Citation: | LI Bo,LIU Bei,ZHANG Peng,et al. A two-scale coarse-grained discrete element methodand experimental verification of bulk coal[J]. Coal Science and Technology,2024,52(3):225−235. DOI: 10.12438/cst.2023-1065 |
The discrete element method (DEM) is commonly used for simulating particle systems at the engineering scale, but computational efficiency remains a limiting factor for large-scale particle system simulations. Existing coarse-grained methods have limited applicability and lack a universal theoretical basis. To address this issue, this study utilizes dimensional analysis to describe the scaling laws of physical quantities in an exact scaled system. By using representative volume elements (RVE), approximate conservation relationships for mass, momentum, and energy are established between the coarse-grained system and the original system. Scaling relationships for corresponding physical quantities at two different scales (global and particle level) are obtained.To validate the correctness of the proposed two-scale coarse-grained DEM method, the method is applied to the falling and rotation tests of bulk coal. The particle size in the actual tests is 4mm, while in the simulations, five groups of coal particles with different scaling coefficients ranging from 4 mm to 12 mm are used. The total volume of bulk coal in both the tests and simulations is 0.001 m3. The falling test of bulk coal uses the average impact force and the reposeangle as comparative indicators. The results show that as the particle size of coal increases, the relative errors of both indicators generally increase (at a particle size of 12 mm, the error in impact force is 14.36%, and the error in the reposeangle is 19.05%).The rotational test of bulk coal uses the correlation coefficient between the applied force on the upper sample and the profile curve of the bulk coal heap as a comparative indicator. The results show that as the particle size increases, the relative error increases, and the correlation coefficient generally decreases (at a particle size of 12 mm, the force error is 39.29%, and the correlation coefficient is
[1] |
ROUABAH M,BOURGEOIS S,BRIANON S,et al. A numerical tool to predict powder behaviour for pharmaceutical handling and processing[J]. Journal of Drug Delivery Science and Technology,2022,70:103258. doi: 10.1016/j.jddst.2022.103258
|
[2] |
ZENGY,MAOB Q,JIAF G,et al. Modelling of grain breakage of in a vertical rice mill based on DEM simulation combining particle replacement model[J]. Biosystems Engineering,2022,215:32−48. doi: 10.1016/j.biosystemseng.2021.12.022
|
[3] |
XU WJ,WANG L,CHENG K. The failure and river blocking mechanism of large-scale anti-dip rock landslide induced by earthquake[J]. Rock Mechanics and Rock Engineering,2022,55(8):4941−4961. doi: 10.1007/s00603-022-02903-x
|
[4] |
张美晨,赵丽娟,李明昊,等. 基于双向耦合法的采煤机螺旋滚筒振动特性分析及实验研究[J]. 煤炭科学技术,2024,52(3):200−216
ZHANG Meichen,ZHAO Lijuan,LIM inghao, et al. Analysis and experimental study on the vibration characteristics of the spiral drum of a shearer based on two-way coupling methods[J]. Journal of China Coal Society,2024,52(3):200−216
|
[5] |
ZHAO Y,SUN X X,MENG W J. Research on the axial velocity of the raw coal particles in vertical screw conveyor by using the discrete element method[J]. Journal of Mechanical Science and Technology,2021,35(6):2551−2560. doi: 10.1007/s12206-021-0526-z
|
[6] |
WANG Z Q,WANG X J,ZHUANG J J,et al. Multiple parameter collaborative optimization of a particle separation equipment for coal cleaning production[J]. Journal of Environmental Chemical Engineering,2021,9(4):105646. doi: 10.1016/j.jece.2021.105646
|
[7] |
GAN J Q,ZHOU Z Y,YU A B. A GPU-based DEM approach for modelling of particulate systems[J]. Powder Technology,2016,301:1172−1182. doi: 10.1016/j.powtec.2016.07.072
|
[8] |
KUWAGI K,MOKHTAR M A,OKADA H, et al. Numerical experiment of thermoset particles in surface modification system with discrete element method (Quantization of cohesive force between particles by agglomerates analysis)[J]. Numerical Heat Transfer,Part A:Applications,2009,56(8):647−664.
|
[9] |
MOKHTAR M A,KUWAGI K,TAKAMI T,et al. Validation of the similar particle assembly (SPA) model for the fluidization of Geldart's group A and D particles[J]. AIChE Journal,2012,58(1):87−98. doi: 10.1002/aic.12568
|
[10] |
SAKAI M,ABE M,SHIGETO Y,et al. Verification and validation of a coarse grain model of the DEM in a bubbling fluidized bed[J]. Chemical Engineering Journal,2014,244:33−43. doi: 10.1016/j.cej.2014.01.029
|
[11] |
SAKAIM,KOSHIZUKA S. Large-scale discrete element modeling in pneumatic conveying[J]. Chemical Engineering Science,2009,64(3):533−539. doi: 10.1016/j.ces.2008.10.003
|
[12] |
TAKABATAKEK,MORIY,KHINASTJG,et al. Numerical investigation of a coarse-grain discrete element method in solid mixing in a spouted bed[J]. Chemical Engineering Journal,2018,346:416−426. doi: 10.1016/j.cej.2018.04.015
|
[13] |
BIERWISCHC,KRAFTT,RIEDEL H,et al. Three-dimensional discrete element models for the granular statics and dynamics of powders in cavity filling[J]. Journal of the Mechanics and Physics of Solids,2009,57(1):10−31. doi: 10.1016/j.jmps.2008.10.006
|
[14] |
NAKAMURAH,TAKIMOTO H,KISHIDA N,et al. Coarse-grained discrete element method for granular shear flow[J]. Chemical Engineering Journal Advances,2020,4:100050. doi: 10.1016/j.ceja.2020.100050
|
[15] |
KISHIDAN,NAKAMURA H,TAKIMOTOH,et al. Coarse-grained discrete element simulation of particle flow and mixing in a vertical high-shear mixer[J]. Powder Technology,2021,390:1−10. doi: 10.1016/j.powtec.2021.05.028
|
[16] |
LU L Q,XU J,GE W,et al. EMMS-based discrete particle method (EMMS–DPM) for simulation of gas–solid flows[J]. Chemical Engineering Science,2014,120:67−87. doi: 10.1016/j.ces.2014.08.004
|
[17] |
CHU K W,CHEN J,YU A B. Applicability of a coarse-grained CFD–DEM model on dense medium cyclone[J]. Minerals Engineering,2016,90:43−54. doi: 10.1016/j.mineng.2016.01.020
|
[18] |
TAUSENDSCHÖNJ,KOLEHMAINENJ,SUNDARESAN S,et al. Coarse graining Euler-Lagrange simulations of cohesive particle fluidization[J]. Powder Technology,2020,364:167−182. doi: 10.1016/j.powtec.2020.01.056
|
[19] |
程宏旸,THOMAS Weinhart. 关于采用粗粒化提高颗粒材料多尺度模拟守恒特性的研究[J]. 计算力学学报,2022,39(3):373−380. doi: 10.7511/jslxCMGM202214
CHENG Hongyang,THOMAS Weinhart. On the conservation properties of CG-enriched concurrent coupling methods for muti-scale modeling of granular materials[J]. Chinese Journal of Computational Mechanics,2022,39(3):373−380. doi: 10.7511/jslxCMGM202214
|
[20] |
FENG Y T,HAN K,Owen D R J,et al. On upscaling of discrete element models:similarity principles[J]. Engineering Computations,2009,26:599−609. doi: 10.1108/02644400910975405
|
[21] |
FENG Y T,OWEN D R J. Discrete element modelling of large scale particle systems—I:exact scaling laws[J]. Computational Particle Mechanics,2014,1:159−168. doi: 10.1007/s40571-014-0010-y
|
[22] |
赵婷婷,冯云田. 大规模颗粒系统的精确缩尺和粗粒化离散元方法[J]. 计算力学学报,2022,39:365−372.
ZHAO Tingting,FENG Yuntian. Exact scaling laws and coarse-grained discrete element modellingof largescale granular systems[J]. Chinese Journal of Computational Mechanics,2022,39:365−372.
|
[23] |
XIA R,LI B,WANG X W,et al. Measurement and calibration of the discrete element parameters of wet bulk coal[J]. Measurement,2019,142:84−95. doi: 10.1016/j.measurement.2019.04.069
|
[24] |
WANG Z S,LI B,LIANG C,et al. Response analysis of a scraper conveyor under chain faults based on MBD-DEM-FEM[J]. Strojniski Vestnik-Journal of Mechanical Engineering,2021,67(10):501−516. doi: 10.5545/sv-jme.2021.7300
|
[25] |
李铁军,王学文,李 博,等. 基于离散元法的煤颗粒模型参数优化[J]. 中国粉体技术,2018,24(5):6−12.
LI Tiejun,WANG Xuewen,LI Bo, et al. Optimization method for coal particle model parameters based on discrete element method [J]. China Powder Science and Technology,2018,24(5):6−12.
|
[1] | YIN Yanchun, ZHENG Wuwei, ZHAO Tongbin, REN Wentao, ZHANG Wei, ZHAO Zhigang. Automatic measurement method of drilling-cuttings of boreholes in the coal seam and test study[J]. COAL SCIENCE AND TECHNOLOGY, 2023, 51(11): 23-32. DOI: 10.12438/cst.2022-2006 |
[2] | JIANG Yanhang, BAI Gang, ZHOU Xihua, WANG Yuxi, FU Tianyu, HU Kun. Test and analysis of coal adsorption volume of CH4[J]. COAL SCIENCE AND TECHNOLOGY, 2022, 50(12): 144-152. DOI: 10.13199/j.cnki.cst.2021-0617 |
[3] | ZHANG Jinhua, ZHANG Mengyuan, CHEN Yanpeng, CHEN Zhenhong, CHEN Hao, DONG Zhen, CHEN Shanshan, XUE Junjie. Progresses and revelation of underground coal gasification field test[J]. COAL SCIENCE AND TECHNOLOGY, 2022, 50(2): 213-222. |
[4] | TANG Jupeng, REN Lingran, PAN Yishan, ZHANG Xin. Simulation test study on coal and gas outburst under conditions of high in-situ stress[J]. COAL SCIENCE AND TECHNOLOGY, 2022, 50(2): 113-121. |
[5] | LIU Zhenling, ZHENG Zhongya. Simulation test study on temperature field evolution of coal spontaneous combustion in gob[J]. COAL SCIENCE AND TECHNOLOGY, 2020, 48(8): 114-120. |
[6] | SONG Jinxing, YU Shiyao, SU Xianbo. Study on velocity sensitivity damage mechanism and its proof test of coal reservoir[J]. COAL SCIENCE AND TECHNOLOGY, 2018, (6). |
[7] | Qin Hongxing Dai Guanglong Zhang Shuchuan Tang Mingyun, . Optimal selection and application of mark gas based on coal low temperature oxidation test[J]. COAL SCIENCE AND TECHNOLOGY, 2015, (6). |
[8] | Study on Model Test of Underground Gasification of Coking Coal[J]. COAL SCIENCE AND TECHNOLOGY, 2013, (5). |
[9] | Study on Coal Oxidized Dynamics Test with Low Temperature Based on CO Density[J]. COAL SCIENCE AND TECHNOLOGY, 2012, (3). |
[10] | Study on Permeability Comparison Tests with Two Different Gas Content Coal Samples[J]. COAL SCIENCE AND TECHNOLOGY, 2011, (8). |
1. |
徐乔木,赵星杰,卜侃侃. 旋转多斗装车系统受限空间内复杂粒度散料堆积特性研究. 煤. 2025(04): 86-91 .
![]() |