| ELECTROMAGNETISM, OPTICS, ACOUSTICS, HEAT TRANSFER, CLASSICAL MECHANICS, AND FLUID DYNAMICS |
Prev
Next
|
|
|
Velocity scaling of granular flow in silos under different discharge modes |
| Tongtong Mu(牟彤彤)1,2, Quan Chen(陈泉)1, Wenjing Wang(王文静)3, Ran Li(李然)1, Ge Sun(孙歌)1,2, and Hui Yang(杨晖)2,1,† |
1 School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
2 College of Medical Instrumentation, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China;
3 School of Physical Science and Technology, ShanghaiTech University, Shanghai 201318, China |
|
|
|
|
Abstract Accurately measuring the velocity field of granular flow in silos and elucidating the distribution law under different discharge modes are essential for understanding the mechanisms of granular rheology and optimizing discharge system design. This work investigates the flow characteristics of black electroplated glass beads in a two-dimensional silo under free-fall discharge and conveyor-belt discharge. The particle tracking velocimetry (PTV) method is employed to measure the velocity field, and the distribution characteristics under the two modes are systematically compared and analyzed. The results show that although there are significant differences in the numerical values of granular velocity, the normalized velocity profiles remain highly consistent. On this basis, a quantitative relationship between the velocity profiles under the two discharge modes is established through the kinematic model. This reveals that the differences in velocity profiles caused by the discharge modes essentially correspond to magnitude scaling, while the overall flow characteristics remain invariant. This finding not only provides a predictive model for the velocity field under conveyor-belt discharge in silos but also contributes empirical data to advance the rheological theory of granular flow.
|
Received: 19 August 2025
Revised: 08 October 2025
Accepted manuscript online: 14 October 2025
|
|
PACS:
|
47.57.Gc
|
(Granular flow)
|
| |
47.57.-s
|
(Complex fluids and colloidal systems)
|
| |
47.80.Cb
|
(Velocity measurements)
|
|
| Fund: This work was supported by the National Natural Science Foundation of China (Grant Nos. 12202280 and 12372384) and the Shanghai Municipal Education Commission AI Program (Grant No. SHJWAIJK241201). |
Corresponding Authors:
Hui Yang
E-mail: yangh_23@sumhs.edu.cn
|
Cite this article:
Tongtong Mu(牟彤彤), Quan Chen(陈泉), Wenjing Wang(王文静), Ran Li(李然), Ge Sun(孙歌), and Hui Yang(杨晖) Velocity scaling of granular flow in silos under different discharge modes 2026 Chin. Phys. B 35 044701
|
[1] Mu Y F, Yao T A, Jia H J, Yu X D, Zhao B, Zhang X S, Ni C W and Du L J 2020 Appl. Energy 275 115368
[2] Huang T C, Wu B, Xie F P, Qian H Y, Li Z, Chen P and Xiang Q X 2024 Biosyst. Eng. 245 96
[3] Jiang S Y, Tu J Y, Yang X T and Gui N 2019 Exp. Comput. Multiph. Flow 1 159
[4] Bhateja A 2020 Phys. Rev. E 102 042904
[5] Choi J, Kudrolli A and Bazant M Z 2005 J. Phys.: Condens. Matter 17 S2533
[6] Bao D S, Zhang X S, Xu G L, Pan Z Q, Tang X W and Lu K Q 2003 Phys. Rev. E 67 062301
[7] Gella D, Zuriguel I and Maza D 2020 Phys. Rev. Lett. 121 138001
[8] Nedderman R and Tüzün U 1979 Powder Technol. 22 243
[9] Nedderman R, Tüzün U, Savage S and Houlsby G 1982 Chem. Eng. Sci. 37 1597
[10] Hsiau S S and Hunt M L 1993 J. Fluid Mech. 251 299
[11] Natarajan V V R, Hunt M L and Taylor E D 1995 J. Fluid Mech. 304 1
[12] Chen Q, Li R, XiuWZ, Zivkovic V and Yang H 2021 Powder Technol. 392 123
[13] Medina A, Córdova J, Luna E and Treviño C 1998 Phys. Lett. A 250 111
[14] Zuriguel I, Maza D, Janda A, Hidalgo R C and Garcimartín A 2019 Granular Matter 21 47
[15] Gella D, Zuriguel I and Ortín J 2019 Phys. Rev. Lett. 123 218004
[16] Gella D, Maza D and Zuriguel I 2020 Powder Technol. 360 104
[17] Janda A, Zuriguel I and Maza D 2012 Phys. Rev. Lett. 108 248001
[18] Gella D, Maza D and Zuriguel I 2021 J. Fluid Mech. 925 A24
[19] Fan B, Zuriguel I, Dijksman J A, Gucht J and Börzsönyi T 2023 Phys. Rev. E 108 044902
[20] Wang B D, Song J, Li R, Han R, Zheng G and Yang H 2020 Chin. Phys. B 29 014207
[21] Shi J and Tomasi 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, June 21-23, 1994, Seattle, WA, USA, pp. 593
[22] Sharmin N and Brad R 2012 Sensors 12 12694
[23] Sun G, Chen Q, Li R, Zheng Z, Xin Y J and Yang H 2022 Powder Technol. 409 117770
[24] Shi S S, Wu P, Jiang M X, Chen B D, Zhang S P, Dong C Y and Wang L 2025 Powder Technol. 452 120562
[25] Zhu H and Yu A B 2005 Granular Matter 7 97
[26] Cruz F, Emam S, Prochnow M, Roux J N and Chevoir F 2005 Phys. Rev. E 72 021309
[27] Laurent B, Krzysztof G, Selam W, Konrad M, Jerome A and Eric M 2020 Comput. Electron. Agric. 172 105346
[28] Zhu H, Yu A B and Wu Y 2006 Powder Technol. 170 125
[29] Alani O, Abraim M, Ghennioui H, Ghennioui A, Ikenbi I and Dahr F E 2021 Energy Rep. 7 888 |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|
