CFD-DEM modelling of the conveying characteristics of a vertical pipeline for deep-sea mineral particles with wide particle size gradations.
Saved in:
| Title: | CFD-DEM modelling of the conveying characteristics of a vertical pipeline for deep-sea mineral particles with wide particle size gradations. |
|---|---|
| Authors: | Li, Tiansong1 (AUTHOR), He, Liyong2 (AUTHOR), Shen, Jiahe1,3 (AUTHOR) jiahe.shen@whut.edu.cn, Yuan, Jianming1,3 (AUTHOR), Jin, Chenglong1 (AUTHOR), Liu, Zhiyuan1 (AUTHOR) |
| Source: | Powder Technology. Mar2025, Vol. 453, pN.PAG-N.PAG. 1p. |
| Subjects: | Discrete element method, Computational fluid dynamics, Ocean mining, Energy consumption, Velocity |
| Abstract: | In this study, the Computational Fluid Dynamics (CFD) and the Discrete Element Method (DEM) are coupled to simulate the particle velocity and distribution, the conveying stability and energy efficiency of large-size and wide-gradation mineral particles in a vertical pipeline, and the accuracy of the coupled model is validated by comparing with previous experimental data. The effects of the conveying speed, the initial concentration and the Particle Size Gradations (PSGs) are investigated. The results of the particle behaviour show that small particles tend to move towards the pipeline centre, while large particles tend to accumulate around the pipeline wall during conveying. The particles are forced to disperse, leading to a more uniform distribution at a high conveying speed and low initial concentration. The conveying performance, including the particle velocities, the conveying stability and the energy efficiency can be improved by increasing the proportion of small particles. [Display omitted] • A coupled CFD-DEM model is developed to analyse particle behaviour. • The conveying performance with wide particle size gradations is studied. • Increasing proportion of small particles improves conveying performance. • The particle size gradation can influence energy efficiency. [ABSTRACT FROM AUTHOR] |
| Copyright of Powder Technology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!
