Abstract
A milling process is one of the important unit processes in mineral processing. In the milling process, the control of particle size distribution is necessary for the later physical separation process. Since the milling process is strongly affected by the equipment designs, operation conditions and raw materials, the control for particle size distribution of milling products is mainly based on empirical rules. Recently, the discrete element method (DEM) has been widely used as an effective tool to investigate the behavior of grinding media. Although the behavior of grinding media can be accurately simulated, it is not well-established the way to predict particle size distribution after milling by the DEM simulation. The objective of this study was to develop a new method to predict particle size distribution in ball milling using the DEM simulation. To predict particle size reduction, a correlation between experiments and the simulation was investigated in various operation conditions, that is, wide range of the rotation speed and the filling ratio of grinding media. In experiments, after lime stone was ground, the average and variance of particle size distribution were evaluated using some kinds of distribution equations. In the DEM simulation, direct simulation of particle disintegration in milling process is generally very difficult because of huge computational load. Therefore, collision energy between grinding media balls or grinding media ball and wall was used as a factor of particle disintegration. As a result, a good correlation between experiments and simulation was obtained. In addition, the particle size distribution in ball milling could be predicted using this correlation. Therefore, these results indicated that the use of the correlation between experiments and the DEM simulation was an effective approach of predicting the particle size distribution in milling process.
| Original language | English |
|---|---|
| Title of host publication | IMPC 2016 - 28th International Mineral Processing Congress |
| Publisher | Canadian Institute of Mining, Metallurgy and Petroleum |
| Volume | 2016-September |
| ISBN (Electronic) | 9781926872292 |
| Publication status | Published - 2016 Jan 1 |
| Event | 28th International Mineral Processing Congress, IMPC 2016 - Quebec City, Canada Duration: 2016 Sep 11 → 2016 Sep 15 |
Other
| Other | 28th International Mineral Processing Congress, IMPC 2016 |
|---|---|
| Country | Canada |
| City | Quebec City |
| Period | 16/9/11 → 16/9/15 |
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Keywords
- Ball mill
- Discrete element simulation
- Grinding
- Milling process
- Particle size distribution
ASJC Scopus subject areas
- Geochemistry and Petrology
- Geotechnical Engineering and Engineering Geology
- Mechanical Engineering
- Earth-Surface Processes
Cite this
Prediction of particle size distribution in milling process using discrete element method. / Fukui, Sho; Tsunazawa, Yuki; Tokoro, Chiharu.
IMPC 2016 - 28th International Mineral Processing Congress. Vol. 2016-September Canadian Institute of Mining, Metallurgy and Petroleum, 2016.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Prediction of particle size distribution in milling process using discrete element method
AU - Fukui, Sho
AU - Tsunazawa, Yuki
AU - Tokoro, Chiharu
PY - 2016/1/1
Y1 - 2016/1/1
N2 - A milling process is one of the important unit processes in mineral processing. In the milling process, the control of particle size distribution is necessary for the later physical separation process. Since the milling process is strongly affected by the equipment designs, operation conditions and raw materials, the control for particle size distribution of milling products is mainly based on empirical rules. Recently, the discrete element method (DEM) has been widely used as an effective tool to investigate the behavior of grinding media. Although the behavior of grinding media can be accurately simulated, it is not well-established the way to predict particle size distribution after milling by the DEM simulation. The objective of this study was to develop a new method to predict particle size distribution in ball milling using the DEM simulation. To predict particle size reduction, a correlation between experiments and the simulation was investigated in various operation conditions, that is, wide range of the rotation speed and the filling ratio of grinding media. In experiments, after lime stone was ground, the average and variance of particle size distribution were evaluated using some kinds of distribution equations. In the DEM simulation, direct simulation of particle disintegration in milling process is generally very difficult because of huge computational load. Therefore, collision energy between grinding media balls or grinding media ball and wall was used as a factor of particle disintegration. As a result, a good correlation between experiments and simulation was obtained. In addition, the particle size distribution in ball milling could be predicted using this correlation. Therefore, these results indicated that the use of the correlation between experiments and the DEM simulation was an effective approach of predicting the particle size distribution in milling process.
AB - A milling process is one of the important unit processes in mineral processing. In the milling process, the control of particle size distribution is necessary for the later physical separation process. Since the milling process is strongly affected by the equipment designs, operation conditions and raw materials, the control for particle size distribution of milling products is mainly based on empirical rules. Recently, the discrete element method (DEM) has been widely used as an effective tool to investigate the behavior of grinding media. Although the behavior of grinding media can be accurately simulated, it is not well-established the way to predict particle size distribution after milling by the DEM simulation. The objective of this study was to develop a new method to predict particle size distribution in ball milling using the DEM simulation. To predict particle size reduction, a correlation between experiments and the simulation was investigated in various operation conditions, that is, wide range of the rotation speed and the filling ratio of grinding media. In experiments, after lime stone was ground, the average and variance of particle size distribution were evaluated using some kinds of distribution equations. In the DEM simulation, direct simulation of particle disintegration in milling process is generally very difficult because of huge computational load. Therefore, collision energy between grinding media balls or grinding media ball and wall was used as a factor of particle disintegration. As a result, a good correlation between experiments and simulation was obtained. In addition, the particle size distribution in ball milling could be predicted using this correlation. Therefore, these results indicated that the use of the correlation between experiments and the DEM simulation was an effective approach of predicting the particle size distribution in milling process.
KW - Ball mill
KW - Discrete element simulation
KW - Grinding
KW - Milling process
KW - Particle size distribution
UR - http://www.scopus.com/inward/record.url?scp=85048339082&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048339082&partnerID=8YFLogxK
M3 - Conference contribution
VL - 2016-September
BT - IMPC 2016 - 28th International Mineral Processing Congress
PB - Canadian Institute of Mining, Metallurgy and Petroleum
ER -