王清泽,杨梅,向金田,张强林,张文洁,李旭杰,胡靖明.基于颗粒缩放理论的沙棘茶毫离散元参数标定[J].干旱地区农业研究,2024,(2):284~292
基于颗粒缩放理论的沙棘茶毫离散元参数标定
Discrete element parameters calibration of Hippophae rhamnoides based on particle scaling theory
  
DOI:10.7606/j.issn.1000-7601.2024.02.30
中文关键词:  沙棘  茶毫粉尘  颗粒缩放理论  离散元  参数标定
英文关键词:Hippophae rhamnoides  tea dust  particle scaling theory  DEM  parameter calibration
基金项目:国家自然科学基金 (52065006);甘肃省科技计划资助项目(22YF7NA114)
作者单位
王清泽 甘肃农业大学机电工程学院甘肃 兰州 730070 
杨梅 甘肃农业大学机电工程学院甘肃 兰州 730070 
向金田 甘肃农业大学机电工程学院甘肃 兰州 730070 
张强林 甘肃农业大学机电工程学院甘肃 兰州 730070 
张文洁 甘肃农业大学机电工程学院甘肃 兰州 730070 
李旭杰 甘肃农业大学机电工程学院甘肃 兰州 730070 
胡靖明 甘肃农业大学机电工程学院甘肃 兰州 730070 
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中文摘要:
      为解决沙棘叶茶茶毫离散元仿真中缺乏准确接触参数的问题,利用物理和仿真休止角堆积试验标定茶毫接触参数;将茶毫颗粒简化为软质球形颗粒,通过量纲分析和颗粒缩放理论将茶毫空气动力学当量粒径从231.37 μm放大至1.8 mm。利用EDEM软件,选定“Hertz–Mindlin with JKR”接触模型,以休止角为响应值,通过Plackett-Burman试验筛选出对休止角影响最显著的3个参数:茶毫-茶毫恢复系数、茶毫-茶毫滚动摩擦系数、茶毫-不锈钢滚动摩擦系数;利用最陡爬坡试验,确定各参数最佳取值范围;根据Box-Behnken试验建立并优化3个显著性参数与休止角的二阶回归方程,对回归方程进行寻优求解。得到3个显著性参数的最优组合:茶毫-茶毫恢复系数为0.159,茶毫-茶毫滚动摩擦系数为0.290,茶毫-不锈钢滚动摩擦系数为0.239。通过对比休止角仿真试验值与物理试验值,二者相对误差为1.97%,表明仿真试验预测效果良好。
英文摘要:
      To address the lack of accurate contact parameters in the discrete element simulation of sea buckthorn leaf tea hair, a physical and simulation resting angle heap experiment was conducted to calibrate the contact parameters of tea hair. The tea hair particles were simplified as soft spherical particles. By dimensional analysis and particle scaling theory, the aerodynamic equivalent diameter of tea hair was enlarged from 231.37 μm to 1.8 mm. The EDEM software was used with the “Hertz\|Mindlin with JKR” contact model. The repose angle was chosen as the response variable, and a Plackett\|Burman experiment was performed to select the three most significant parameters affecting the resting angle: the tea hair\|tea hair restitution coefficient, the tea hair\|tea hair rolling friction coefficient, and the tea hair\|stainless steel rolling friction coefficient. The optimal parameter ranges were determined using a steepest ascent test. Based on Box\|Behnken experimental design, a second\|order regression equation was established and optimized for the three significant parameters and repose angle. The three significant parameters for the optimal combination were as follow: tea hair\|tea hair restitution coefficient was 0.159, tea hair\|tea hair rolling friction coefficient was 0.290, and tea hair\|stainless steel rolling friction coefficient was 0.239. A comparative analysis between the simulated repose angle values and the real values from physical experiments yielded a relative error was 1.97%, indicating good predictive performance in simulation experiments.
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