Grinding Modeling and Energy Efficiency in Ore/Raw Material Beneficiation

A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Processing and Extractive Metallurgy".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 11804

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Guest Editor
School of Mineral Resources Engineering, Technical University of Crete, 73100 Chania, Greece
Interests: mineral processing; grinding; modeling; material beneficiation
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Guest Editor

Special Issue Information

Dear Colleagues,

The grinding process, as a primary stage of ore/raw material processing, is a necessary operation in beneficiation plants. It not only provides the appropriate particle size for subsequent separation operations but also enables the liberation of valuable minerals from the gangue. In addition, due to the depletion of high-grade ores and the growing needs of the industry for the processing of low-grade finely dispersed ores, the development of fine/ultrafine milling processes has attracted particular attention in recent decades. The main concern in ore beneficiation and processing plants is producing the desired product size with the lowest possible energy consumption. It has been estimated that grinding consumes up to 4% of global electrical energy and accounts for more than 50% of the total energy used in mining operations. In addition, more than 90% of the total energy supplied in beneficiation plants is dissipated as heat, kinetic energy, noise, and inefficient breakage of ores/raw material. Therefore, any research effort that has the potential to reduce energy consumption while maximizing grinding efficiency is of great importance. This Special Issue welcomes papers that highlight innovations and future trends in modeling grinding and technological ways to improve the grinding efficiency in ore/raw material beneficiation. Emphasis is placed on mathematical modeling to accurately describe the particle size distribution of grinding products, modeling for the estimation of the energy requirements for size reduction, the simulation and optimization of the grinding process, the investigation of parameters affecting grinding efficiency, the development and design of innovative and efficient grinding equipment, and all issues that contribute to the improvement of process and energy efficiency and reduce the environmental footprint of ore beneficiation and processing plants.

Dr. Evangelos Petrakis
Prof. Dr. Konstantinos Komnitsas
Guest Editors

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Keywords

  • grinding
  • ore/material breakage
  • energy efficiency
  • energy input
  • grinding modeling
  • simulation/optimization of grinding process
  • product size distribution
  • mineral processing
  • ore/material beneficiation

Published Papers (5 papers)

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Research

12 pages, 1935 KiB  
Article
Research on the Relationship between Multi-Component Complex Ore and Its Component Minerals’ Grinding Characteristics under Abrasion Force
by Jinlin Yang, Pengyan Zhu, Hengjun Li, Zongyu Li, Xingnan Huo and Shaojian Ma
Minerals 2023, 13(1), 6; https://doi.org/10.3390/min13010006 - 21 Dec 2022
Cited by 4 | Viewed by 1322
Abstract
The relationship between the grinding characteristics of polymetallic complex ore and its component minerals, pyrrhotite, sphalerite, and quartz, under the action of abrasion was studied, based on batch grinding experiments and theoretical analysis methods of selective grinding. The results show that when the [...] Read more.
The relationship between the grinding characteristics of polymetallic complex ore and its component minerals, pyrrhotite, sphalerite, and quartz, under the action of abrasion was studied, based on batch grinding experiments and theoretical analysis methods of selective grinding. The results show that when the polymetallic complex ore was subjected to the action of abrasion, the crushing effect of ore was enhanced by the existence of sphalerite, that is, sphalerite plays a positive role in the crushing effect of ore. The crushing effect of ore was reduced by the existence of pyrrhotite and quartz, that is, pyrrhotite and quartz plays a negative role in the crushing effect of ore. In addition, the sphalerite had a more prominent effect on the grinding characteristics of the ore. The grinding speed of ore and its component minerals decreased exponentially with the grinding time, and the instantaneous grinding speed of 0 min was negatively correlated with the feed sizes. The rapidly decreasing trend of the grinding speed reached the threshold when the grinding time reached 4 min. The results can provide some theoretical guidance for the study of grinding characteristics of multi-component complex ores in subsequent grinding process. Full article
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17 pages, 3101 KiB  
Article
Research on Grinding Characteristics and Comparison of Particle-Size-Composition Prediction of Rich and Poor Ores
by Shaojian Ma, Hengjun Li, Zhichao Shuai, Jinlin Yang, Wenzhe Xu and Xingjian Deng
Minerals 2022, 12(11), 1354; https://doi.org/10.3390/min12111354 - 26 Oct 2022
Cited by 2 | Viewed by 1415
Abstract
The particle size composition of grinding products will significantly affect the technical and economic indexes of subsequent separation operations. The polymetallic complex ores from Tongkeng and Gaofeng are selected as the research object in this paper. Through the JK drop-weight test, the batch [...] Read more.
The particle size composition of grinding products will significantly affect the technical and economic indexes of subsequent separation operations. The polymetallic complex ores from Tongkeng and Gaofeng are selected as the research object in this paper. Through the JK drop-weight test, the batch grinding test, and the population-balance kinetic model of grinding with the Simulink platform, the grinding characteristics of the two types of ores and the particle-size-composition prediction methods of grinding products are studied. The results show that the impact-crushing capacity of Tongkeng ore and Gaofeng ore are “medium” grade and “soft” grade, respectively. The crushing resistance of Tongkeng ore increases with the decrease in particle size, and the crushing effect is more easily affected by particle size than that of Gaofeng ore. For the same ore, the accuracy order of the three methods is: PSO–BP method > JK drop-weight method > BIII method. For the same method, only the BIII method has higher accuracy in predicting Gaofeng ore than Tongkeng ore, and other methods have better accuracy in predicting Tongkeng ore than Gaofeng ore. The prediction accuracy of the BIII method is inferior to that of the JK drop-weight method and the PSO–BP method and is easily affected by the difference in mineral properties. The PSO–BP method has a high prediction accuracy and fast model operation speed, but the accuracy and speed of the iterative results are easily affected by parameters such as algorithm program weight and threshold. The parameter-solving process of each prediction method is based on different simplifications and assumptions. Therefore, appropriate hypothetical theoretical models should be selected according to different ore properties for practical application. Full article
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24 pages, 3687 KiB  
Article
Research on Grinding Law and Grinding Parameters Optimization of Polymetallic Complex Ores
by Shaojian Ma, Hengjun Li, Zhichao Shuai, Jinlin Yang, Xingjian Deng and Wenzhe Xu
Minerals 2022, 12(10), 1283; https://doi.org/10.3390/min12101283 - 13 Oct 2022
Cited by 4 | Viewed by 1582
Abstract
Grinding plays an important role in mining, construction, metallurgy, chemical, coal and other basic industries. In terms of beneficiation, grinding is the most energy consuming operation. So, reasonable grinding conditions according to the properties of ores is the key to obtain good grinding [...] Read more.
Grinding plays an important role in mining, construction, metallurgy, chemical, coal and other basic industries. In terms of beneficiation, grinding is the most energy consuming operation. So, reasonable grinding conditions according to the properties of ores is the key to obtain good grinding results and reduce energy consumption and resource waste. In this paper, Tongkeng and Gaofeng polymetallic complex ores are taken as research objects, and the effects of grinding law based on single factor condition test and the grinding parameters optimization based on response surface method were studied for two kinds of ores. The results show that grinding time is a significant factor affecting the particle size composition. The suitable grinding concentration of Tongkeng ore and Gaofeng ore is 70% and 75%, respectively. The effect of mill filling ratio on Gaofeng ore is not obvious. The rotational rate has little effect on the grinding technical efficiency. The regression model equations obtained by response surface method are extremely significant, and the relative errors of prediction are all within 1%, indicating high reliability of fitting equations. The order of influencing factors of the two ores is as follows: grinding time > filling ratio > grinding concentration. For Tongkeng ore, the optimized grinding conditions are grinding time 5.4 min, grinding concentration 67% and filling ratio 35%. For Gaofeng ore, the optimized grinding conditions are grinding time 3.8 min, grinding concentration 73% and filling ratio 34%. Full article
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31 pages, 9265 KiB  
Article
Integration of Lineal Geostatistical Analysis and Computational Intelligence to Evaluate the Batch Grinding Kinetics
by Freddy A. Lucay, José Delgado and Felipe D. Sepúlveda
Minerals 2022, 12(7), 823; https://doi.org/10.3390/min12070823 - 28 Jun 2022
Viewed by 1331
Abstract
The kinetic characterization of the grinding process has always faced a special challenge due to the constant fluctuations of its parameters. The weight percentage of each size (WPES) should be mentioned. There are particular considerations for WPESs, because their tendencies are not monotonic. [...] Read more.
The kinetic characterization of the grinding process has always faced a special challenge due to the constant fluctuations of its parameters. The weight percentage of each size (WPES) should be mentioned. There are particular considerations for WPESs, because their tendencies are not monotonic. The objective of this work is to provide a methodology and model that will allow us to better understand the kinetics of grinding through the analysis of the Response Surface (RS), using geostatistical (data reconstruction) and computational intelligence (meta-model) techniques. Six experimental cases were studied and trends were evaluated/adjusted with multiple parameters, including an identity plot adjusted to 0.75–0.90, a standardized error histogram with a mean of −0.01 to −0.05 and a standard deviation of 0.63–1.2, a standardized error based on an estimated value of −0.09 to −0.02, a meta-model adjusted to between 92 and 99%, and finally, using the coefficient of variation, which classifies the information (stable/unstable). In conclusion, it was feasible to obtain the results of the WPES from RS, and it was possible to visualize the areas of greatest fluctuation, trend changes, error adjustments, and data scarcity without the need for specific experimental techniques, a coefficient analysis of the fracturing or the use of differential equation systems. Full article
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12 pages, 1431 KiB  
Article
Pre-Processing to Increase the Capacity of SAG Mill Circuits—Case Study
by Homero Delboni, Jr., Evandro Costa e Silva, Vladmir Kronemberger Alves and Ana Carolina Chieregati
Minerals 2022, 12(6), 727; https://doi.org/10.3390/min12060727 - 6 Jun 2022
Cited by 1 | Viewed by 4643
Abstract
This paper describes the adopted approach for increasing the capacity of an existing industrial grinding circuit by adapting the respective configuration to process the ore from a new mine. Accordingly, due to Sossego mine exhaustion, Vale S. A. decided to use the existing [...] Read more.
This paper describes the adopted approach for increasing the capacity of an existing industrial grinding circuit by adapting the respective configuration to process the ore from a new mine. Accordingly, due to Sossego mine exhaustion, Vale S. A. decided to use the existing industrial facilities and infrastructure for processing the Cristalino ore deposit located in Para state, within the Brazilian Amazon. Considering the higher hardness of Cristalino ore compared to Sossego ore, a reduction in capacity in the existing SAG grinding circuit was anticipated. A comprehensive grinding pilot plant campaign was conducted with a characterization program including 98 Cristalino ore samples, as described throughout this paper. Sossego grinding circuit was also surveyed for mathematical modeling and simulations to assess such an estimative further. The mathematical model calibration for setting different circuit configurations and operating conditions to enhance the circuit’s capacity was based on the combination of pilot plant results and ore characterization. Simulations indicated that a capacity increase of 12% would be achieved in the existing grinding circuit by further crushing 35% of SAG mill fresh feed. Such figures would represent yearly additions of 8.3 kt in copper and 250 kg in gold productions. Full article
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