Optimizing key parameters for grinding energy efficiency and modeling of particle size distribution in a stirred ball mill
Abstract Fine grinding using a stirred ball mill can enhance ore liberation but incurs high energy consumption, which can be minimized by optimizing operating conditions. This study explores the impact of key operational parameters—grinding time, stirrer tip speed, solid concentration, and feed size...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-025-87229-8 |
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| author | Abdalla M. Elbendari Suzan S. Ibrahim |
| author_facet | Abdalla M. Elbendari Suzan S. Ibrahim |
| author_sort | Abdalla M. Elbendari |
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| description | Abstract Fine grinding using a stirred ball mill can enhance ore liberation but incurs high energy consumption, which can be minimized by optimizing operating conditions. This study explores the impact of key operational parameters—grinding time, stirrer tip speed, solid concentration, and feed size—on grinding efficiency, evaluated using specific energy inputs, in stirred milling of Egyptian copper ore. The particle size distribution (PSD) of ground products was simulated using the Gates–Gaudin-Schuhmann model (GGS) and the Rosin-Rammler-Benne (RRB) function. Taking minimum energy consumption into account, the finest particles (100% ~1 μm) were achieved at the maximum stirrer speed of 500 rpm and a moderate solid concentration of 33.3% after 17 h of grinding, consuming approximately 1225 kWh/t. Experimental data demonstrated a linear correlation between the natural logarithm of the cumulative retained fraction and particle size (µm). The proposed model accurately describes PSDs across different solid concentrations and grinding durations. |
| format | Article |
| id | doaj-art-258d8f7f91484958ad62b2bc82cc7cb4 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-258d8f7f91484958ad62b2bc82cc7cb42025-02-02T12:21:58ZengNature PortfolioScientific Reports2045-23222025-01-0115111810.1038/s41598-025-87229-8Optimizing key parameters for grinding energy efficiency and modeling of particle size distribution in a stirred ball millAbdalla M. Elbendari0Suzan S. Ibrahim1Minerals Beneficiation and Agglomeration Department, Minerals Technology Institute, Central Metallurgical Research & Development Institute (CMRDI)Minerals Beneficiation and Agglomeration Department, Minerals Technology Institute, Central Metallurgical Research & Development Institute (CMRDI)Abstract Fine grinding using a stirred ball mill can enhance ore liberation but incurs high energy consumption, which can be minimized by optimizing operating conditions. This study explores the impact of key operational parameters—grinding time, stirrer tip speed, solid concentration, and feed size—on grinding efficiency, evaluated using specific energy inputs, in stirred milling of Egyptian copper ore. The particle size distribution (PSD) of ground products was simulated using the Gates–Gaudin-Schuhmann model (GGS) and the Rosin-Rammler-Benne (RRB) function. Taking minimum energy consumption into account, the finest particles (100% ~1 μm) were achieved at the maximum stirrer speed of 500 rpm and a moderate solid concentration of 33.3% after 17 h of grinding, consuming approximately 1225 kWh/t. Experimental data demonstrated a linear correlation between the natural logarithm of the cumulative retained fraction and particle size (µm). The proposed model accurately describes PSDs across different solid concentrations and grinding durations.https://doi.org/10.1038/s41598-025-87229-8Sub-micron grindingStirred ball millSpecific energy inputCumulative oversize distribution predictionSignature plot |
| spellingShingle | Abdalla M. Elbendari Suzan S. Ibrahim Optimizing key parameters for grinding energy efficiency and modeling of particle size distribution in a stirred ball mill Scientific Reports Sub-micron grinding Stirred ball mill Specific energy input Cumulative oversize distribution prediction Signature plot |
| title | Optimizing key parameters for grinding energy efficiency and modeling of particle size distribution in a stirred ball mill |
| title_full | Optimizing key parameters for grinding energy efficiency and modeling of particle size distribution in a stirred ball mill |
| title_fullStr | Optimizing key parameters for grinding energy efficiency and modeling of particle size distribution in a stirred ball mill |
| title_full_unstemmed | Optimizing key parameters for grinding energy efficiency and modeling of particle size distribution in a stirred ball mill |
| title_short | Optimizing key parameters for grinding energy efficiency and modeling of particle size distribution in a stirred ball mill |
| title_sort | optimizing key parameters for grinding energy efficiency and modeling of particle size distribution in a stirred ball mill |
| topic | Sub-micron grinding Stirred ball mill Specific energy input Cumulative oversize distribution prediction Signature plot |
| url | https://doi.org/10.1038/s41598-025-87229-8 |
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