Improving grinding efficiency and performance of new impeller type ball mill using discrete element method simulations and Taguchi method

Abstract In this paper, a new grinding method utilizing impeller‐driven particle motions was proposed. A discrete element kinetic model for simulating the grinding process of SiO 2 material was established. Through the quantitative analysis of energy conversion during grinding, the kinetic energy of particles, the kinetic energy of materials, and the energy consumed by materials were identified as three indicators for evaluating the grinding efficiency and performance of the ball mill. The optimal impeller structural parameters for improving the energy conversion efficiency of the ball mill were determined using the Taguchi method. The grinding efficiency and microstructure performance of the impeller type and traditional ball mills were compared. The results show that the energy loss between the materials and impeller accounted for the most significant proportion, about 30.4% of the total conversion energy. Based on the signal‐to‐noise ratio analysis, the optimum structural parameters of the impeller were obtained as follows: the height–diameter ratio of 1/2, blade thickness of 3 mm, inclination angle of 80°, and blade number of 5. Compared with planetary and horizontal ball mills, the average particle size of powders ground with the impeller‐type ball mill improved by 8.16% and 11.38%, respectively, and the particle uniformity increased by 1.22% and 26.5%.

Authors

Institutions

Publication Details

Journal
International Journal of Applied Ceramic Technology
Published
2024-12-12
DOI
https://doi.org/10.1111/ijac.15009
Primary Topic
Mineral Processing and Grinding
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improving grinding efficiency and performance of new impeller type ball mill using discrete element method simulations and Taguchi method

Zhiwen Liu, F. Li, Dan Zeng, Mingjun Zhang et al.
International Journal of Applied Ceramic Technology
Mineral Processing and Grinding
article

Improving grinding efficiency and performance of new impeller type ball mill using discrete element method simulations and Taguchi method

Zhiwen Liu, F. Li, Dan Zeng, Mingjun Zhang, Daiwei Li
article en

Abstract

Abstract In this paper, a new grinding method utilizing impeller‐driven particle motions was proposed. A discrete element kinetic model for simulating the grinding process of SiO 2 material was established. Through the quantitative analysis of energy conversion during grinding, the kinetic energy of particles, the kinetic energy of materials, and the energy consumed by materials were identified as three indicators for evaluating the grinding efficiency and performance of the ball mill. The optimal impeller structural parameters for improving the energy conversion efficiency of the ball mill were determined using the Taguchi method. The grinding efficiency and microstructure performance of the impeller type and traditional ball mills were compared. The results show that the energy loss between the materials and impeller accounted for the most significant proportion, about 30.4% of the total conversion energy. Based on the signal‐to‐noise ratio analysis, the optimum structural parameters of the impeller were obtained as follows: the height–diameter ratio of 1/2, blade thickness of 3 mm, inclination angle of 80°, and blade number of 5. Compared with planetary and horizontal ball mills, the average particle size of powders ground with the impeller‐type ball mill improved by 8.16% and 11.38%, respectively, and the particle uniformity increased by 1.22% and 26.5%.

International Journal of Applied Ceramic TechnologyVol. 22(3)
Central South University (CN), Changsha University of Science and Technology (CN), Nanjing University (CN), University of South China (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hunan Province
Affordable and clean energy
Openalex Percentile: Top 77%
Mineral Processing and Grinding
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.