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By Xiaodong Yu, Jinxia Zhang, Fusheng Niu, Hongmei Zhang

The three-dimensional (3D) fractal dimension is an important parameter to analyze the 3D structure and flocculation effect of the hematite flocs. In this work, the 3D fractal dimension of hematite flocs was predicted by establishing the particle swarm optimization (PSO) algorithm optimized with the back propagation (BP) neural network (PSO-BP). The proposed model considers four factors, namely, the flocculant quantity, flocculation time, stirring speed, and temperature, as the input parameters. We normalize the input data during the preprocessing stage. The BP neural network was optimized by using the PSO algorithm for realizing the 3D fractal dimension. The prediction accuracy and effectiveness of the model were evaluated. The experimental results showed that the predictions performed by the proposed PSO-BP neural network were better than that of BP neural network. In addition, the root mean square error (RMSE), mean squared relative error (MSRE), mean absolute error (MAE), and mean absolute relative error (MARE) of the proposed model are lower, compared with the errors of the BP network. Similarly, the measurement coefficient R2 of the proposed model is higher, compared with the BP network. The maximum absolute error of the model is 0.0772, the maximum relative error is 0.02405, and the regression coefficient r is 0.98592. These results showed that the proposed model has a good performance and high prediction accuracy. When verifying the practicability and the effectiveness of the proposed PSO-BP model, the prediction results of 10 groups of hematite flocculation experimental data under different conditions showed that the prediction value of the proposed PSO-BP model was closer to the ground truth as compared to the BP model. Therefore, the proposed model is suitable for predicting the 3D fractal dimension of hematite flocculation.

Oct 3, 2022

By Sufi Md Gulzar, L B. Roy

Rock engineering tasks like tunnelling, dam and building construction, and rock slope stability rely heavily on properly estimating the rock’s uniaxial compressive strength (UCS), a crucial rock geomechanical characteristic. As high-quality specimen are not always possible, scientists often estimate UCS indirectly. The primary objective of this paper is to assess the efficacy of long short-term memory (LSTM), K-nearest neighbour (KNN), a combination of particle swarm optimisation (PSO) with an artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) to estimate the UCS of sandstones from Jharia, Dhanbad, India. Point load index (PLI), porosity (n), P-wave velocity (Vp), density (ρ), and moisture content (%) are the parameters used for the present study. Finally, a comparison was made between the various prediction algorithms outputs. The findings of the study validated the effectiveness of computational intelligence methods in forecasting UCS compared to other models used in this paper. The KNN achieves overall the best results, with an R2 of 0.95 for training, 0.94 for testing, and an RMSE of 0.03 for training and 0.05 for testing.

Nov 23, 2023

By Ashish Kumar Vishwakarma, Vivek Kumar Himanshu, Kaushik Dey

The accurate prediction of blast-induced ground vibration due to underground ring blasting is a prominent need for ensuring the safety of structures. Different site-specific empirical equations are available for the prediction of ground vibration. These empirical equations are best suited when the monitoring and blasting locations are present in the same medium. The change in the medium alters the behavior of wave propagation. Hence, existing empirical equations have limitations in peak particle velocity (PPV) prediction when the blasting location is an underground hard rock mine and the monitoring location is ground surface. This is because the underground metal mine comprises different levels having void in the form of excavated stope or paste-filled stope. It is very difficult to predict the magnitude of PPV on the surface in such instances. Therefore, this study has been carried out to predict the PPV at surface due to underground blasting. In this paper, PPV data was recorded at surface for 207-ring blasts. Furthermore, the PPV has also been measured at different underground locations for 47-ring blasts. Different empirical equations along with k-nearest neighbor (KNN) and random forest (RF) model of machine learning technique were developed for the prediction of PPV. Most of the empirical models have higher accuracy in the prediction of PPV at an underground location. This shows that scaled distance-based empirical predictors are best suited when the monitoring and blasting media are the same. However, the empirical models do not predict PPV accurately when the monitoring location is ground surface and the blast is conducted underground. The machine learning models are better suited for PPV prediction in such cases. Based on the analysis performed for the case study site, RF model predicts PPV at surface with the highest accuracy. The coefficient of determination and root mean square error for RF model used for predicting PPV at ground surface are 0.94 and 0.438 mm/s respectively. The RF-based model is also the best suited among all the models for predicting PPV at underground locations as well.

Apr 20, 2024

By Pratoomkhuan N. Lertsgoon

A large underground cavern with dimensions of 25m × 175m × 49m (W×L×H) was excavated in sandstone and siltstone to house 4 units of hydropower generator and was completed in 2000. In feasibility study stage, the property of the siltstone which governs the ceiling of the cavern was questionable due to slaking phenomenon. Parameters on rock properties for design were back calculated from actual ground response measured from a trial excavation. For safety of construction, comparison between prediction and actual ground responses during excavation had proceeded. The prediction was provided by means of PHASES and PHASE2 software and the actual rock response was detected by the provided monitoring system.

Jan 1, 2003

By D. Dunbar

The flooding of open pits is now receiving considerable attention from the mining industry as an option that may minimize environmental impacts, particularly when anoxia in pit-lake deep waters can effectively eliminate oxidation of pit-wall sulfides. This paper describes a state-of-the-art, coupled physical-geochemical pit-lake model. The model is used to verify that a controlled, two-stage infilling of the open pit at the Kori Kollo gold mine, southeast of La Paz, Bolivia, would result in a cost-effective, environmentally responsible closure strategy. By filling the pit initially with highly saline surface waters and naturally saline deep groundwater and then capping with fresh river water, a very stable and strongly stratified pit lake will be developed. In addition, the stratification will result in the isolation of metal-rich saline bottom waters from surface waters of good quality. Results of this model provide defensible predictions of the physical stability and evolution of water quality in the Kori Kollo pit lake over time. The model results indicate that anoxic conditions will develop below the fresh-saline water boundary within one to two years, followed by the rapid onset of sulfate-reducing conditions in the bottom waters. Hydrogen sulfide produced by sulfate reduction will readily react with dissolved metals to form highly insoluble metal sulfides. The process results in the gradual removal of metals from the water column and the concomitant improvement of water quality over time. A notable benefit of this strategy is that it can be fully integrated with other mine site closure options as well as future environmental-management strategies. The proposed plan allows for the safe isolation of saline waters, the potential for passive treatment in anoxic bottom waters of ARD seepage from other mine site operations, should they arise, and a repository for future reactive wastes that could be effectively isolated in a physically and chemically stable environment.

Jan 1, 2003

By D. Dunbar

Flooding of open pits now receives considerable attention from the mining industry as an option that may minimize environmental impacts, particularly when anoxia in pit lake deep waters can effectively eliminate oxidation of pit-wall sulphides. A state-of-the-art, coupled physical-geochemical pit lake model is used to verify that a cost-effective, environmentally responsible closure strategy for the open pit at the Kori Kollo gold mine, southeast of La Paz, Bolivia is to adopt a controlled, two-stage infilling of the open pit upon cessation of operations. By filling the pit initially with highly saline waters from evaporation/infiltration basins and naturally saline deep groundwater, followed by capping with fresh river water, a very stable and strongly stratified pit lake will be developed. In addition, the stratification will result in the isolation of metal-rich saline bottom waters from surface waters of good quality. Results of this model provide defensible predictions of the physical stability and evolution of water quality in the Kori Kollo pit lake over time. The model results indicate that anoxic conditions will develop below the fresh-saline water boundary within 1 to 2 years, followed by the rapid onset of sulphate reducing conditions in the bottom waters. Hydrogen sulphide produced by sulphate reduction will readily react with dissolved metals to form highly insoluble metal sulphides. The process results in the gradual removal of metals from the water column and the concomitant improvement of water quality over time. A notable benefit of this strategy is that it can be fully integrated with other mine site closure options as well as future environmental management strategies. The proposed plan allows for: 1) safe storage of saline evaporation basin waters; 2) the potential for passive treatment in anoxic bottom waters of ARD seepages from other mine site operations should they arise; and 3) a repository for future reactive wastes that could be effectively isolated in a physically and chemically stable environment.

Jan 1, 2001

By Frédéric Flament, Daniel Hodouin, Claude Bazin

A control strategy is proposed to meet the following specifications of flotation control: minimize the variations of concentrate and tails grades and recovery while limiting the amplitude of variations of the manipulated variables. The strategy consists of determining future control actions which optimize a performance criterion over a limited time horizon. The desired dynamic behaviour of the controlled flotation plant is specified using reference models. The strategy is tested on a 2-computer plant simulator working in an environment which emulates the industrial conditions.

Jan 1, 1993

By Guido Deissnann, Jennifer L. Kirkaldy, Stephan Kistinger, Carol M. Pettit

Contaminated mine drainage presents a potential hazard for aquatic ecosystems and groundwater resources. Reliable predictions of long-term developments in seepage quality are necessary to select reasonable decommissioning options and remediation measures for waste-rock heaps during mine closure and/or mining site rehabilitation to minimize future risks and environmental hazards. Extensive geochemical modeling work was used to assess the consequences of various remediation options for waste rock heaps at a former uranium mine in Eastern Germany. The predicted contaminant discharges are used for an assessment of long- term benefits of decommissioning alternatives to derive conclusions for sustainable remediation measures using risk-based cost/benefit analyses.

Jan 1, 2000

By Yucheng Li, De Huang, Yonghong Liu

Mine frictional resistance is one of the essential parameters of mine ventilation systems, and it is of considerable significance for the prevention and control of mine risks and accident hazards. Frictional resistance requires a lot of resources and time and has errors. To reduce the errors of frictional resistance, a regression model of frictional resistance is proposed based on the correlation analysis of the affecting factors. Through the comparative test analysis of seven regression methods, it is found that the classification and regression tree method for solving the proposed regression model has better performance than other methods. The least square error criterion is used to calculate and rank the importance of the factors affecting frictional resistance. The results show that the cross-sectional area of the tunnel, the support method, and the presence or absence of devices or pedestrian ladders have the most considerable influence on the prediction accuracy of frictional resistance. The support methods and cross-sectional areas are essential input variables. Through the combination test analysis of the influencing factors, the results show that the regression model does not have predictive ability when the number of input variables is less than 3 and the best predictive performance cannot be obtained using all the influencing factors. The best prediction model of resistance is to combine the shape of the tunnel, the support method, the presence or absence of devices or pedestrian ladders, and the cross-sectional area. The method proposed in this paper does not require a lot of resources and time investment, and the frictional resistance error is small. At the same time, it solves the problem of resistance prediction with incomplete data of influencing factors and provides a compelling new method for obtaining frictional resistance parameters.

Jan 28, 2022

By Greg Partington, Darryl Thorburn, Charlene Wildman, Elisa Puccioni, Connie Payne, Campbell McKenzie

"Mineral prospectivity modelling of polymetallic nodule deposits has been completed over the Cook Islands Exclusive Economic Zone (CIEEZ) using the GIS based Weights of Evidence modelling technique. Polymetallic nodules, also known as manganese nodules, have been explored as a possible resource for a number of metals including cobalt since the early 1970s. Recent data on the nodule composition and abundance in the CIEEZ has led to a renewed interest in the prospectivity for manganese nodules in the region. The predictive modelling has used the most recently accepted mineral model for polymetallic deep-sea nodule deposition to identify factors that are most likely to map the presence of this type of mineralisation in the CIEEZ.Manganese nodules form on the deep seafloor as concretions formed by concentric layering of iron and manganese hydroxides around a core and they grow at a very slow rate, on the order of millimeters per million years. The available data for the CIEEZ indicates a greater abundance in the area of nodules formed by hydrogenetic processes, which are the result of slow precipitation of metallic components from seawater. The environment in which the nodules are most abundant is at depths between 4,000 m and 6,000 m in areas of low sedimentation rate. Hydrogenous nodules commonly grow on siliceous and pelagic clay sediment, they are less common on other types of sediment."

Sep 1, 2014

By C. Orf. Chukabarah

Erratic behavior in convergency during iterative numerical-method evaluation of mine ventilation fan characteristic curves is one of the common problems encountered in mine ventilation network analysis. Five different sets of mine fan data points, that had resulted in unsatisfactory fan characteristic curves, were re-analyzed in the present study, using an embedded mine network optimization computer program. Current results revealed that all five fan data sets not only can be satisfactorily fitted as Yang (1992) did with MFIRE subprogram, but can further be optimized with unique solutions as implemented in the present study. It was concluded, inter alia, that the improved MFIRE-based mine fan curve-fitting computer subprogram (SPLINE) produces satisfactorily similar fan curves as SPSS-based curve-fitting algorithms, including when the latter method uses either standardized or unstandardized fan curve data sets.

Jan 1, 1993

By M. Sadegh Safarzadeh, Stanley M. Howard

The two-dimensional predominance area (Kellogg) diagram (PAD) surfaces bounding the three-dimensional Cu-As-S-O system were constructed at 900 K. The computations employed gases As4O6(g), O2(g), and SO2(g) as the independent coordinate species to generate diagrams of As4O6(g) − O2(g),O2(g) − SO2(g), and As4O6(g) − SO2(g), while the third gas (As4O6, O2, or SO2) was fixed. The results indicate that there is no shared boundary between enargite (Cu3AsS4) and copper sulfate (CuSO4); however, at PO2 < 10−6 atm, PAs4O6 < 10−10 atm, and PSO2 > 10−4 atm, CuSO4 is the stable phase at 900 K. The chemical driving force for oxidation of intermediate phases between enargite and copper sulfate is substantial except for basic sulfate (CuO · CuSO4).

By Bezalel C. Haimson

Long before excavation begins, the in situ stresses in the horizon of planned underground chambers can be measured by employing the hydrofracturing technique in existing exploratory holes. Such measurements produce the stress magnitudes and directions required for the rational design of rock structures. Two recent case histories are cited in which preexcavation stress measurements for the design of underground powerhouses proved very beneficial in the orientation of the chambers and the estimation of the stability and required support. A third stress measurement case is related to the preexcavation design of tunnels that will house doughnut-shaped superconductive magnets for the storage of electric energy. In all cases, expensive later modifications were probably prevented by measuring stresses early in the design stage.

Jan 1, 1976

By Fangyu Liu

In the grand tapestry of scientific inquiry, there are individuals whose contributions resonate far beyond the confines of laboratories and lecture halls. It is with profound admiration and respect that we present this special collection of Mining, Metallurgy & Exploration, dedicated to celebrating the remarkable career of Dr. Patrick Taylor. Dr. Taylor, recently retired from the Colorado School of Mines as the Emeritus Ansell Distinguished Professor of Chemical Engineering, possesses over 45 years of expertise in mineral processing and extractive metallurgy. His remarkable journey has seen him traversing the globe, from Canada to Egypt, contributing to pyrometallurgy, hydrometallurgy, and mineral processing. Dr. Taylor’s portfolio encompasses lab work, pilot-plant projects, research, and process development across various metals, with an impressive array of authored papers, presentations, and nine patents to his name. A soughtafter consultant for over 20 companies and an esteemed expert witness, Dr. Taylor also led the Kroll Institute for Extractive Metallurgy at Colorado School of Mines. Under his guidance, more than 100 graduate students and post-docs have undertaken transformative research, while Dr. Taylor’s 45-year tenure as a university lecturer and the creation of 10 industryfocused short courses underscore his dedication to knowledge dissemination. His contributions extend to crafting professional engineering exam questions for a quarter-century and active participation in esteemed organizations like SME, TMS, ASM, and MMSA.

Sep 16, 2023

By Barbara J. Arnold

Combat Infantrymen’s Badge and Bronze Star Medal. Following his discharge from the Army, he re-entered SDSM&T in 1946 and earned a B.S. degree in Metallurgical Engineering in 1948. He then received an M.S. from Montana Tech (MT), worked several years in industry and then as an Assistant Professor at the University of Washington (Seattle). He joined his Montana Tech colleague, Douglas W. Fuerstenau, at The Massachusetts Institute of Technology (MIT), receiving his doctorate in 1957. While at MIT, he married Clare M. Donaghue of Dorchester, Massachusetts, in 1955

Jan 3, 2022

By Jürgen Brune, Purushotham Tukkaraja

This editorial introduces a special focus issue on mine ventilation innovations. It highlights key areas such as ventilation on demand, automation, thermal management, atmospheric monitoring systems, and prevention of mine fires and explosions. The issue aims to address the critical role of mine ventilation in maintaining the health and safety of miners.

Mar 21, 2022

By Jim Gebhardt

Douglas W. Fuerstenau (DWF) grew up on a farm and in several small communities in rural South Dakota during the depression years, where he learned the value of hard work. Working hard can produce results but being clever and hardworking will give you a bright future. In his later school years, Fuerstenau’s family moved to Rapid City where his intellectual curiosity and capacity helped him graduate with a B.S. in Metallurgical Engineering from the South Dakota School of Mines and Technology in 1949. His technical interests led to graduate studies and completion of a master’s degree from the Montana School of Mines in 1950 and Sc.D. degree from the Massachusetts Institute of Technology (MIT) in 1953.

By Jürgen F. Brune

The Fourth Industrial Revolution, that of digital technologies and their application, is rapidly impacting the mining industry, as it is manufacturing, transportation, agriculture, trade, and most other industries. Mining is about 40,000 years old and has its origins in Africa. Since its earliest days, it has experienced four distinct “revolutions” that each resulted in significant improvements in production, productivity, and safety and health: The First Revolution in the fifteenth through eighteenth centuries brought technologies that improved miners’ lives and health, including pumps, forced and mechanical ventilation with wind catchers and bellows, the wire rope and black powder, to name a few. Many simple, muscle- or water-driven machines have been pictured and described in great detail by Agricola who wrote De Re Metallica in 1556. Agricola was familiar with, and concerned about, accidents where miners fell off rotten, wooden ladders, acrid smoke, and dust that caused respiratory illnesses and diseases. He also knew the dangers of fatigue and recommended that miners should sing aloud to prevent them from falling asleep.

By J. F. T. Agapito, R. R. Goodrich

Yield pillars have been used for many years to help reduce stresses near mine openings and improve roof and floor stability. A yield pillar is often defined as a pillar that fails but retains residual strength. Stress transfer occurs through the roof and floor after the peak strength of the pillar is reached. High stresses are transferred from around the openings onto abutments that can be barrier pillars or unmined ground. This mechanism, often referred to as pressure arching, is possible as long as the width of yield pillar mining (panel width) is less than the critical width above which stresses cannot be carried by the overburden. Significant stress transfer also can occur due to small amounts of pillar and/or floor yielding before the peak strength is reached. This is accomplished in a quasi-elastic manner with little or no visible roof and pillar fracturing or floor heave. Long-term stability may be achieved when stresses and mechanical properties are favorable to prefailure yielding. This paper gives practical examples where improvements in stability and resource recovery were achieved with this mechanism. Yielding was assessed by comparing measured and calculated vertical pillar stresses. Results indicated that calculated stresses in the pillars were 25% to 40% higher than the measured stresses, demonstrating significant arching load transfer to the abutments. Prefailure yielding is probably often present but unintentional in both development and production areas. Better recognition and use of this mechanism should lead to design improvements, as mines become deeper.

Jan 1, 2003

By Thor Skjeggedal

The Norwegian contracting firm A/S Høyer-Ellefsen has for the last 2.5 years carried out substantial pregrouting in a 7600m long tunnel just outside the city of Oslo. This has been done to avoid groundwater lowering and consequent damage to surface structures. A WIRTH TBM is used in combination with a 2 boom Atlas Copco hydraulic jumbo for the drilling of groutholes in front of the machine. The detailed procedure for the drilling and grouting will be discussed, and the results obtained will be presented.

Jan 1, 1981