东北大学学报:自然科学版 ›› 2016, Vol. 37 ›› Issue (9): 1264-1268.DOI: 10.12068/j.issn.1005-3026.2016.09.011

• 机械工程 • 上一篇    下一篇

基于离散元和全析因实验设计的BPM力学参数

李强1, 巩亚东1, 宋伟刚1, 及钊2   

  1. (1. 东北大学 机械工程与自动化学院, 辽宁 沈阳110819; 2. 吉林大学 机械科学与工程学院, 吉林 长春130025)
  • 收稿日期:2015-05-29 修回日期:2015-05-29 出版日期:2016-09-15 发布日期:2016-09-18
  • 通讯作者: 李强
  • 作者简介:李强(1986-),男,辽宁沈阳人,东北大学博士研究生; 巩亚东(1958-),男,辽宁本溪人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(51375082).

BPM Mechanical Parameters Based on Discrete Element Method and Full Factorial Experiment Design

LI Qiang1, GONG Ya-dong1, SONG Wei-gang1, JI Zhao2   

  1. 1. School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China; 2. School of Mechanical Science and Engineering, Jilin University, Changchun 130025, China.
  • Received:2015-05-29 Revised:2015-05-29 Online:2016-09-15 Published:2016-09-18
  • Contact: LI Qiang
  • About author:-
  • Supported by:
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摘要: 为研究岩石微观力学参数与宏观力学性能之间关系并提高岩石破碎离散元仿真效率,从破碎原理出发,基于EDEM进行单轴压缩数值分析,研究摩擦系数、材料剪切模量、微观颗粒个数、平行键强度和刚度对岩石抗压强度和宏观刚度的影响.再通过全析因实验设计得到影响岩石力学性能关键的主效应和交互效应,并以此为变量运用回归方法对黏结颗粒模型(bonded particle model,简称BPM)的宏观力学参数进行预测并进行方差、拟合优度和残差分析.仿真及物理实验结果证明该预测模型可行,误差率小于10%.

关键词: 离散元方法, 全析因实验, 黏结颗粒模型, 回归分析, 破碎原理

Abstract: In order to investigate the relationship between microscopic and macroscopic mechanical properties of rock, and to improve the efficiency of rock breakage simulation in EDEM (extended discrete element method ), samples for breakage simulation were prepared. Based on the breakage principle, EDEM was used to simulate rock uniaxial compression test. The influence of friction coefficient, shear modulus, micro particle number, parallel bond strength and stiffness on compressive strength and macro stiffness was analyzed. The key and interaction effects were obtained by the full factorial experiment. Regression analysis method was used to predict BPM macroscopic mechanical parameters and to analyze the variance, goodness of fit and residuals. The results show that the error rate of prediction model is less than 10%.

Key words: discrete element method(DEM), full factorial experiment, BPM(bonded particle model), regression analysis, breakage principle

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