Highly parallel computer simulations of particle pinning: zener vindicated

Miodownik, Mark; Holm, Elizabeth A.; Hassold, Gregory N.

doi:10.1016/s1359-6462(00)00354-7

Cited by 116 publications

(72 citation statements)

References 18 publications

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“…Impurity effects on grain boundary migration is discussed in the review paper [47] and also in [6,13]. Modeling of the influence on grain boundary migration kinetics from particle drag forces is discussed in the review paper [48] and in conjunction with Monte Carlo Potts modeling in [49], with cellular automata in [50] and using phase field formalism in [51][52][53][54].…”

Section: Classical Results and Empirical Modelsmentioning

confidence: 99%

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Approaches to Modeling of Recrystallization

Hallberg

2011

Metals

153

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Control of the material microstructure in terms of the grain size is a key component in tailoring material properties of metals and alloys and in creating functionally graded materials. To exert this control, reliable and efficient modeling and simulation of the recrystallization process whereby the grain size evolves is vital. The present contribution is a review paper, summarizing the current status of various approaches to modeling grain refinement due to recrystallization. The underlying mechanisms of recrystallization are briefly recollected and different simulation methods are discussed. Analytical and empirical models, continuum mechanical models and discrete methods as well as phase field, vertex and level set models of recrystallization will be considered. Such numerical methods have been reviewed previously, but with the present focus on recrystallization modeling and with a rapidly increasing amount of related publications, an updated review is called for. Advantages and disadvantages of the different methods are discussed in terms of applicability, underlying assumptions, physical relevance, implementation issues and computational efficiency.

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Section: Classical Results and Empirical Modelsmentioning

confidence: 99%

“…In [48], the Monte Carlo Potts model is used in a study of Zener pinning and is also compared to results from phase field and front tracking methods. Monte Carlo Potts modeling of particle pinning is also discussed in [49].…”

Section: Monte Carlo Potts Modelsmentioning

confidence: 99%

Approaches to Modeling of Recrystallization

Hallberg

2011

Metals

153

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“…The significant aspect is that the grain behaviors of the HAZ have been studied. Researchers have given some mechanisms as follows: dispersed particles [2,6,7], stress relief [4], Zener pinning [6,10], smooth-boundary pinning [4] and grain boundary migration [10].…”

Section: Discussionmentioning

confidence: 99%

“…D lim is the limiting grain size based on the Zener drag effect [6,7]. The pinning effect of the precipitates could severely hinder the grain growth.…”

Section: Introductionmentioning

confidence: 99%

Finite-Element Thermal Analysis and Grain Growth Behavior of HAZ on Argon Tungsten-Arc Welding of 443 Stainless Steel

Wang

Deng

Zheng

et al. 2016

Metals

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This paper presents a numerical and infrared experimental study of thermal and grain growth behavior during argon tungsten arc welding of 443 stainless steel. A 3D finite element model was proposed to simulate the welding process. The simulations were carried out via the Ansys Parametric Design Language (APDL) available in the finite-element code, ANSYS. To validate the simulation accuracy, a series of experiments using a fully-automated welding process was conducted. The results of the numerical analysis show that the simulation weld bead size and the experiment results have good agreement. The grain growth in the heat-affected zone of 443 stainless steel is influenced via three factors: (1) the thermal cycle experienced; (2) grain boundary migration; and (3) particle precipitation. Grain boundary migration is the main factor. The modified coefficient k of the grain growth index is calculated. The value is 1.16. Moreover, the microhardness of the weld bead softened slightly compared to the base metal.

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“…Anderson and his co-workers were the first to introduce the Potts model into grain growth simulations, applying this method to model the grain growth kinetics (Anderson et al, 1984), grain size distribution and topology (Srolovitz et al, 1984a), influence of particle dispersions (Srolovitz et al, 1984b), anisotropic grain boundary energies as well as abnormal grain growth Rollett et al, 1989;Rollett & Mullins, 1996). By incorporating specific elements corresponding to various microstructural processes into the basic algorithm, the MC method has been adapted to model for instance grain growth in twophase materials (Holm et al, 1993) and composites (Miodownik et al, 2000), abnormal grain growth (Lee at al., 2000, Messina et al, 2001Ivasishin et al, 2004), static recrystallization (Srolovitz et al, 1986;Srolovitz et al, 1988;Rollett et al, 1992a, Rollett & Raabe, 2001Song & Rettenmayr, 2002)), dynamic recrystallization (Peczak, 1995;Rollett et al, 1992b) and sintering Chen et al, 1990, Matsubara, 1999, and it has been demonstrated that such MC simulations are capable of reproducing the essential features of these microstructural phenomena. Nowadays, the MC method is often preferred to deterministic methods such as cellular automaton (Geiger et al, 2001) and phase-field models (Tikare et al, 1998) at the mesoscopic level, mainly due to its inherent simplicity and flexibility.…”

Section: Introductionmentioning

confidence: 99%

Monte Carlo Simulations of Grain Growth in Metals

Esche¹

2011

Applications of Monte Carlo Method in Science and Engineering

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Highly parallel computer simulations of particle pinning: zener vindicated

Cited by 116 publications

References 18 publications

Approaches to Modeling of Recrystallization

Approaches to Modeling of Recrystallization

Finite-Element Thermal Analysis and Grain Growth Behavior of HAZ on Argon Tungsten-Arc Welding of 443 Stainless Steel

Monte Carlo Simulations of Grain Growth in Metals

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