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arXiv 1801.03060cond-mat.softcond-mat.dis-nn
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基于拓扑拓扑结构的粒度网络刻画

Characterizing Granular Networks Using Topological Metrics

Joshua A. Dijksman, Lenka Kovalcinova, Jie Ren, Robert P. Behringer, Miroslav Kramar, Konstantin Mischaikow, Lou Kondic

摘要:

我们进行了直接比较的实验和数值实现的完全相同的颗粒系统,因为它经历剪切堵塞。我们调整用于最佳地代表实验设置和结果的数值方法,以微观接触力动力学。这里提出的措施范围从微观,通过中观系统的全系统特性。介观力网络的拓扑性质提供了微观和宏观尺度之间的关键环节。我们报告了两个主要发现:无论应变历史和填充密度如何,填充物中具有至少两个接触的颗粒的数量是系统机械状态的良好预测器。在实验和数值计算中探索的所有措施,包括应力张量导出的措施和接触数,都以一种普遍的方式依赖于非响尾蛇颗粒的分数,$f_{NR}$。力网络拓扑也倾向于显示这种普遍性,但主曲线的形状更多地取决于数值模拟的细节。特别是,我们表明,增加力噪声的数值数据集可以显着改变数据中的拓扑特征。我们的结论是,$f_{NR}$和拓扑度量是有用的措施时,考虑量化的状态的颗粒系统。

英文摘要:

We carry out a direct comparison of experimental and numerical realizations of the exact same granular system as it undergoes shear jamming. We adjust the numerical methods used to optimally represent the experimental settings and outcomes up to microscopic contact force dynamics. Measures presented here range form microscopic, through mesoscopic to system-wide characteristics of the system. Topological properties of the mesoscopic force networks provide a key link between micro and macro scales. We report two main findings: the number of particles in the packing that have at least two contacts is a good predictor for the mechanical state of the system, regardless of strain history and packing density. All measures explored in both experiments and numerics, including stress tensor derived measures and contact numbers depend in a universal manner on the fraction of non-rattler particles, $f_{NR}$. The force network topology also tends to show this universality, yet the shape of the master curve depends much more on the details of the numerical simulations. In particular we show that adding force noise to the numerical data set can significantly alter the topological features in the data. We conclude that both $f_{NR}$ and topological metrics are useful measures to consider when quantifying the state of a granular system.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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