Numerical simulation of recrystallization in BCC metals

Montaño-Zuñiga, Ixchel M.; Sepulveda-Cervantes, Gabriel; López-Hirata, Vı́ctor M.; Rivas-López, Diego I.; González-Velázquez, Jorge Luis

doi:10.1016/j.commatsci.2010.05.042

Cited by 3 publications

(4 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some researchers simulated the microstructure and texture evolution during SRX in interstitial free (IF) steel using an MC method [96][97][98][99]. The simulation results of Hayakawa et al [98] showed that 111 || ND texture (-fiber), which is a typical rolling annealing texture in steel sheets, is obtained by a grain boundary nucleation mechanism.…”

Section: Recrystallizationmentioning

confidence: 97%

“…Choi et al [96] calculated the yield surface of IF steels by coupling a viso-plastic self-consistent polycrystalline model with an MC technique. Montaño-Zuñiga et al [99] found that the -fiber orientation was dominant for the recrystallization due to its higher mobility. The Avrami exponent of their simulated SRX kinetics was in agreement with the one reported in IF steels.…”

Section: Recrystallizationmentioning

confidence: 98%

See 1 more Smart Citation

Progress in mesoscopic modeling of microstructure evolution in steels

Xiao

Chen

et al. 2011

Sci. China Technol. Sci.

View full text Add to dashboard Cite

The mesoscopic modeling developed rapidly in the past three decades is a promising tool for predicting and understanding the microstructure evolution at grain scale. In this paper, the recent development of mesoscopic modeling and its application to microstructure evolution in steels is reviewed. Firstly, some representative computational models are briefly introduced, e.g., the phase field model, the cellular automaton model and the Monte Carlo model. Then, the emphasis is put on the application of mesoscopic modeling of the complex features of microstructure evolution, including solidification, solid-state phase transformation, recrystallization and grain growth. Finally, some issues in the present mesoscopic modeling and its perspective are discussed. microstructure evolution, steel, phase field, cellular automaton, Monte Carlo Citation:Xiao N M, Chen Y, Li D Z, et al. Progress in mesoscopic modeling of microstructure evolution in steels.

show abstract

Section: Recrystallizationmentioning

confidence: 97%

Section: Recrystallizationmentioning

confidence: 98%

Progress in mesoscopic modeling of microstructure evolution in steels

Xiao

Chen

et al. 2011

Sci. China Technol. Sci.

View full text Add to dashboard Cite

show abstract

“…One of these methods is the called phase-field method which usually is based on a solution of the nonlinear Cahn-Hilliard equation using mainly thermodynamic and atomic diffusion data 5 . The phase-field method has been used to simulate phase transformations in different alloy systems 2,3,6,7 . One of the typical applications of the phase-field method is the microstructural simulation of the phase decomposition in alloy systems with a miscibility gap 8 .…”

Section: Introductionmentioning

confidence: 99%

“…Since these methods have permitted to simulate different heat treating or operating conditions, which are sometimes difficult to obtain in a practical way for instance, very prolonged times 1 . Additionally, the use of numerical methods can be used to understand in more detail the mechanism and growth kinetics of different phase transformations, which occur during the heating of alloys 2,3 . Several numerical methods 4 have been used to analyze the phase transformations in alloys.…”

Section: Introductionmentioning

confidence: 99%

Numerical analysis of phase decomposition in A-B binary alloys using Cahn-Hilliard equations

Lezama-Alvarez¹,

Ávila-Dávila

López-Hirata³

et al. 2013

Mat. Res.

Self Cite

View full text Add to dashboard Cite

The analysis of phase decomposition was carried out using the nonlinear and linear Cahn-Hilliard equations in a hypothetical A-B alloy system with a miscibility gap. These equations were solved by the explicit finite difference method assuming a regular solution model. The supersaturated solid solution and decomposed phases were considered to have an fcc structure. Different aging temperatures and thermodynamic interaction parameters Ω A-B were used to simulate different alloy systems. The numerical simulation results showed that the growth kinetics of phase decomposition in the alloy with 30at.% A was slower than that of 50 at.% A. Additionally, the start time and modulation wavelength of phase decomposition are strongly affected by the thermodynamic interaction parameter Ω A-B value. The numerical simulation results showed that the growth kinetics of phase decomposition with the linear equation is slower than that with the nonlinear one.

show abstract