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This book has been the definitive reference for the mineral processing industry for over thirty years. This industry standard reference provides practicing engineers and students of mineral processing, metallurgy, and mining with practical information on all the common techniques used in modern processing installations. Each chapter is dedicated to a major processing procedure-from underlying principles and technologies to the latest developments in strategies and equipment for processing increasingly complex refractory ores. The 8th Edition of this classic reference enhances coverage of practical applications via the inclusion of new material focused on meeting the pressing demand for ever greater operational efficiency, while addressing the pivotal challenges of waste disposal and environmental remediation. Advances in automated mineralogy and analysis and high-pressure grinding rolls are given dedicated coverage. The new edition also contains more detailed discussions of comminution efficiency, classification, modeling, flocculation, reagents, liquid-solid separations, and beneficiation of phosphate, and industrial materials.

Mineral Processing Design and Operations is expected to be of use to the design engineers engaged in the design and operation of mineral processing plants and including those process engineers who are engaged in flow-sheets development.Provides an orthodox statistical approach that helps in the understanding of the designing of unit processes. The subject of mineral processing has been treated on the basis of unit processes that are subsequently developed and integrated to form a complete strategy for mineral beneficiation. Unit processes of crushing, grinding, solid-liquid separation, flotation are therefore described in some detail so that a student at graduate level and operators at plants will find this book useful. Mineral Processing Design and Operations describes the strategy of mathematical modeling as a tool for more effective controlling of operations, looking at both steady state and dynamic state models. * Containing 18 chapters that have several worked out examples to clarify process operations* Filling a gap in the market by providing up-to-date research on mineral processing* Describes alternative approaches to design calculation, using example calculations and problem exercises

Coal beneficiation processes are often based on gravitational enrichment techniques. Therefore, various types of jigs are often used in this area. A number of factors determine the quality of the final product. Therefore, proper and systematic monitoring of such a process is necessary. The present work examined the effect of the hutch water amount and the amount of processed coal (system capacity) on the yield and ash grade in individual density–size fractions. A statistical method in the form of the Kruskal–Wallis test and the Friedman test was used to evaluate the process. These tests were proposed as universal and reliable alternatives to classical analysis of variance (ANOVA) analysis. The performed analysis allowed for the determination of what process conditions should be selected in order to obtain certain effects. Therefore, it allowed us to apply certain combinations of hutch water amount, system capacity and particle characteristics to maximize the expected effects. The application of statistical analysis methods in the form of Kruskal–Wallis and Friedman tests to evaluate process efficiency creates new possibilities to monitor and optimize the jigging process in both context of amount and quality of final product and is very important not only for mining enterprise but also from an environmental point of view.

Providing practicing engineers and students of mineral processing, metallurgy, and mining with practical information on all the common techniques used in modern processing installations, this industry standard introduces the latest technologies and incorporates environmental issues to place the subject of mineral processing in a contemporary context, addressing concerns of sustainability and cost effectiveness. --

Sustainable potable groundwater supply is crucial for human development and the preservation of natural habitats. The largest endorheic inland lake in Kazakhstan, Balkhash Lake, is the main water resource for the arid southeastern part of the country. Several ore enrichment plants that are located along its shore have heavy metal pollution potential. The study area is located around a plant that has an evident anthropogenic impact on the Balkhash Lake aquatic ecological system, with ten known heavy metal toxic hotspots endangering fragile habitats, including some indigenous human communities. This study assessed the risk of heavy metal contamination from tailing dump operations, storage ponds, and related facilities and suggested management practices for preventing this risk. The coastal zone risk assessment analysis used an innovative integrated groundwater numerical flow and transport model that predicted the spread of groundwater contamination from tailing dump operations under several mitigation strategies. Heavy metal pollution prevention models included a no-action scenario, a filtration barrier construction scenario, and two scenarios involving the drilling of drainage wells between the pollution sources and the lake. The scenario assessment indicates that drilling ten drainage wells down to the bedrock between the existing drainage channel and the lake is the optimal engineering solution for confining pollution. Under these conditions, pollution from tailings will not reach Lake Balkhash during the forecast period. The methods and tools used in this study to enable mining activity without environmental implications for the region can be applied to sites with similar anthropogenic influences worldwide.

The Tailings Management Handbook is important and timely because there is no other comprehensive resource rooted in the new fundamentals and global principles for tailings management. Tailings management requires interdisciplinary and cross-functional understanding and support, which is apparent throughout this handbook. Dive into the wealth of information contributed by more than 100 world-renowned experts, beautifully crafted into a full-color handbook that focuses on the basics, life-cycle planning, site and tailings characterization, TSF design and construction, as well as systems and operations of TSFs. The inclusion of 42 case studies is an added plus with real-world successes and lessons learned.

A serious problem faced by the metal mineral mining industry is the challenge to the sustainable development of resource mining due to the continuous decline of ore geological grade. In the case of producing concentrates of the same quality, compared with using only high-grade raw ore, ore blending is a way to slow down the decline of ore geological grade by combining high- and low-grade raw ore. There are many ore blending models considering cost minimization or profit maximization as the target value, ignoring the fact that ore blending is intended to obtain a homogenized product. Moreover, the ore blending model cannot be solved by traditional operational research methods when blended grade stability of multiple elements is considered in the ore blending program. In this paper, a multi-objective ore blending optimization model is constructed for the comprehensive utilization of associated resources in ores. It minimizes the deviation of the grade of each metallic element in the blended associated ore from the beneficiation grade and the percentage of different types of rocks at the unloading point. To solve this multi-objective optimization model, an intelligent optimization method is proposed that is an improved multi-objective optimization algorithm based on the Non-dominated Sorting Genetic Algorithm III (NSGA-III). The case study shows that the proposed model and algorithm can effectively solve the mixing problem of polymetallic ores and obtain a satisfactory ore blending solution.

Reverse flotation is a commonly used method for separating carbonate minerals from apatite, but its application to phosphate beneficiation coarse rejects, which are low in P2O5, is often costly due to the high collector dosages used. This study aimed to explore alternative techniques for preconcentration before flotation to improve recovery rates and reduce costs. Our investigation focused on dense medium separation and acid leaching. Dense medium separation, conducted at a cut-off density of 2.76, yielded a preconcentrate with 27% P2O5 and a recovery rate of 90%. The feed material had an initial P2O5 content of 20.52% and a particle size range of +40 µm to −4 mm. In contrast, acid leaching, employing an 8% acetic acid solution over 35 min, yielded a concentrate with 29.11% P2O5, an LOI of 8.99%, and a recovery rate of 100% from an ore fraction [400–200 µm] with an initial P2O5 content of 22.82% and an LOI of 15.78%. Furthermore, integrating flotation and leaching resulted in a concentrate with 32.27% P2O5 and a recovery rate of 98.38%. These findings suggest that combining acid leaching with flotation can enhance P2O5 recovery and reduce processing costs for low-grade phosphate ores.

In order to solve the problems of a slow solving speed and easily falling into the local optimization of an ore-blending process model (of polymetallic multiobjective open-pit mines), an efficient ore-blending scheduling optimization method based on multiagent deep reinforcement learning is proposed. Firstly, according to the actual production situation of the mine, the optimal control model for ore blending was established with the goal of minimizing deviations in ore grade and lithology. Secondly, the open-pit ore-matching problem was transformed into a partially observable Markov decision process, and the ore supply strategy was continuously optimized according to the feedback of the environmental indicators to obtain the optimal decision-making sequence. Thirdly, a multiagent deep reinforcement learning algorithm was introduced, which was trained continuously and modeled the environment to obtain the optimal strategy. Finally, taking a large open-pit metal mine as an example, the trained multiagent depth reinforcement learning algorithm model was verified via experiments, with the optimal training model displayed on the graphical interface. The experimental results show that the ore-blending optimization model constructed is more in line with the actual production requirements of a mine. When compared with the traditional multiobjective optimization algorithm, the efficiency and accuracy of the solution have been greatly improved, and the calculation results can be obtained in real-time.

This book provides an orthodox statistical approach that helps in the understanding of the designing of unit processes. The subject of mineral processing has been treated on the basis of unit processes that are subsequently developed and integrated to form a complete strategy for mineral beneficiation. Unit processes of crushing, grinding, solid/liquid separation, and flotation are therefore described in some detail so that a student at graduate level and operators at plants will find this book useful. This book describes the strategy of mathematical modeling as a tool for more effective controlling of operations, looking at both steady state and dynamic state models.