Force-Chain Finder: A software tool for the recursive detection of force-chains in granular materials via minor principal stress
Force-Chain Finder: A software tool for the recursive detection of force-chains in granular materials via minor principal stress
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DOI：
10.1016/j.cpc.2023.109070
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发表时间：
2023-12
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影响因子：
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通讯作者：
Omid Ejtehadi;Aashish K. Gupta;S. Khajepor;Sina Haeri
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作者：
Omid Ejtehadi;Aashish K. Gupta;S. Khajepor;Sina Haeri
颗粒介质中的力传递是通过颗粒间的非均匀接触网络（称为力链）进行的。彻底了解这些链的结构对于更好地理解它们产生的宏观特征是必不可少的。本文介绍了力链分析（FCF），一个开源的软件工具，旨在检测力链在粒状材料。利用基于每个粒子与相邻粒子的相互作用为每个粒子计算的应力张量，该工具有效地识别了最大压缩主应力的大小和方向。通过粒子及其邻居的递归遍历，基于主应力方向的对齐来鲁棒地检测力链，该主应力方向由参数α（以弧度为单位的角度）决定。该软件提供了一套全面的后处理功能，包括以不同格式导出结果，从而能够对特定区域和动态现象进行详细分析。此外，该软件便于计算与链大小和种群有关的统计措施。通过简化离散元法（DEM）模拟中力链的识别和表征，该工具显着提高了力链分析的效率和准确性。因此，该软件通过使研究人员能够毫不费力地检测和分析力链，促进了对颗粒材料行为的更深入了解。摘要程序标题：力链分析（FCF）CPC库程序文件链接：https：//doi.org/10.17632/33pkc4f63t.1开发人员的存储库链接：https://github.com/Particles-Research/Force_Chain_Finder_Public/tree/mainLicensing规定：GNU通用公共许可证3编程语言：C++，Python补充材料：说明性示例问题的性质：FCF的主要目标是有效和全面地检测离散元建模（DEM）中出现的力网络求解方法：该方法基于“J.Peters，M. Muthuswamy，J. Wibowo，and A.托尔德西利亚，颗粒材料中力链的表征，物理评论E 72，041307（2005）"。它利用小主应力的概念来识别准线性链，每个链至少由三个粒子组成。然而，已经实施了重大的算法修改，以提高该过程的准确性，从而能够检测链分支和合并。
Force transmission in granular media occurs through an inhomogeneous network of inter-particle contacts referred to as force-chains. A thorough understanding of the structure of these chains is indispensable for a better comprehension of the macroscopic signatures they generate. This paper introduces Force-Chain Finder (FCF), an open-source software tool designed for detecting force-chains in granular materials. Leveraging the stress tensor computed for each particle based on its interactions with neighbouring particles, the tool effectively identifies the magnitude and direction of the most compressive principal stress. Through a recursive traversal of particles and their neighbours, force-chains are robustly detected based on the alignment of the principal stress directions, which is decided by a parameterα(an angle in radians). The software provides a comprehensive suite of post-processing features, including the exportation of results in different formats, enabling detailed analysis of specific regions and dynamic phenomena. Additionally, the software facilitates the computation of statistical measures pertaining to chain size and population. By streamlining the identification and characterization of force-chains within discrete element method (DEM) simulations, this tool significantly enhances the efficiency and accuracy of force-chain analysis. Thus, the software promotes deeper insights into the behaviour of granular materials by enabling researchers to effortlessly detect and analyse force-chains.PROGRAM SUMMARYProgram Title:Force Chain Finder (FCF)CPC Library link to program files:https://doi.org/10.17632/33pkc4f63t.1Developer's repository link:https://github.com/Particles-Research/Force_Chain_Finder_Public/tree/mainLicensing provisions:GNU General Public License 3Programming Language:C++, PythonSupplementary material:Illustrative examplesNature of the Problem:FCF has been developed with the primary objective of efficiently and comprehensively detecting force networks that arise in Discrete Element Modelling (DEM) simulations of granular flow.Solution Method:The method is based on the work of “J. Peters, M. Muthuswamy, J. Wibowo, and A. Tordesillas, Characterization of force chains in granular material, Physical Review E 72, 041307 (2005)”. It utilizes the concept of minor principal stress to identify quasilinear chains, each consisting of at least three particles. However, significant algorithmic modifications have been implemented to enhance the accuracy of the procedure, enabling the detection of chain branching and merging.