Validation of a coupled model of discrete element method with multibody kinematics to simulate the screening process of a swing-bar sieve
Validation of a coupled model of discrete element method with multibody kinematics to simulate the screening process of a swing-bar sieve
复制标题
离散元法与多体运动学耦合模型模拟摆杆筛筛选过程的验证
DOI：
10.1016/j.powtec.2019.01.076
复制
发表时间：
2019-03
影响因子：
5.2
通讯作者：
Jianqun Yu
中科院分区：
文献类型：
--
作者：
Yang Wang;Jianqun Yu
摆杆筛是一种广泛用于粮食分级、清洗和种子加工的分离设备。筛网甲板的运动是一种复杂的平面运动。本文以LA-LK实验室规模摆动杆筛和大豆颗粒为研究对象。提出了用实-虚边界法建立屏蔽甲板几何模型的方法。采用平面多体运动学对筛板的运动进行了建模。采用离散元法（DEM）和多体运动学（MBK）的耦合模型对大豆颗粒在筛板上的流动和通过进行了数值模拟。此外，还进行了LA-LK摆杆筛的实验研究。在不同粒径范围的大豆颗粒沿筛板的通过率分布方面，模拟结果与实验结果吻合较好。验证了本文提出的实虚边界法和DEM与MBK的耦合模型。该工作为摆杆筛的设计优化及相关研究提供了参考。
The swing-bar sieve is a separation machine that is widely used in grain grading and cleaning as well as seed processing. The motion of the screen deck is a complex planar motion. In this paper, the LA-LK laboratory scale swing-bar sieve and soybean particles are taken as the research objects. The real-virtual boundary method is proposed to build the geometrical model of the screen deck. The motion of the screen deck is modelled using the planar multibody kinematics. The flowing and passing of soybean particles on the screen deck are simulated by the coupled model of the discrete element method (DEM) with multibody kinematics (MBK). In addition, experiments using the LA-LK swing-bar sieve are conducted. The simulated results are in good agreement with those obtained experimentally in terms of the distributions of passing percentage for different size ranges of soybean particles along the screen deck. This verifies the real-virtual boundary method and the coupled model of DEM with MBK we proposed in this paper. This work provides a reference for the design optimization of the swing-bar sieve and the related research.
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DOI：
--
发表时间：
2005
期刊：
Journal of Jilin University of Technology
影响因子：
--
作者：
Fu Hong
通讯作者：
Fu Hong
DOI：
10.1016/s1674-5264(09)60092-2
发表时间：
2009-07
期刊：
Mining Science and Technology (china)
影响因子：
--
作者：
Yanhui Chen;Xin Tong
通讯作者：
Yanhui Chen;Xin Tong
影响因子：
4.7
作者：
Geoff P. Delaney;P. Cleary;M. Hilden;R. Morrison
通讯作者：
Geoff P. Delaney;P. Cleary;M. Hilden;R. Morrison
影响因子：
4.6
作者：
J. Li;C. Webb;S. Pandiella;G. Campbell
通讯作者：
J. Li;C. Webb;S. Pandiella;G. Campbell
DOI：
10.1016/s0378-4371(99)00183-1
发表时间：
1999-07-15
影响因子：
3.3
作者：
Zhou, YC;Wright, BD;Yu, AB
通讯作者：
Yu, AB