Stochastic 3D modeling of Ostwald ripening at ultra-high volume fractions of the coarsening phase

Stochastic 3D modeling of Ostwald ripening at ultra-high volume fractions of the coarsening phase
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DOI:
10.1088/0965-0393/23/6/065001
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发表时间:
2015-07
影响因子:
1.8
通讯作者:
A. Spettl;R. Wimmer;Thomas Werz;M. Heinze;S. Odenbach;C. Krill;V. Schmidt
A. Spettl;R. Wimmer;Thomas Werz;M. Heinze;S. Odenbach;C. Krill;V. Schmidt
中科院分区:
材料科学3区
文献类型:
--
作者:
A. Spettl;R. Wimmer;Thomas Werz;M. Heinze;S. Odenbach;C. Krill;V. Schmidt

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我们提出了一个(动态)随机模拟模型的3D晶粒形貌经历晶粒粗化现象称为奥斯特瓦尔德熟化。对于粗化相的低体积分数,经典的LSW理论预测的平均粒径和收敛到自相似的粒径分布的幂律演化;实验表明,这种行为也适用于高体积分数。在目前的工作中,我们已经分析了3D图像,在半固态Al-Cu合金显示超高体积分数的粗化(固体)相随时间的推移原位记录。利用这些信息,我们开发了一个随机模拟模型的3D形态的粗化晶粒在任意的时间步长。我们的随机模型基于随机拉盖尔镶嵌,并且根据定义是自相似的-即它仅取决于平均粒径,而平均粒径又可以在每个时间点进行估计。对于一个给定的平均直径,随机模型只需要三个额外的标量参数,这影响颗粒的大小和形状的分布。评估表明,即使用这种最小的信息的随机模型产生的实验数据的统计特性的一个很好的表示。
We present a (dynamic) stochastic simulation model for 3D grain morphologies undergoing a grain coarsening phenomenon known as Ostwald ripening. For low volume fractions of the coarsening phase, the classical LSW theory predicts a power-law evolution of the mean particle size and convergence toward self-similarity of the particle size distribution; experiments suggest that this behavior holds also for high volume fractions. In the present work, we have analyzed 3D images that were recorded in situ over time in semisolid Al–Cu alloys manifesting ultra-high volume fractions of the coarsening (solid) phase. Using this information we developed a stochastic simulation model for the 3D morphology of the coarsening grains at arbitrary time steps. Our stochastic model is based on random Laguerre tessellations and is by definition self-similar—i.e. it depends only on the mean particle diameter, which in turn can be estimated at each point in time. For a given mean diameter, the stochastic model requires only three additional scalar parameters, which influence the distribution of particle sizes and their shapes. An evaluation shows that even with this minimal information the stochastic model yields an excellent representation of the statistical properties of the experimental data.