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  • Open Access

    ARTICLE

    Simulating the Effect of Temperature Gradient on Grain Growth of 6061-T6 Aluminum Alloy via Monte Carlo Potts Algorithm

    Qi Wu*, Jianan Li, Lianchun Long, Linao Liu

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 99-116, 2021, DOI:10.32604/cmes.2021.015669

    Abstract During heat treatment or mechanical processing, most polycrystalline materials experience grain growth, which significantly affects their mechanical properties. Microstructure simulation on a mesoscopic scale is an important way of studying grain growth. A key research focus of this type of method has long been how to efficiently and accurately simulate the grain growth caused by a non-uniform temperature field with temperature gradients. In this work, we propose an improved 3D Monte Carlo Potts (MCP) method to quantitatively study the relationship between non-uniform temperature fields and final grain morphologies. Properties of the aluminum alloy AA6061-T6 are used to establish a trial… More >

  • Open Access

    ABSTRACT

    Data Assimilation for Grain Growth Prediction via Multi-Phase-Field Models

    Hiromichi Nagao1,2,*, Shin-ichi Ito1,2, Tadashi Kasuya3, Junya Inoue4,3

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 127-127, 2019, DOI:10.32604/icces.2019.05384

    Abstract Data assimilation (DA) is a computational technique to integrate numerical simulation models and observational/experimental data based on Bayesian statistics. DA is accepted as an essential methodology for the modern weather forecasting, and is applied to various fields of science including structural materials science. We propose a DA methodology to evaluate unobservable parameters involved in multi-phase-field models with the aim of accurately predicting the observed grain growth, such as in metals and alloys. This approach integrates models and a set of observational image data of grain structures. Since the set of image data is not a time series, directly applying conventional… More >

  • Open Access

    ABSTRACT

    Phase Field Simulation of Stress Evolution during Grain Growth Process

    T. Uehara1, M. Fukui2, N. Ohno3

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.2, No.3, pp. 61-66, 2007, DOI:10.3970/icces.2007.002.061

    Abstract Stress evolution during grain growth in microstructure formation process are simulated by using the phase field model. Fundamental equations accounting for the coupling effects among phase transformation, temperature and stress/strain have been formulated based on thermodynamical laws, in which thermal expansion, transformation dilatation, and stress dependency on phase transformation are considered. An elasto-plastic constitutive relationship is applied so as to obtain the residual stresses. Based on these equations, numerical simulations are carried out by the finite element method. Results for two kinds of initial arrangement of nuclei are demonstrated in this paper. One model has four nuclei at the four… More >

  • Open Access

    ARTICLE

    Monte Carlo Simulation of Ti-6Al-4V Grain Growth during Fast Heat Treatment

    Amir Reza Ansari Dezfoli1, Weng-Sing Hwang1,2

    CMC-Computers, Materials & Continua, Vol.49-50, No.1, pp. 1-11, 2015, DOI:10.3970/cmc.2015.049.001

    Abstract Investigations of the microstructural evolution of Titanium (Ti) alloys during high temperature processes and heat treatment are attracting more attention due to wide variety of applications for such alloys. In most of these processes the Titanium alloys are subjected to fast heating or cooling rates. In this paper, Monte Carlo simulation is used to simulate the grain growth kinetics of Ti-6Al-4V alloy during fast heat treatment. Here, Monte Carlo simulation of grain growth is based on the Q-state Potts model. Our model is calibrated using the parabolic grain growth law, dn-d0n = kt, where the empirical constants are taken… More >

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