• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

使用六边形密堆积结构识别二维颗粒材料优化离散元模型的微观参数。

Identify the Micro-Parameters for Optimized Discrete Element Models of Granular Materials in Two Dimensions Using Hexagonal Close-Packed Structures.

作者信息

Zhou Xiaodong, Jin Dongzhao, Ge Dongdong, Chen Siyu, You Zhanping

机构信息

Rizhao City Transportation Bureau, Rizhao 276800, China.

Department of Civil, Environmental, and Geospatial Engineering, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931-1295, USA.

出版信息

Materials (Basel). 2023 Apr 13;16(8):3073. doi: 10.3390/ma16083073.

DOI:10.3390/ma16083073
PMID:37109908
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10143340/
Abstract

The widely used simple cubic-centered (SCC) model structure has limitations in handling diagonal loading and accurately representing Poisson's ratio. Therefore, the objective of this study is to develop a set of modeling procedures for granular material discrete element models (DEM) with high efficiency, low cost, reliable accuracy, and wide application. The new modeling procedures use coarse aggregate templates from an aggregate database to improve simulation accuracy and use geometry information from the random generation method to create virtual specimens. The hexagonal close-packed (HCP) structure, which has advantages in simulating shear failure and Poisson's ratio, was employed instead of the SCC structure. The corresponding mechanical calculation for contact micro-parameters was then derived and verified through simple stiffness/bond tests and complete indirect tensile (IDT) tests of a set of asphalt mixture specimens. The results showed that (1) a new set of modeling procedures using the hexagonal close-packed (HCP) structure was proposed and was proved to be effective, (2) micro-parameters of the DEM models were transit form material macro-parameters based on a set of equations that were derived based on basic configuration and mechanism of discrete element theories, and (3) that the results from IDT tests prove that the new approach to determining model micro-parameters based on mechanical calculation is reliable. This new approach may enable a wider and deeper application of the HCP structure DEM models in the research of granular material.

摘要

广泛使用的简单立方中心（SCC）模型结构在处理斜向荷载和精确表示泊松比方面存在局限性。因此，本研究的目的是开发一套用于粒料离散元模型（DEM）的建模程序，该程序具有高效率、低成本、可靠精度和广泛适用性。新的建模程序使用集料数据库中的粗集料模板来提高模拟精度，并利用随机生成方法的几何信息来创建虚拟试件。采用在模拟剪切破坏和泊松比方面具有优势的六方密堆积（HCP）结构取代SCC结构。然后通过一组沥青混合料试件的简单刚度/粘结试验和完整间接拉伸（IDT）试验，推导并验证了接触微观参数的相应力学计算方法。结果表明：（1）提出了一套采用六方密堆积（HCP）结构的新建模程序，并证明其有效；（2）基于离散元理论的基本构型和机理推导的一组方程，将DEM模型的微观参数从材料宏观参数转换而来；（3）IDT试验结果证明了基于力学计算确定模型微观参数的新方法是可靠的。这种新方法可能使HCP结构DEM模型在粒料研究中得到更广泛和深入的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/52086a4f4fdb/materials-16-03073-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/43720319f6a4/materials-16-03073-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/c36664b85699/materials-16-03073-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/fde686b6e3bf/materials-16-03073-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/b4d45e693161/materials-16-03073-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/62b122a87cc9/materials-16-03073-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/679145299a81/materials-16-03073-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/45f13207af36/materials-16-03073-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/b5561c17fec5/materials-16-03073-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/d36c384adf3c/materials-16-03073-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/50bf563dffb3/materials-16-03073-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/cb16fed63ce9/materials-16-03073-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/72deaab8c542/materials-16-03073-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/f0aebcfe8ca4/materials-16-03073-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/f43176678e42/materials-16-03073-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/52086a4f4fdb/materials-16-03073-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/43720319f6a4/materials-16-03073-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/c36664b85699/materials-16-03073-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/fde686b6e3bf/materials-16-03073-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/b4d45e693161/materials-16-03073-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/62b122a87cc9/materials-16-03073-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/679145299a81/materials-16-03073-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/45f13207af36/materials-16-03073-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/b5561c17fec5/materials-16-03073-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/d36c384adf3c/materials-16-03073-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/50bf563dffb3/materials-16-03073-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/cb16fed63ce9/materials-16-03073-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/72deaab8c542/materials-16-03073-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/f0aebcfe8ca4/materials-16-03073-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/f43176678e42/materials-16-03073-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/10143340/52086a4f4fdb/materials-16-03073-g015.jpg

相似文献

1
Identify the Micro-Parameters for Optimized Discrete Element Models of Granular Materials in Two Dimensions Using Hexagonal Close-Packed Structures.使用六边形密堆积结构识别二维颗粒材料优化离散元模型的微观参数。
Materials (Basel). 2023 Apr 13;16(8):3073. doi: 10.3390/ma16083073.
2
Cross-Functional Test to Explore the Determination Method of Meso-Parameters in the Discrete Element Model of Asphalt Mixtures.跨功能测试以探索沥青混合料离散元模型中细观参数的确定方法
Materials (Basel). 2021 Oct 3;14(19):5786. doi: 10.3390/ma14195786.
3
Investigating the Functions of Particles in Packed Aggregate Blend using a Discrete Element Method.使用离散元法研究粒料在密实集料混合料中的作用。
Materials (Basel). 2019 Feb 13;12(4):556. doi: 10.3390/ma12040556.
4
Shear Deformation Behavior of a Double-Layer Asphalt Mixture Based on the Virtual Simulation of a Uniaxial Penetration Test.基于单轴贯入试验虚拟模拟的双层沥青混合料剪切变形行为
Materials (Basel). 2020 Aug 21;13(17):3700. doi: 10.3390/ma13173700.
5
Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry.离散元法在制药行业制造过程模拟中的应用
Pharmaceutics. 2019 Aug 15;11(8):414. doi: 10.3390/pharmaceutics11080414.
6
A Simplified Calibration Procedure for DEM Simulations of Granular Material Flow.颗粒材料流动离散单元法模拟的一种简化校准程序
Materials (Basel). 2024 Sep 30;17(19):4833. doi: 10.3390/ma17194833.
7
Effects of Aggregate Mesostructure on Permanent Deformation of Asphalt Mixture Using Three-Dimensional Discrete Element Modeling.基于三维离散元模型的集料细观结构对沥青混合料永久变形的影响
Materials (Basel). 2019 Nov 2;12(21):3601. doi: 10.3390/ma12213601.
8
Multicomponent granular mixing in a Bohle bin Blender-Experiments and simulation.多组分颗粒在 Bohle 仓混合机中的混合-实验与模拟。
Int J Pharm. 2020 Mar 30;578:119131. doi: 10.1016/j.ijpharm.2020.119131. Epub 2020 Feb 11.
9
Self-assembly of granular spheres under one-dimensional vibration.颗粒球在一维振动下的自组装。
Soft Matter. 2018 Dec 12;14(48):9856-9869. doi: 10.1039/c8sm01763h.
10
Inversion Method of the Young's Modulus Field and Poisson's Ratio Field for Rock and Its Test Application.岩石杨氏模量场和泊松比场的反演方法及其试验应用
Materials (Basel). 2022 Aug 8;15(15):5463. doi: 10.3390/ma15155463.

引用本文的文献

1
Experimental Testing and Constitutive Modelling of Pavement Materials.路面材料的试验测试与本构模型
Materials (Basel). 2023 Jun 5;16(11):4186. doi: 10.3390/ma16114186.

本文引用的文献

1
Cold In-Place Recycling Asphalt Mixtures: Laboratory Performance and Preliminary M-E Design Analysis.就地冷再生沥青混合料：实验室性能及初步力学经验设计分析
Materials (Basel). 2021 Apr 18;14(8):2036. doi: 10.3390/ma14082036.