Search Documents

By T. Fabritius, L. Hekkala, J. Härkki

The Outokumpu steel belt sintering technology is used for manufacturing chromite pellets that are charged into smelting furnace for ferrochromium production. Hot air is blown through the moving bed of raw pellets. Direct temperature and flow measurements are difficult to do in the bed of a real scale belt sintering process. Therefore, a tested and reliable mathematical model would be a valuable help for optimising operational parameters of the process and designing new constructional improvements. The aim of this work is to present a mathematical model that calculates the gas flow and temperature distribution in the bed of pellets and the atmosphere. Computational fluid dynamics program FLUENT is used to calculate the gas flow, composition and temperature of the gas in the sintering bed during processing. Energy equation for the bed, containing the effects of evaporation of water and oxidation of carbon and iron oxide, will be added to the model to obtain the temperature of the pellets. The porous media model used for pressure drop calculations in the bed is shortly discussed. A comparison between CFD-calculations and experiments with a pilot scale batch-sintering reactor are also presented. The final model can be used as an engineering tool when developing the process and the equipment further. Different designs can be easily tested with the model and the effects of the changes to the flow pattern and temperature distribution can be studied.

Jan 1, 2004

By R. B. Khumalo, T. Chauke, T. Mtshali, F. K. Mulenga, B. Makgate, N. M. Chiloane, T. Moyane, V. C. Madanda

While high production rates are important for the profitability of a mine, the influence of geotechnical engineering cannot be ignored. In block caving, a high-stress level is required for cave propagation; this is one of the core elements for ore recovery. Therefore, stress distribution and geological structures play a major role in the planning and layout design of the mine. This paper explores the influence of stress and geological features on the design of the mine from the feasibility study phase. The geology and stress measurement of the mine were determined through logging and overcoring, respectively. This study found that while production rate is the primary operational consideration, the long-term layout design of the undercut face advance, face angle, drawpoint spacing, and undercutting sequence is mainly governed by the stress orientation and major geological structures. Moreover, widely spaced drawpoints result in isolated draw zones, consequently, resulting in ore loss and early dilution whereas closely spaced drawpoints affect the stability of the major apex pillar. This paper also provides insight into how operations can leverage stress distribution to optimise mine layout and safety in massive mining methods.

Nov 24, 2025

By P. Stefanek, N. Duda, B. Jachni, P. Stefaniak, B. Bursa

The Zelazny Most Tailings Storage Facility (TSF) is the largest reservoir of post–flotation tailings in Europe. The total amount of tailings from the mines in Lubin, Rudna, and Polkowice are stored each year at the disposal facility, which reaches approximately 30 million tons. It is crucial to accurately monitor and maintain such a huge storage facility, for the safety and economics of the entire region. In general, the monitoring network installed at the Zelazny Most TSF includes four groups of components: (a) geotechnical network (VW pore pressure transducers and inclinometers), (b) hydrological network (open piezometers, water level gauges, drainage discharge measurements, (c) geodetic survey network (e.g. surface and in-depth benchmarks, laser measurements, GPS measurements within GEOMOS network and (d) seismic network (e.g. accelerometer stations, cone penetration tests.) Apart from the above, chemical water analyses, tests of soil samples, monitoring of spigotting processes, and monitoring of relief wells’ discharge are also conducted. In total, approximately 2900 monitoring instruments are installed within the area of the Zelazny Most TSF. Such large amounts of data from the various information sources makes manual data analysis by the engineers almost impossible. In this paper we discuss a machine learning driven approach to improve the quality of the monitoring and maintenance of such facilities. We focus on the seismic cone penetration test (SCPT) data analysis. First, we carefully describe the collected data, its quality and availability. Then we discuss possible events that can occur in the TSF that need to be predicted using SCPT. Based on the information obtained in these two steps, the applicability of several machine learning methods is estimated. Some of them are then tested on available historical data. The algorithms described in this article will be further developed in the IlluMINEation project (H2020).

Sep 1, 2021

By D. Marcotte, R. V. Dutaut

"In mineral resource evaluations, geostatistical methods known as global change of support allow prediction of the theoretical histogram and gradetonnage curves prior to interpolations or simulations of grades. Two methods commonly used by professionals to guide the choice of interpolation parameters and assess results are the discrete Gaussian model (DGM) and the indirect lognormal correction (IndLog). These models rely upon an estimate of the dispersion variance of the blocks, which is derived by numerical integration of the variogram model over a discretized block. Due to difficulties in obtaining well-formed traditional experimental variograms (especially in the presence of outliers and limited clustered data), many professionals prefer to use ‘normalized’ variograms such as correlogram (non-ergodic variogram), pairwise-relative, or variogram of the normal score transform. A series of simulations with different grade distributions and variogram models are used to assess the performances and robustness of the various variogram estimators with respect to the DGM and IndLog global change of support. Our results show that the traditional variogram, the correlogram, and normal score variogram have better performances, compared to pairwise, for both DGM and IndLog. Moreover, DGM provided better results than IndLog for the grade distributions that are not strictly lognormal. These findings provide valuable guides for geostatistics practitioners. IntroductionWhen reporting resource estimates,practitioners are required to follow generalstandards described in the NI43-101 (CIMguidelines), JORC, or SAMREC codes. One cangenerally recognize three main parts directlyrelated to the block model:•,Pre-processing: exploratory data analysis (EDA), domaining, capping, compositing, declustering, variography•,Processing: block size, neighbourhood, interpolation types (linear or nonlinear)•,Post-processing: classification, reporting.Pre-processing aims to simplify and strengthen the processing step. Ideally, domaining, capping. and compositing is aimed at defining a single homogenous population. During the processing phase, a common practice is to use a block size corresponding to the planned selective mining unit (SMU). In most precious metal deposits (gold, notably), the SMU size is frequently smaller than the recommended half data spacing (Journel and Huijbregts 1978), resulting in high estimation variance and either a high degree of smoothing if the regression slope is managed or a high degree of conditional bias if it is not. Most actual resource estimates are made using block sizes between one-quarter to one-sixth of the average data spacing, sometimes even smaller. In addition to the block size, the interpolation choices for the neighbourhood selection and interpolator (e.g. inverse distance (ID) or ordinary kriging) are often based on the Qualified Person’s (the QP) experience and some basic validation plots that often do not consider the conditional bias (e.g. trends or SWATHs plots, which are designed to compare two sets of population using a one-dimensional graph)."

Jan 1, 2018

By J. Sjöberg, T. Savilahti, S. B. Umar

"Sublevel caving in Malmberget mine results in mining-induced surface deformation. One of the currently mined orebodies is the Printzsköld orebody. As mining deepens there is need to assess the behaviour of the cave formed in the subsurface above this orebody. Numerical analysis was used to assess the effects of extraction to deeper levels and perform strength parametric studies. Stress redistribution was studied, and the results showed high stress buildups in the hangingwall and the crown pillar. Two failure mechanisms have been identified – shear and tensile. Reducing cohesion by 50% increased the area of the yielded zone by more than 100% in the hangingwall.IntroductionThe Malmberget mine is owned and operated by the Luossavaara-Kiirunavaara AB (LKAB) mining company. Iron ore is extracted by large-scale sublevel caving. The mine comprises a total of 20 orebodies, about 10 of which are in production today (Figure 1). The mine is located in the municipality of Gallivare, about 100 km north of the Arctic Circle (Figure 2).Successful sublevel caving requires progressive caving of the orebody after initial blasting. This results in caving of the hangingwall, sometimes all the way to surface, resulting in surface deformation. As mining progresses to deeper levels a larger area is affected by deformation. Over the years, extraction from the Malmberget orebodies has led to deformation of the ground surface, affecting residential areas and existing infrastructure.Forecasting the caving process is not straightforward as it can be rapid or slow, depending on the rock mass conditions, stress conditions, the failure mechanisms at work, etc. Moreover, several of the orebodies in Malmberget are non-daylighting, which makes reliable caving analysis even more difficult, primarily since there is less available experience from such cases. The present study was designed to improve the understanding of the caving and deformation mechanisms at Malmberget, and in particularly for the Printzskold orebody"

Jan 1, 2017

By Ernie Holden, Chris Ringas

In the last 20 years, In Line Inspection (ILI) using intelligent pigs has become the principal tool used by pipeline operators to assess the condition of their pipelines. New pipelines are normally designed to take intelligent pigs, but many older pipelines require some modifications and special procedures for their inspection. This paper is aimed at practicing engineers and managers of pipelines, or people aspiring to those positions. The paper describes the benefits of ILI and some of the practical issues regarding pipeline preparation and cleaning, choice of inspection tool, running pigs in pipelines, and what to do with the data collected. What are the responsibilities of the Pipeline Engineer ? ? Maintain reliable and acceptable performance of the pipeline in terms of safety and product delivery at economical cost. ? Provide a defined margin of safety for operating the pipeline at its designated pressure. ? Provide timely information on all pipeline defects such that repairs can be carried out according to a managed schedule. What Defects does the Pipeline Operator have to cope with ? A useful record of actual incidents seen in pipelines can be obtained from the web site of the US Office of Pipeline Safety (OPS) - http://ops.dot.gov/stats/stats.htm. US pipeline Operators are obliged by Law to report all pipeline incidents exceeding certain threshold criteria (e.g loss of life, escape of product, cost of incident etc). These OPS statistics show that corrosion and third party damage have remained consistently the prime causes of reportable incidents in the US, with similar experience elsewhere. There are several kinds of flaws and defects in pipelines that can lead to failure, the main families being :- ? Metal loss ? Cracks or crack-like defects ? Laminations and other mid-wall defects ? Geometric anomalies

Jan 1, 2006

By A. F. Silva, J. M. G. Sotomayor, V. F. N. Torres

Geotechnical monitoring plays an important role in the detection of operational safety issues in the slopes of open pits. Currently, monitoring companies offer several solutions involving robust technologies that boast highly reliable data and the ability to control risky conditions. The monitoring data must be processed and analysed so as to allow the results to be used for several purposes, thereby providing information that can be used to manage operational actions and optimize mining plans or engineering projects. In this work we analysed monitoring data (pore pressure and displacement) and its correlation with the tension and displacement of the mass of an established failure slope calculated using the finite element method. To optimize the back-analysis, a Python language routine was developed using input data (point coordinates, parameter matrix, and critical section) to use software with the rock mass parameters (cohesion, friction angle, Young’s modulus, and Poisson’s ratio). For the back-analysis, the Mohr-Coulomb criterion was applied with the shear strength reduction technique to obtain the strength reduction factor. The results were consistent with both the measured displacements and the maximum deformation contours, revealing the possible failure mechanism, allowing the strength parameters to be calibrated according to the slope failure conditions, and providing information about the contribution of each variable (parameter) to the slope failure in the study area.

Oct 1, 2021

By G. Broadbent

It is an honour to be invited as a speaker to this ICCR conference and a pleasure to be with you here in South Africa. I have been asked to talk about the competitiveness of coal versus other energy alternatives. Coal supplies nearly one-quarter of the global primary energy. Its most direct competitors are gas, nuclear and renewables. Oil is predominantly for transport fuels. Fuel oil is competitive with coal when crude is below its long-run average price and has some niche opportunities. But I will confine my comments to nuclear, renewables and particularly natural gas as the most potent current competitive threat to coal. Competitiveness is more than just cost and price; there is environmental acceptability, security or reliability and increasingly image. These factors are more of a spectrum than discrete issues. Dollars and cents remain the key issue for competitiveness but one must recognize the impact of politics in sustainable development and energy security.

Jan 1, 2001

By D. Moses, J. A. Onyango

Carbonatites are generally competent rock masses with rock mass rating class II rating 60–74. In spite of their competency, they tend to be affected by weak features like manganese-iron veins and/or in situ rock damage due to brecciation associated with carbonatite complexes. Rock slope failure in such hard rocks is complex since such structures within the rock mass form weak links that could potentially control slope instability. In this contribution, a numerical simulation using phase2 v 7.0 was carried out to investigate the influence of in situ rock damage on the stability of mine pit walls. The outcome reveals that, the existence of breccia in the competent rock mass has the capability to reduce the slope stability performance particularly at gentle dipping angles of emplacement in close range to the slope toe. However, as the emplacement position of breccia moves away from the pit wall, the stability performance increases at gentle dipping angle <50º. On the contrary, at the dipping angle of 50° the performance of slope reduced, and at steeper angles >50° the impact becomes negligible. Thus, from a series of analyses, mine design in brecciated rock masses, the ratio of 1:5 between the breccia distance from slope toe and pit depth should be implemented to counter its impact, and if the breccia is within or close to the pit limit, a deliberate effort must be made to mine it out.

Sep 1, 2025

By B. Clermont

Ball mills are usually the largest consumers of energy within a mineral concentrator. Comminution is responsible for 50% of the total mineral processing cost. In today?s global markets, expanding mining groups are trying to optimize mill performances. Since comminution is concerned with liberating valuable minerals for recovery in the separation process, it is crucial to run the mills at the best operating conditions which lead to good liberation at competitive throughputs with minimum costs (energy and wear). The high availability of the equipment is also essential to maximize production and profit. To reach this key objective, continuous and reliable information about the mill operation is vital. An innovative tool which can deliver information about in-mill dynamics has been developed by Magotteaux. It can provide online and accurate measurements of the degree of grinding ball fill and pulp position for timely decision making and actions. This tool could be used on its own or linked to an automatic grinding ball loading system named Magoload. Therefore, ball load could be kept constant by using direct measurement. This article describes the Sensomag and presents some of the major improvements that can be achieved with it. Some other promising avenues are still to be explored. Keywords: Comminution, process control, process optimization, process instrumentation, online analysis.

Jan 1, 2010

By K. Cole, D. Mesa, P. Brito-Parada, M. R. van Heerden

Turbulence in mechanical flotation cells, achieved via an impeller, plays a key role in keeping particles in suspension, dispersing air bubbles, and promoting particle-bubble collision. However, studying the hydrodynamics of a flotation cell is not a simple task, due to the complex nature of flotation systems which are opaque, turbulent, multiphase and polydisperse in terms of particle and bubble sizes. In this paper we study the impact of impeller design modifications on the hydrodynamics of a continuously overflowing bench-scale flotation tank. To this end, two different impeller designs, with and without a stator, were assessed using Positron Emission Particle Tracking (PEPT). This allowed the authors to determine, for the first time, the effect of an impeller design on the behaviour of both hydrophobic and hydrophilic particle tracers. It was experimentally observed that the use of a stator modifies the hydrodynamics within the flotation cell, distorting the lower mixing loop that is characteristic of axial impellers. The role of the stator in dissipating turbulence results in reduced particle velocities outside of the impeller-stator region. These results have important implications for flotation cell design and are discussed in the context of the impact that different designs have on particle movement, flotation hydrodynamics and, ultimately, flotation performance. The data set generated is also extremely valuable for modelling and validation purposes. Keywords: Flotation, flotation tank, impeller design, rotor, stator, PEPT, hydrodynamics

Jan 1, 2020

By E. K. Mutinda, D. K. Maina, R. M. Kasomo, B. O. Alunda

Assessment of blast fragment size distribution is critical in mining operations because it is the initial step towards mineral extraction. Different empirical models and techniques are available for predicting and investigating the consequences of blasting, one of which is the Kuznetsov Cunningham-Ouchterlony (KCO) model. In this paper we summarize the advances in the empirical models from inception until now, and explore the improvements that have been made so far with particular emphasis is on the most recent KCO model. Utilization of the model and the errors that arise between expected and the actual outcomes are analysed. The results indicate that the KCO model remains useful for predicting the blast fragmentation at limestone mine sites, despite the availability of other advanced prediction models. It is also a valuable instrument for pre-surveying the impact of varying certain parameters of a blast plan.

Mar 1, 2021

By J. P. T. Kapusta

"The copper smelting industry faces increasingly stringent environmental regulations and must continue driving innovation to reduce energy usage in its production chain. With the coming of age of ‘bottom-blowing’ copper technologies in China over the last decade, much renewed attention has been brought to tuyere bath smelting for clean copper-making. Since bottom-blowing sonic injection was originally developed and implemented in steelmaking in the 1970s and lead smelting in the 1990s, the time seems appropriate to revisit the sonic injection concepts and dispel some myths. After reviewing the trends in the copper industry and providing a brief historical context of research and development related to sonic injection, the author presents a comparison of the main submerged tuyere bath smelting technologies, namely the Noranda Reactor (NR), the Teniente Converter (TC), and the Chinese Bottom-Blowing Smelting Furnace (SKS/BBS) for copper, and the Queneau-Schuhmann-Lurgi Reactor (QSL) for lead. The core of this article, however, consists of a brief description of the fundamental theories for sonic injection (jetting regime) and ‘sonic flow mapping’ to illustrate the relationship between the minimum tuyere back-pressure required to achieve sonic flow and the tuyere internal diameter. The article also offers a comparison between side- and bottom-blowing in jetting regime before concluding with the author’s vision of the new trend in submerged tuyere bath smelting. IntroductionIn the last decade, developments in the copper smelting industry have been driven by two key concepts: (1) increasing cleaner smelting capacity to meet the world’s growing copper demand, as illustrated in Figure 1, and (2) increasing process off-gas capture to comply with more stringent environmental regulations and abide by a corporate social responsibility ethic of a clean work environment (for smelter employees) and clean air (for families living around smelters). The copper smelting industry has also faced some major challenges in the last few decades, including (1) low treatment and refining charges (TC/RC or processing fees) impacting custom smelters, (2) lower concentrate quality and grades with higher levels of impurities (e.g. As and Hg), (3) higher processing and transportation costs due to the rising cost of energy, (4) restrictions in process intensification (tonnage oxygen usage) due to furnace integrity limits, and (5) scarcity of educated and trained personnel due to fewer metallurgists graduating from pyrometallurgical school programmes combined with a high retirement rate of skilled workers."

Nov 1, 2018

By S. Banisi, A. Ghasemi, E. Nematollahi

Discrete element method (DEM) has been used as a popular simulation method to verify designs by visualising how material will flow through complex equipment geometries. Although DEM simulation is a powerful design tool, finding a DEM model which includes real material properties (e.g., shape, cohesion and friction coefficients) is not computationally feasible. In order to obtain more realistic results, particle energy loss due to rolling friction has been highlighted by many researchers. To implement a reverse torque to account for rolling friction, various models have been proposed. On account of the complexity of the problem, there is no unique model for all applications (i.e. dynamic and pseudo-static regimes). In this paper, an in-house developed DEM software (KMPCDEM ©) was used to assess the robustness of three commonly used models by comparing the repose angle of iron ore pellets obtained through the draw down test in a laboratory setup and then the elastic–plastic spring dashpot model was modified based on considering the individual parameters instead of relative parameters of two contact entities. Results showed that the modified model could produce higher repose angle. The modified model was used to calibrate DEM simulation of repose angle of iron ore pellets in a laboratory setup of the draw down test. Comparison of the calibrated DEM simulation and laboratory results showed 2° differences between the predicted and measured angle of repose. This difference was attributed to considering the particle shape effects by assuming a spherical shape for particles. Keywords: DEM, rolling friction,particle shape, repose angle

Jan 1, 2020

By John E. Leitch

The cost of corrosion as measured by such cost components as the renovation or replacement of coated steel, or the use of expensive coating systems on steel, is considerable. Extrapolating from figures for the USA would place the overall cost of corrosion for South Africa as a figure of the order of magnitude of something over 1% of the GNP. This is a sizeable amount, of which costs associated with atmospheric corrosion would be a significant proportion. The corrosivity of an atmosphere can be defined as the ability of the atmosphere to cause corrosion in a given metal or alloy (International Standards Organization [1]). The ISO Standard 9223 specifies the key factors in the atmospheric corrosion of metals and alloys, and defines categories of corrosivity on the basis of these factors. Prior to the publication of that ISO standard, Callaghan published the results of his twenty-year exposure programme and his excellent corrosivity map of Southern Africa [2]. The present author published updates of the corrosivity map in 1999 [3] and again in 2003 [4]. The summary of the individual areas of corrosivity around Southern Africa was published in the latter paper, and is reproduced here as the following TABLE 1. Of significance in TABLE 1 are the numerous regions of very high corrosivity (C5 or beyond), particularly the rural West Coast shoreline, the North East Coast (KZN) shoreline, and the coastal cities Cape Town, Durban and Richards Bay. The corrosivity map as published is obviously based on much extrapolation as only a small number of points have been measured. During the past three years further measurements have been made, mostly however at the same sites in order to give greater reliability and to monitor long-term trends with changes in pollution. These two aspects are incorporated in this update. There has become available a greater amount of air pollution data for centres in South Africa than was the case some years ago. In this present paper the pollution data are used to extrapolate the corrosivity over areas where little or no direct corrosivity measurement has been made. This methodology is described in ISO 9223.

Jan 1, 2006

By L. Hekkala, J. Ollila, J. Keihäs, P. Mäkelä

The Outokumpu Steel Belt Sintering (SBS) Technology is used for manufacturing chromite pellets that are charged into a smelting furnace for ferrochromium production. One of the main elements in successful furnace operation is the control of gas flows inside the furnace, giving improved temperature distribution in the bed during the process. Computational Fluid Dynamics (CFD) gives excellent opportunities for studying these phenomena. An investigation using CFD can be performed relatively fast. For example, implications of different configurations can be studied within a day and an optimum design chosen. Therefore, Outokumpu Technology has developed a Steel Belt Sintering Model (SBSM), which takes advantage of a commercial CFD code. Each main physicochemical event occurring in a steel belt sintering furnace is incorporated independently in the SBS model as a sub-model, enabling every event to be studied separately. The commercial CFD code solves mass, momentum, species and energy equations for determination of the gas flow, composition and temperature. In addition, the Outokumpu SBSM takes into account the moving pellet bed, drying of pellets interms of water content, coke combustion, oxidation and reduction of chromite and the decomposition of carbonates and silicates. During the development of the model, numerous laboratory-scale tests were performed. The sub-models were validated against the laboratory tests. The reliability of the Outokumpu Steel Belt Sintering Model was validated against a pilot-scale batch-sintering furnace by comparing the modelling results against measurements. The aim of this paper is to give a brief presentation of the Outokumpu steel belt sintering model by showing some general modelling examples. Emphasis has been placed on demonstrating some of the main features of the model.

Jan 1, 2007

By A. Krause

Shovel-truck systems for loading and hauling material in open pit mines are now routinely analysed using simulation models or off-the-shelf simulation software packages, which can be very expensive for once-off or occasional use. The simulation models invariably produce different estimations of fleet sizes due to their differing estimations of cycle time. No single model or package can accurately estimate the required fleet size because the fleet operating parameters are characteristically random and dynamic. In order to improve confidence in sizing the fleet for a mining project, at least two estimation models should be used. This paper demonstrates that the Machine Repair Model can be modified and used as a model for estimating truck fleet size in an open pit shovel-truck system. The modified Machine Repair Model is first applied to a virtual open pit mine case study. The results compare favourably to output from other estimation models using the same input parameters for the virtual mine. The modified Machine Repair Model is further applied to an existing open pit coal operation, the Kwagga Section of Optimum Colliery as a case study. Again the results confirm those obtained from the virtual mine case study. It is concluded that the Machine Repair Model can be an affordable model compared to off-the-shelf generic software because it is easily modelled in Microsoft Excel, a software platform that most mines already use. This paper reports part of the work of a MSc research study submitted to the University of Witwatersrand, Johannesburg, South Africa. Keywords: simulation, bunching, probability distributions, cycle time, queuing, matching, shovel-truck, OEM.

Jan 1, 2007

By R. Nyirenda, B. Besa, N. Dzimunya

The accurate estimation of peak particle velocity (PPV) is crucial during the design of bench blasting operations in open pit mines, since the vibrations caused by blasting can significantly affect the integrity of nearby buildings and other structures. Conventional models used to predict blast-induced vibrations are not capable of capturing nonlinear relationships between the different blasting-related parameters. Soft computing techniques, i.e., techniques that are founded on the principles of artificial intelligence, effectively model these complexities. In this paper, we use the random forest (RF) algorithm to develop a model to predict blast-induced ground vibrations from bench blasting using 48 data records. The model was trained and tested using WEKA datamining software. To build this model, a feature selection process using several combinations of Attribute Evaluators and Search Methods under the WEKA Select Attributes tab was performed. The correlation coefficient of the actual data and RF model-predicted data was 0.95, and the weighted average of the relative absolute error (RAE) was 10.9%. The RF model performance was also compared to the equivalent-path-based (EPB) equation on the testing data-set, and it was seen that the RF model can effectively be used to predict PPV. The study also demonstrates that the EPB equation is a suitable empirical method for predicting PPV.

Mar 30, 2023

By D. Kumar, B. Rai, S. G. Srinivasan, V. Jain

Chalcopyrite and pyrite are among the major gold bearing minerals in the world. The gold content in chalcopyrite and pyrite varies from 0.02 to 200 ppm and 0.01 to 20 ppm, respectively. Apart from gold, chalcopyrite is also the primary source of copper. Thus, the recovery of gold and copper are often associated with the recovery of chalcopyrite and pyrite. Flotation is one of the most successful methods applied to beneficiate chalcopyrite and pyrite. The success of a flotation process depends on an appropriate choice of the flotation collector used to achieve the desired selectivity. A thorough understanding of the atomic structure of the predominantly exposed mineral surfaces can immensely aid in developing highly selective collectors that can exploit both the physical and chemical characteristics of these surfaces. In the present study, density functional theory calculations within the plane wave framework are used to understand the surface structure and reconstruction of the most stable chalcopyrite (001), (100), (110) and (112) and most stable pyrite (100) surfaces. The chalcopyrite (001) and (100) metal-terminated surfaces undergo significant reconstruction and result in metal-metal bond formation in the sub-surface layer while the surface layer is replaced by S-atoms. On the other hand, the (001) and (100) S-terminated surfaces show S—S disulfide bond formation upon relaxation, which are consistent with literature reports. The chalcopyrite (110), (112) surfaces and pyrite (100) surface undergo rearrangement, but no reconstructions in terms of metal-metal or disulfide bond formation are observed on these surfaces. Keywords: DFT, surface reconstruction, pyrite, chalcopyrite, adsorption

Jan 1, 2020

By P. J. Petit

"The complex planning required to achieve any planned production yields multiple and dissociated responses over the life of project (LOP). The customary decision-making process negates the possibilities of developing optimized and integral solutions from operating levels up to business and strategic levels. This results in an inefficient project or overall underperformance of the operation.In the project setting, disconnected trade-offs and improved performance studies become inadequate, because they are site-specific and use only a few comparative parameters. They are often based on a small data-set.Decisions taken to achieve overall objectives require the correct determination and dissemination of key performance indicators (KPIs). The KPIs indicate efficiency in operation, whereby the marginal rate of technical substitution corresponds to the rate of production. It is the necessary condition for optimization. Performance realization for sustainability follows optimization modelling, the latter often being presented with financial results such as business net present value (NPV). It considers techno-financial constraints and provides a strategic and aligned outlook of KPI decisions for an enhanced and integrated outcome.This paper explains a mining case study that is rendered efficient, and through business optimization (BO) short-term and sustainable targets are reached. Business optimization increases the NPV by 14.7%. This is achieved by challenging conventional decision-making associated with maximizing business value by including environmental externalities within the LOP."

Jan 1, 2016