in and after hot rolling as well as metal flow and temperature can be easily obtained through the proposed model using rolling condition and alloy composition as the functional variables. This model is a very useful tool for designing and optimizing rolling conditions so that products with the best internal quality and dimensional accuracy can be obtained.

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“…There are some integrated models [11][12][13][14] that can reportedly predict the evolution of , P, widmanstätten-, and B. These models were based on classical nucleation and growth theories (CNGT), developed for low-carbon steel strips, and thus, focused on the prediction of the grain size which affects significantly the mechanical strength and elongation.…”

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confidence: 99%

Prediction of Bainite Intervened in Ferrite-Pearlite Forging Steel I. Modeling

et al. 2009

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The successive ferrite () + pearlite (P) transformations from austenite () were modeled to predict the presence of bainite in as-forged medium-carbon manganese steels. The kinetics of diffusional transformations were calculated based on classical nucleation and growth theory coupled with CALPHAD multi-component thermodynamics. The description of the growth rate of proeutectoid-includes a time dependence due to the carbon enrichment in the remaining . The / interface was assumed to be in negligible-partitioned local equilibrium (NPLE). The kinetics calculation of P nucleating on the surface was integrated into the model. Given the transformation temperature range in continuous cooling, the growth rate of P was also expressed in the NPLE constraint for /cementite. The concentration of untransformed ( U ) can be monitored and should be dependent on the extent of the preceding transformations. Thus, the energies available for the nucleation and diffusionless growth of bainitic-were evaluated from the thermodynamics of the U single-phase system, which is proposed as a method to predict the inclusion of bainite in the final þ P microstructure.

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A Kinetic Model for Phase Transformations of Low Carbon Steels during Continuous Cooling

Cited by 27 publications

References 4 publications

Prediction of Bainite Start Temperature in Alloy Steels with Different Grain Sizes

Prediction of Bainite Start Temperature in Alloy Steels with Different Grain Sizes

Three-dimensional Numerical Analysis of Microstructural Evolution in and after Bar and Shape Rolling Processes.

Prediction of Bainite Intervened in Ferrite-Pearlite Forging Steel I. Modeling

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