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Instability in rockpasses at deep levels often initiates as a result of stress induced fracturing of the rock on the walls of the pass. This may then progress to a stage at which the geological structure of the rock mass becomes dominant and permits large joint-defined blocks and slabs to become unstable. In this paper, a technique is described in which jointing parameters and their variabilities?orientations, spacings and lengths?are taken into account in estimating the extent of failure that may develop around a typical unsupported deep level gold mine rockpass. The results of this prediction are compared with the results obtained from a review of pass performance in the gold mining industry.

Jan 1, 2005

By I. Ince, S. Kahraman, M. Rostami, B. Dibavar

The density, porosity, and strength of rocks are fundamental in the design of geo-engineering projects. Determining these properties requires the preparation of smooth core samples, which is usually impossible for soft rocks. Besides, only fragmented samples may be available in some projects. A method for predicting rock properties from rock particles such as drilling debris would therefore be useful. This study was undertaken to develop prediction equations for compressive strength (UCS), tensile strength (BTS), density, and porosity values from the crushability index (CI) obtained from rock fragments. The results showed that UCS, BTS, density, and porosity were strongly correlated with the CI. The physical characteristics and strength of rocks may be predicted with the help of the derived equations. The CI test is a valuable tool for estimating rock properties in drilling projects and in situations where core specimens are not available.

Mar 14, 2024

By I. C. R. Gilchrist

A principal requirement in the design of a backfill transportation pipeline is the accurate prediction of the values of key slurry flow parameters. Input variables, such as particle size and solids concentration, are usually determined by the load-bearing requirements of the placed fill. It is therefore necessary to identify the optimum conditions of transport for a particular combination of input variables. This paper critically reviews the methods available to predict the values of flow parameters in slurry pipeline systems in the light of experimental data generated at a test facility. Particular reference is made to rod milled waste and deslimed tailings transport systems and, in the case of the former, it is shown that both pumping and load-bearing requirements can be optimized.

Jan 1, 1988

By I. O. Ondicho, E. K. Mutinda, B. O. Alunda, E. Agyekum

Driven by the necessity to improve blast performance regarding fragment size distribution in limestone mines, this paper introduces the prediction and measurement of blast fragmentation distribution through the modified Kuz-Ram (MKR) and Kuznetsov-Cunningham-Ouchterlony (KCO) models. Precise prediction and measurement of rock fragmentation resulting from blasting play a critical role in hard rock ore extraction. This is due to the substantial influence of post-blast ore size distribution on the efficiency of all subsequent downstream rock handling and processing operations. Additionally, employing secondary breakage of boulders, when necessary, leads to an unjustified rise in production costs. In this paper, the MKR and KCO models were utilised to identify the most appropriate model for application in Bisil and Simba quarries situated in Kajiado County, Kenya. Split-Desktop was used for blast fragment measurement by processing digital images obtained after blasting and computing the fragment size distribution of the blasted rock. As per the investigation, the recorded percentages of boulders generated at the sites ranged from 7% to 12.3% for the Simba quarry and from 11.2% to 23.9% for the Bisil quarry, respectively. Regression, correlation, and root mean square error (RMSE) were employed as the primary performance indicators. The study concluded that KCO outperformed MKR in accurately predicting blast fragment sizes in the examined quarries.

Mar 5, 2025

By A. Singh, R. D. Govender

The current method employed to quantify the efficiency of separation of ferromagnetic ores by wet low intensity magnetic drum separators (WLIMS) incorporates the use of a conventional benchscale Davis Tube (DT) operating at a magnetic field intensity that is equivalent to that of the drum’s surface. However, empirical research has indicated that the magnetic force, or force index, rather than the magnetic field intensity, is the critical factor in the operation of the magnetic separator (Murariu and Svoboda, 2002). Furthermore, the current aforementioned practice would yield incorrect information as the magnetic field gradients produced by a typical WLIMS unit differs considerably from that of a bench-scale DT. In light of this, research on magnetite focusing primarily on the scale-up of DT results to pilotscale WLIMS were undertaken. The investigation entailed a comparative study between that of a typical WLIMS circuit and a bench-scale DT. The purpose was to practically evaluate the performance of a WLIMS, bench-marked against the traditional laboratory-scale DT unit. Moreover, the secondary objective was to produce a magnetite concentrate graded at 69% Fe, 95% -45μm, as a suitable source of separation media for use in the Dense Medium Separation (DMS) industry. Fundamental findings of previous works provided a framework for the study, however, a realworld approach was explored. Preliminary testwork conducted at Mintek investigated the performance of a DT and a typical multi-stage laboratory-scale WLIMS circuit (operating at 1000 Gauss at the surface). The results attained indicated that a DT operating at high intensities is comparable to a single rougher WLIMS stage. Additionally, it was observed that the three stage laboratory-scale WLIMS circuit performed similarly to the DT operating at 1000 Gauss. Moreover, piloting testwork was undertaken, carried out in larger 380mm drums, and the results attained showed a strong correlation with laboratory-scale findings. Keywords: Davis Tube, wet low intensity magnetic separation, magnetite

Jan 1, 2020

By M. Kamali

In this research, in order to predict the peak particle velocity (PPV)(as vibration indicator) caused by blasting projects in the excavations of the Karoun III power plant and dam, three techniques including statistical, empirical, and neural network were used and their results were interpreted and compared. First, multivariate regression analysis (MVRA) was used as statistical approach. Next, PPV was predicted using some widely used empirical models. Lastly, an artificial neural network was used. In the ANN model, maximum charge per delay, total charge per round, distance from blast site, direction of firing, blasthole length, number of blastholes, total delay in milliseconds, number of delay intervals, and average specific charge were taken into consideration as input parameters and consequently the PPV as output parameter. The results of the techniques were interpreted from two points of view. Firstly, the correlation between the observed data and predicted ones, secondly the total error between observed data and predicted ones. The MVRA had a satisfactory correlation but its error of estimation was comparatively very high. The empirical model had reliable correlation and a small error of estimation; in total the results of empirical method were more reliable than those of MVRA. Generally, the ANN approach showed very high correlation and a very small error. The results of this research indicated that the ANN model is the best predicting model for PPV in comparison with other approaches.

Jan 1, 2010

By F. Sawyerr

A bubble population balance model is proposed for the prediction of Sauter mean bubble diameters in mechanical flotation cells. In the model, the flotation cell is treated as two separate, statistically homogeneous zones?the impeller zone, and the bulk tank zone. Balance functions for the rates of bubble breakage, coalescence, recirculation and inlet-outlet events are proposed based on classical chemical engineering research in two- and three-phase fluid mixing systems. An initial simulation of the population balance model shows trends in bubble size distributions comparable to measured distributions in industrial mechanical flotation cells.

Jan 1, 1998

By G. Akdogan, Q. G. Reynolds, S. J. Baumgartner

A computational model of a submerged arc furnace (SAF) used in the production of ferrochrome is presented. The model‘s intended use is to investigate the extent to which intrinsic and extrinsic properties of the raw materials affect burden distribution and electrical resistance within the furnace. The model is built on the discrete element method and calculates the mechanical interactions of particle distributions resulting from the flow motion of typical raw materials used in the smelting of chromium ore. This model excludes the effects of thermodynamics, furnace chemistry, and heat transfer. It illustrates how the consumption of materials (chromite pellets, flux, and reductant) is affected by changes in electrode length, reductant fractions, and reductant sizing and density during the formation of a reductant bed. The resistance calculation algorithm developed by Mintek was applied to construct networks developed from particle contacts, which can quantitatively generate estimates of the electrode-to-electrode and electrode-to-bath electrical conduction conditions.

Apr 16, 2024

By A. Adeli, A. V. Metcalfe, E. Addo, E. Sepulveda

"The accurate modelling of geometallurgical data can significantly improve decision-making and help optimize mining operations. This case study compares models for predicting copper recovery from three indirect test measurements that are typically available, to avoid the cost of direct measurement of recovery. Geometallurgical data from 930 drill core samples, with an average length of 19 m, from an orebody in South America have been analysed. The data includes copper recovery and the results of three other tests: Bond mill index test; resistance to abrasion and breakage index; and semi-autogenous grinding power index test. A genetic algorithm is used to impute missing data at some locations so as to make use of all 930 samples. The distribution of the variables is modelled with D-vine copula and predictions of copper recovery are compared with those from regressions fitted by ordinary least squares and generalized least squares. The D-vine copula model had the least mean absolute error. IntroductionIn this paper we compare the use of D-vine copula, generalized least squares (GLS), and ordinary least squares (OLS) for modelling geometallurgical data from an orebody in South America. The first objective is to construct models for predicting copper recovery (Rec) from the Bond mill index test (BWi); resistance to abrasion and breakage index (A*b); and semi-autogenous grinding (SAG) power index test (Spi). This involves fitting a D-vine copula and regression models fitted by OLS and GLS. The second objective is to investigate the performance of the fitted models for predicting Rec (Willmott and Matsuura 2005).Traditional resource model approaches either ignore the mineral processing characteristics of extracted tonnages or treat processing as an independent component of a mining operation. The net present value (or any other objective) can be truly optimized only by considering the mining operation as an integrated system in which net value is defined as the end-product that the company sells. This approach requires the resource model to be extended to include all relevant rock properties and processing responses."

Mar 1, 2019

By N. Snyders, I. Mwandawande, S. M. Bradshaw, M. Karimi

"Computational fluid dynamics (CFD) was applied to predict the average gas holdup and the axial gas holdup variation in a 13.5 m high cylindrical column 0.91 m diameter. The column was operating in batch mode. A Eulerian-Eulerian multiphase approach with appropriate interphase momentum exchange terms was applied to simulate the gas-liquid flow inside the column. Turbulence in the continuous phase was modelled using the k-_ realizable turbulence model. The predicted average gas holdup values were in good agreement with experimental data. The axial gas holdup prediction was generally good for the middle and top parts of the column, but was over-predicted for the bottom part of the column. Bubble velocity profiles were observed in which the axial velocity of the air bubbles decreased with height in the column. This may be related to the upward increase in gas holdup in the column. Simulations were also conducted to compare the gas holdup predicted with the universal, the Schiller-Naumann, and the Morsi-Alexander drag models. The gas holdup predictions for the three drag models were not significantly different. IntroductionColumn flotation is an important concentration technology that is used in the mineral processing and coal beneficiation industries. The growing interest in the use of column flotation in mineral processing has been attributed to the simpler flotation circuits and improved metallurgical performance compared to conventional flotation cells (Finch and Dobby, 1990). Flotation columns have also found other applications outside mineral processing, such as de-inking of recycled paper (Finch and Hardie, 1999).In column flotation, a rising swarm of air bubbles generated by means of air spargers is employed to collect the valuable mineral particles and separate them from the gangue minerals in a countercurrent process. Wash water, which is continuously fed at the top of the column, is used to eliminate entrained particles and stabilize the froth. The column volume can be divided into two sections – the collection zone in which the bubbles collect the floatable mineral particles, and the cleaning zone (or froth zone) where product upgrading is enhanced through the removal of unwanted particles entrained in the water mixed with bubbles from the collection zone."

Jan 1, 2019

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 M. Karimi

Artificial neural networks (ANNs) have found their applications in the modelling of unit operations of mineral processing plants. In this research, laboratory-scale tests were conducted, using a three-inch diameter Mozley hydrocyclone. Main parameters included pressure drop at inlet, solid per cent, vortex and apex diameter were adjusted. The corrected cut size (d50c) and the flow rates of underflow and overflow were determined. Multi layers perceptron (MLP) feed forward network architectures were designed to predict the responses. The results showed a good correlation between experimental and network output, for corrected cut size and flow rates. Keywords: hydrocyclone, artificial neural network, corrected cut size, flow rates.

Jan 1, 2010

By E. Öğretici, S. Kahraman

The indirect estimation of intact rock properties is particularly useful for preliminary investigations in engineering projects. In this paper we examine the usability of electrical resistivity, a nondestructive measurement, for the prediction of physical and mechanical rock characteristics. Physico-mechanical tests (uniaxial compression, Brazilian tensile, density, and porosity tests) and electrical resistivity measurements were performed on specimens of 36 rock types. Before the resistivity tests, the specimens were completely saturated with saline solution. Evaluation of the test results showed that there are medium or strong correlations between resistivity and rock properties. There are also strong or stronger correlations between the two parameters for the rock classes. The regression equations developed were statistically tested, and their validity was confirmed. The results were also compared with previous studies. The conclusion is that electrical resistivity measurement can be used for reliably estimating physical and mechanical rock characteristics.

Aug 8, 2024

By V. G. Pienaar, B. M. Mbiya, P. T. Slatter

[a constant b constant cc onstant c' constant D pipe diameter (m) Dshear shear diameter (m) E error function fth theoretical friction factor F function F' function K fluid consistency index (Pa sn) kv valve loss coefficient L pipe length (m) n flow behaviour index N number of data points ?P valve pressure drop (Pa) Q flow rate (m3/s) Re Reynolds number Re3 Reynolds number (Slatter) V average velocity (m/s) Vann annulus velocity (m/s) x variable X number of independent variables y variable Y number of fundamental dimensions z variable µeff effective viscosity (Pa s) ? valve degree of opening d partial derivative ? fluid density (kg/m3) [ ] function]

Jan 1, 2007

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 S. Swanepoel, A. V. Cherkaev, Q. G. Reynolds, M. Erwee

Ferrochrome (FeCr) is a vital ingredient in stainless steel production and is commonly produced by smelting chromite ores in submerged arc furnaces. Silicon (Si) is a componrnt of the FeCr alloy from the smelting process. Being both a contaminant and an indicator of the state of the process, its content needs to be kept within a narrow range. The complex chemistry of the smelting process and interactions between various factors make Si prediction by fundamental models infeasible. A data-driven approach offers an alternative by formulating the model based on historical data. This paper presents a systematic development of a data-driven model for predicting Si content. The model includes dimensionality reduction, regularized linear regression, and a boosting method to reduce the variability of the linear model residuals. It shows a good performance on testing data (R2 = 0.63). The most significant predictors, as determined by linear model analysis and permutation testing, are previous Si content, carbon and titanium in the alloy, calcium oxide in the slag, resistance between electrodes, and electrode slips. Further analysis using thermodynamic data and models, links these predictors to electrode control and slag chemistry. This analysis lays the foundation for implementing Si content control on a ferrochrome smelter.

Mar 14, 2024

By P. C. -H. Rhee, H. -G. Lee, J. -H. Choi, D. S. Kim, S. -B. Lee

In order to predict the composition of inclusions and to ascertain a method to prevent inclusions from forming in liquid Fe-16 mass Cr alloy, a thermodynamic database was developed through a quantitative determination of thermodynamic relationships of Cr-Al-Si-Mn systems in the liquid Fe alloys. Applications of the databases to the prediction of Mn/Si complex deoxidation with Alin Fe-16 mass Cr alloy were demonstrated in succession. The electromagnetic levitation technique using a cold crucible was employed to separate inclusions from liquid metallic alloys completely and to prevent any contamination from surroundings. Various interaction parameters in the liquid Fe-16 mass per cent Cr alloy system were determined; these are: [eAl(Fe)Cr= 0.19/T, rAl(Fe)O,Cr= -0.01, rAl(Fe)O,Cr= -0.00013, eS1Cr(Fe)= -0.38/T,rSi(Fe)O,Cr= 0.007, rO(Fe)Si,Cr= 0.0044, rA1(Fe)Si,Cr= -0.0075, rSi(Fe)A1,Cr= -0.0078, rSi(Fe)Mn,Cr= 0.005, and rMn(Fe)Si,Cr=0.01.] An improved database, utilizing interaction parameters for molten metal determined in this study, and the Fact Sage slag database of the MnO-SiO2-Al2O3-CrOx-MgO system were used for thermodynamic calculations. These were carried out under various thermodynamic conditions, and results were compared with experimental data of Si/Al, Mn/Si, and Mn/Si/Al deoxidation equilibria. With the abovementioned results, together with experimentally obtained data, thermodynamic conditions were determined, in particular Mn and Si contents, under which liquid inclusions form in liquid Fe-16 mass per cent Cr alloy. The critical Al content in liquid Fe-16 per cent Cr alloy, above which solid inclusion of corundum phase ((Al,Cr)2O3) formed, was as low as 10 ppm. This indicates that extreme care must be taken in controlling the Al content in the metal to avoid formation of solid corundum phase ((Al,Cr)2O3) inclusion. The compositional change prediction of inclusions, which originate from slag entrapment and by Ca addition, was demonstrated by use of the alloy database optimized through this study, and the Fact Sage oxide database. For Si-deoxidized Fe-16 per cent Cr alloy, high Si and low basicity of slag are effective to obtain liquid inclusions. For Al-deoxidized Fe-16 per cent Cr alloy, it is important to keep the Si content lower than 0.1 per cent and it is required to add Ca. Keywords: inclusion, thermodynamic simulation, deoxidation, Fe-16 per cent Cr alloy,stainless steel, interaction parameter, cold crucible

Jan 1, 2004

By George Kayesa

[ ] A multiple-bench slope failure occurred at Letlhakane mine on 14th July 2005. No injuries or damage to equipment was suffered and mining production was not affected. Slope failure was preceded by the precursors of tension crack formation, crack widening and extension as well as slope monitoring targets movement. It was predicted that slope failure was imminent using the Geomos slope monitoring system, though the timing was not certain. The area to be affected by the slope failure was also known before hand as was the slope failure mode. As a result, measures were taken to avoid exposing personnel and mining equipment to the slope failure risk. This paper discusses how the prediction of the slope failure of 14th July 2005 using the Geomos slope monitoring system resulted into avoiding potentially fatal injury, damage to mining equipment and loss of mining production.

Jan 1, 2006

By K. Aoki, Y. Mito, S. Shirasagi

The authors developed the TBM Excavation Control System (the TBM Navigator), in order to realize the advanced observational construction. During the excavation using this system, the rock strength value is immediately calculated from the TBM driving data as an index of rock properties, and the drill energy coefficient is also calculated from the drill logging data that is carried out using the probe hole ahead of the tunnel face. In this study, a new, geostatistical simulation-based method is proposed for the automatic prediction of the rock properties ahead of the tunnel face with good precision, using both the drill logging data and the TBM driving data. The applicability of this method is validated through the prediction at the actual tunnel excavation that passes through the faults. Les auteurs ont mis au point un Système de Contrôle de forage avec la machine à pleine section (Navigateur de la machine à pleine section), en vue de réaliser un système de surveillance plus efficace. Avec ce système, la résistance de la roche est immédiatement calculée, au cours du forage, à partir des données de conduite de la machine, comme indice des propriétés de la roche, et le coefficient d'énergie de la foreuse est également calculé à partir des données de log de forage collectées dans un trou de sonde foré dans le front de taille. Dans cette étude, on propose une nouvelle méthode basée sur la simulation géostatistique qui permet de prévoir d’une manière automatique, des propriétés de roches se trouvant derrière le front de taille avec une précision satisfaisante, à l’aide des données de log de forage et celles de conduite de la machine à pleine section. Cette méthode s’est avérée suffisamment précise au cours du forage d’un tunnel réel qui traversait une zone de failles. Die Autoren entwickelten das TBM Ausschachtungssteuerungssystem (den TBM Navigator), um noch besser überwachte Bauarbeiten zu ermöglichen. Unter Einsatz dieses Systems wird die Gesteinsfestigkeit während der Ausschachtungsarbeiten unmittelbar aus den TBM Antriebsdaten als ein Index für die Gesteinseigenschaften berechnet. Gleichzeitig wird auch der Bohrenergiekoeffizient aus den Bohrlogdaten berechnet, die an Hand der Probebohrung am Stirnende des Tunnels erhalten wurden. In der vorliegenden Studie wurde ein neuartiges, auf geostatistischen Methoden basierendes Verfahren für die automatische und angemessen genaue Vorhersage der Gesteinseigenschaften am Stirnende des Tunnels vorgeschlagen, für das sowohl die Bohrlogdaten als auch die TBM Antriebsdaten verwendet werden. Die Anwendbarkeit dieser Methode wird durch die Vorhersage bei einer tatsächlichen, durch Verwerfungen verlaufenden Tunnelausschachtung bewiesen.

Jan 1, 2003

Prediction of the performance of explosives In bench mining by C. M. LOWNDS, B.Se. Hons (Rhodes), Ph.D (Cape) (Visitor) Some of the problems encountered in the calculation of the relative weight strength of explosives are discussed, and a realistic model of the behaviour of explosion products in a borehole is proposed. The heat flow from condensed to gaseous products is calculated as a function of time, and the relationship between the pressure and the volume of the product gases is found by a consideration of the compression of the rock between radial cracks. Work done on the burden is assumed to cease when the cracks first appear at the face. Reasonable values of burden and crack velocities are obtained from the model. Calculations of the relative weight strengths of aluminized mixtures of ammonium nitrate and fuel oil show that the increased density resulting from the addition of aluminium is the main advantage to be gained.

Jan 2, 1975