Search Documents

By A. D. Davis, C. J. Webb, A. Heriba

Introduction The disposal of spent ore from cyanide heap-leach processing facilities is of concern to the mining industry, the regulatory agencies and the general public. The disposal of an additional several hundred million tons of spent ore from heap-leaching operations is planned in the western United States during the next decade, and this amount could increase if gold prices rise. In the past decade, more than fifteen million tons of spent ore have been disposed of in the Black Hills of South Dakota. The criterion for offloading spent ore was set by the South Dakota Department of Environment and Natural Resources at 0.5 ppm weak acid dissociable (WAD) cyanide. South Dakota's nitrate offloading limits vary for each mine, depending on ore type and other factors. Concentrations of nitrate in the leachate from spent ore depositories could be the result of conversion from other nitrogen-containing species. One likely source of nitrate is residual explosives from the blasting of ore. Previous work on the combustion products of nitrogen explosives has shown incomplete oxidation (Johansson and Persson, 1970). Another likely nitrate source is the degradation of cyanide to ammonia, followed by oxidation to nitrite and nitrate. A third possibility may be leaching of background nitrate from soil or rock. Objective The primary objective of this research was to investigate laboratory procedures for predicting nitrate concentrations in effluent after the disposal of spent ore at heap-leach gold processing operations. Laboratory tests were performed to define the concentrations of nitrate and nitrite in leachate as a function of time. Sources and species conversions were examined by investigating the nitrogen contributions from cyanide neutralization and from blasting with ammonium nitrate/fuel-oil (ANFO) explosives. Ore processing at cyanide heap-leach facilities Gold mines in the northern Black Hills of South Dakota normally use the following steps in their heap-leach cyanidation processing: Blasting. Surface gold mines in the Black Hills use ANFO explosives (approximately 95% ammonium nitrate and 5% fuel oil). Field evidence and studies show that explosives often fail to ignite or burn completely in shot holes. One reason is that ammonium nitrate absorbs moisture readily, which reduces blast efficiency. Ferguson and Leask (1988) cited a study conducted at the Fording coal mine in southeastern British Columbia. In that study, the total nitrogen released to surface and ground water was estimated to be about 6% of the slurry explosives. However, Ferguson and Leask (1988), in a later analysis of water quality near coal mines in the Kootenay coal fields, indicated that this is likely an overestimate of the nitrogen release. Mines that used ANFO explosives in dry conditions released 0.2% of the nitrogen from blasting. Cyanidation. At surface gold mines in the northern Black Hills, cyanide species from heap leaching can be classified into free cyanides and simple ions, weak complexes, moderately strong complexes and strong complexes (Scott and Ingles, 1981). Degradation of cyanide and disposal of spent ore. Methods of destroying cyanides include hydrogen peroxide oxidation, natural degradation and evaporation, water leaching and alkaline chlorination. Hydrogen peroxide is used to oxidize cyanides in the northern Black Hills mining area. The hydrogen peroxide oxidation reaction forms cyanate, which can hydrolyze to form ammonium and carbonate ions. After formation of ammonia or ammonium ion, further oxidation to nitrite (NO2-) and nitrate (NO3-) can occur. Spent tailings from gold processing in the Black Hills normally are disposed of in tailings facilities constructed in nearby drainages. Infiltrating rainwater with a typical pH of about 5.6 is an additional component introduced into the spent ore after disposal. Methods Field sample collection. Spent ore samples were collected from conveyor belts (or other convenient points) at heap-leach mines by personnel from the South Dakota Department of Environment and Natural Resources. The samples were placed in black plastic bags that were contained within 5-gal buckets and sealed to prevent exposure to ultraviolet light. The samples had a minimum head space to limit evaporation and contact

Jan 1, 1997

By A. D. Davis

The disposal of spent ore from cyanide heap-leach processing facilities is of concern to the mining industry, regulatory agencies, and the public. Disposal of several hundred million tons of additional spent ore is planned in the western United States during the next decade, with increased amounts likely if gold prices rise. In the past decade, more than fifteen million tons of spent ore have been disposed of in the Black Hills. South Dakota's off-loading criterion for cyanide has been set by the state's Department of Environment and Natural Resources at 0.5 parts per million (ppm) as weak acid dissociable (WAD) cyanide. Nitrate off-loading limits vary for each mine in the state, depending on ore type and other factors. Nitrate concentrations in leachate from spent ore depositories could be caused by conversion from other nitrogen-containing species. One likely source of nitrate is residual explosives from blasting of ore. Previous work on the combustion products of nitrogen explosives has shown incomplete 3xidation (Johansson and Persson, 1970). Another likely nitrate source is degradation of cyanide to ammonia, followed by oxidation to nitrite and nitrate.

Jan 1, 1994

By Yannis Faitakis, Brenda M. Wright, Gail Powley, Mark Hamblin, Randy B. Paine

A major problem in the ore extraction process is the high degree of variation in the mix of materials that make up the mined ore. The mix of materials makes it extremely difficult to characterize and predict the behavior of the ore when it is processed. The Quality Production Database (QPD) tool was successfully used in order to predict and transfer information regarding the quality characteristics of the ore being delivered to the extraction and hydrotransport unit operators. This paper describes the use of QPD in the prediction of various ore characteristics at the Syncrude Canada Ltd. processing facility.

Jan 1, 2000

By Qiong Wu, Li Guo, Qinghua Gu

BP neural network is a multilayer feedforward network trained by error back-propagation algorithm, which is one of the most widely used neural network models. However, BP neural network has exposed more and more shortcomings and deficiencies with the expansion of the application scope. In the prediction of ore quantity, BP neural network has the characteristics of slow convergence and easy to fall into local minimum point. In order to obtain the global optimal solution, and to improve the defects of BP neural network, this paper proposes combination optimization algorithm of genetic algorithm (GA) and BP neural network to improve the speed and accuracy of forecasting the main design flow chart and the analysis of the sort distinguish algorithm are offered, and then some problem in the design and debugging of the algorithm are discussed. On this basis, the GA-BP neural network model is constructed and applied to optimize the initial weights and threshold value of BP neural network. This model choices the floating point coding method to encode the connection weights and thresholds, and divides subjects into several populations. Through the introduction of selection, mutation, crossover, initial weight and other operators, making operational synergies between the various groups. This study selects 30 geological units, 8 quantitative variables (Pb, Zn, Cu, Mo, Si, Ni, Co, V) and 12 qualitative variables to carry out empirical analysis. Then the simulation of the algorithm is carried out in MATLAB and the parameters are analysed. By normalizing the input samples, 22 groups of observation data are used as the training data for prediction, and the latter 8 groups of observation data are used as the test data to be verified. The results show that when the ore quantity characteristics are not very significant, the model will produce prediction bias. But the improvement of the algorithm increases the efficiency of the function approach capacity of BP neural network and conquer the BP neural network system’s instability. It provides an auxiliary guide for ore prediction, which have higher reference value.

Jan 1, 2017

By Birger Schmidt

INTRODUCTION Urban tunneling in soil poses a unique set of problems to planners, designers and contractors. One of the important concerns is the impact of tunneling on the environment: not only the effects of noise, vibrations, construction traffic and surface traffic diversions, but also the effects of ground movements and dewatering on existing structures and facilities. Underpinning or other protection of structures often consume more than 10% of the total construction cost of an urban rapid transit tunnel, and another unknown percentage is expended on construction procedures designed to minimize these environmental effects. Ideally, many basic planning and design decisions should be based on reliable predictions of ground movements due to tunneling. Some of these decisions are: the choice of tunnel alignment and depth to minimize risks and effects of ground movements; selection of schemes to protect existing structures through soil improvement or underpinning, or outright acquisition and possible' demolition; relocation of utilities; selection of procedures for construction monitoring and project control; and the choice of construction and lining methods. To make rational decisions of this nature, the owner and his designers must perform analyses that will balance risks and costs of a variety of alternatives; but to make meaningful risk analyses, they must employ rational methods of predicting ground movements and their effects and must know the reliability of these predictions. Of course, the risk analyses also must consider politics, public relations, insurance and liabilities.

Jan 1, 1974

By M. Z. Rashad

The intersection of joint sets and excavation planes leads to removable blocks which can be expected to fall or slide. The amount and cost of supports required to stabilize these blocks of excavation are related to the number and dimensions of key blocks, the mechanical properties of joints and the active forces present. In this work, the application of the block theory in the study of the kinematics and stability of removable blocks is investigated considering any number of sliding faces for some Egyptian limestone quarries.

Jan 1, 1993

By R. H. Zeng

Many subsidence researchers in the U. S. have developed new empirical function methods to predict subsidence, or attempted to validate some empirical functions developed by foreign researchers for use in the U. S. An attempt is made in this paper to develop a new empirical function to predict a surface subsidence basin due to longwall mining. In the U. S., the emphasis of empirical methods for the subsidence prediction over longwall panels has been in large part on determining the profile functions for the major cross-sections of a subsidence basin. In this approach, the surface monuments are usually laid out along the major cross-sections and thus, the subsidence profiles developed are restricted for subsidence prediction along the major cross-sections. However in practice many monuments or surface structures for which subsidence prediction for damage evaluation is required, are not laid out along the major cross-section of the basin. In such cases, it is difficult to get either the empirical profile function for the cross-sections where these structures are located or to predict their subsidence based on the profile function developed for the major cross-sections. Therefore, there exists a strong need to develop a subsidence basin function with a reasonable degree of accuracy, which can be determined or confirmed by the data of scattered monuments on a surface basin. The same subsidence basin function can also be used for prediction of subsidence for any arbitrary points over a longwall panel. In 1982, He (1) proposed the clastic theory, for which he developed the basic differential equations describing the movement and deformation of overburden due to underground mining, and performed the selection of best solution for the equations. He found that the Weibull dietribution is the optimal solution. The Weibull distribution has three parameters that vary to fit the subsidence profile so well that the profile function derived from it provides a high degree of accuracy in subeidence prediction. However the results

Jan 1, 1986

By Manuel Gomez

This, report presents correlative data on ash and sulfur forms for Pittsburgh seam coal from Greene County, Pa. Prediction equations were developed for sulfur form distributions and washability characteristics. The equations developed were evaluated with an independent set of exploration core samples. It was demonstrated-that both sulfur distributions and washability characteristic's can be predicted from exploration core data ahead of mining. This information can improve the efficiency of selective mining techniques for the production of a uniform metallurgical coal product.

Jan 1, 1967

By W. L. Zhong

Probability function integration method is one of the influence function method. It is a widely accepted method in many mining districts in China and Poland mainly because its theory and formulae can well-represent the surface subsidence basins due to longwall mining of flat or near-flat seams. This paper introduces the basic theory of the probability function integration method and determines its 4 basic parameters by analyzing the measured subsidence profiles in eight longwall panels in Northern Appalachian Coal field. It also discusses the two methods for determining the 4 parameters. Finally the acquired parameters are used to predict the subsidence and deformation of the houses for damage assessment. Comparisons are made between the measured and the predicted subsidence. Probability Function Integration Method The probability function integration method for predicting surface movements and deformations is widely used in China and Poland. The governing equation of the method contains five parameters: subsidence factor, a, offset of inflection point, d, tangent of the major influence angle, tan fl, horizontal movement constant, b, and major dispersion angle e (e = 90. for flat seams). Its applicable range iis much larger including seams less than 30' from the horizontal, critical and noncritical mining and soft to hard overburden.

Jan 1, 1986

By K. Oraee

Rate of penetration of Tunnel Boring Machines (TBM) has a significant role in the planning, measurement of productivity and performance of any tunneling project. In this paper, the application of Adaptive Neuro Fuzzy Inference System (ANFIS) in prediction of TBM penetration rate is evaluated. For this purpose, a database including Rock Quality Designation (RQD), Uni-axial Compressive Strength (UCS) of the rock, the Distance between Planes of Weakness (DPW) in the rock mass, and empirical data regarding rate of penetration of TBM from several tunneling projects are collected. The Rate of Penetration is then estimated by using ANFIS. These results are then compared with measured TBM penetration rates (actual data). It is concluded that ANFIS can be applied successfully for such purpose and result in high accuracy for prediction for the rate of penetration of TBM. The method provided in this paper can assist the mining engineer to estimate the performance of tunneling accurately.

Jan 1, 2012

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 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