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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 Shiwei Wang, Ziwen Li, Chenhu Zhang, Peng Chen, Chengyong Wang

Accurate prediction of the partition coefficients in coal gravity separation is key to improving the preparation efficiency of coal and promoting its clean utilization. In China, the approximate formula method (AFM) has been applied to the calculation of coal gravity separation partition coefficients for decades, but its accuracy is limited. To improve the accuracy of the predicted partition coefficients, and thus the product yield of coal preparation plants, the present study proposes a modified hyperbolic tangent model to derive direct calculation formulas for the heavy medium and water medium separation partition coefficients. Four groups of coal samples were used to verify the accuracy of the direct formulas, and their predictions were compared with those of the AFM. The results showed that the partition coefficients and partition curves predicted by the direct formulas were closer to the actual values than those predicted by the AFM. Further, when the cleaned coal ash content was basically the same, the cleaned coal yield predicted by the direct formula was lower than that predicted by the AFM, and was also closer to the actual value. These results demonstrate that the direct formula produces more accurate results compared to the conventional AFM. As this formula has a reasonable theoretical basis, is simple to apply, and produces accurate results, it is expected to help improve the design and management level of coal preparation plants.

Oct 15, 2022

By Theodore Triplett

To assess the value of various subsidence mitigation techniques, twelve linear foundations were constructed above a longwall mine. The structures were monitored during and after undermining, and footing curvatures at the time of cracking were compared with predicted values. An unreinforced concrete footing sustained substantial damage. Other footings received varying degrees of damage, with inclusion of a sand layer significantly affecting performance. A post-tensioned concrete foundation suffered minimal cracking. Also, a technique developed by the Bureau of Mines is presented for determining the subsidence, slope, curvature and strain of the ground surface.

Jan 1, 1986

By Manuel Gomez

This report presents prediction equations for eleven factors indicative of metallurgical coal quality which have been developed from data obtainable during exploration. Five coke strength parameters and six carbonization product yields have been predicted for coking coals having volatile matter contents in the range 16.3 to 42.1 percent, dry basis. The prediction models developed contain information from the proximate and ultimate analyses, the size consist, and the petrographic composition of coking coals carbonized in BM-AGA retorts at 800°, 900°, and 1,000°C. The equations reported have been evaluated with independent data derived from the 900°C carbonization of 33 binary blends. Present results show that metallurgical coal quality can be predicted ahead of mining. Capability to forecast coal quality is useful in mine planning and should provide basic information for optimization of blending and crushing techniques, leading to the production of uniform coke.

Jan 1, 1968

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 P D. Katsabanis

"This chapter describes the principles for the derivation of the equations for a detonation wave.. Theimportance of the equation of state for the detonation products is demonstrated and commonly used equations of state are discussed. Furthermore a brief introduction to the TIGER code is presented."

Jan 1, 1992

By P D. Katsabanis

This chapter describes the principles for the derivation of the equations for a detonation wave. The importance of the equation of state for the detonation products is demonstrated and commonly used equations of state are discussed. Furthermore a brief introduction to the TIGER code is presented.

Jan 1, 1991

By A. Ersoy, M. D. Waller

The principal factors which require consideration in predicting drilling rates are the bit-type, the bit operating parameters and the characteristics of the penetrated rock. A single index is not a sufficient basis for predicting performance. A variety of rock types were drilled in the laboratory with polycrystalline diamond compact (PDC) and impregnated diamond core bits using a fully instrumented drilling rig at different rotational speeds and with a range of weights on the bit. Quantitative determinations of a wide range of textural, mechanical and intact rock properties were also made. Multi-variable linear regression analysis was then used to develop predictive models of rates of penetration from the operating and rock property data. The models have been verified by statistical tests. The analysis indicated that the models for the pin and hybrid PDC bits have potential for practical application. However, although the model for the impregnated diamond bit appears to be reasonable from a purely statistical point of view, it may not be satisfactory for drilling uses as it is based on two measures of rock hardness alone. The application of multiple regression analysis to PDC drilling performance is novel and the technique shows promise for the prediction of rock drillability with PDC bits. The ability of the technique to provide a mathematical characterisation of the performance of new drill bits in specific rocks may prove to be of value to drill manufacturers and users

Aug 1, 1995

By Peter M. Solozhenkin

Considering the main idea of the paper, namely that the interaction energy of reagents serves as a criterion used for their selection, as well as due to their insufficient study, the authors have therefore considered studying the aspects of computer modelling and molecular dynamics of largely used collectors for the flotation of nonferrous and precious metal ores. Three-dimensional molecular models for sulphydric reagents have been created, studying as well the distribution of the partial charges on their atoms. It has been shown that the value of the partial charge on the phosphorus atom in diethyldithiophosphinate and diethylmonothiophosphinate is high positive. The value of the partial charge of the sulphur atom is negative, strengthening its bond with the metal cations from the mineral surface. The molecular orbitals for the sulphydric reagents have been created determining as well the energy of their level. The computer modelling key parameters have therefore been defined. The new reagents have been tested for gold, copper and rhenium ore flotation. Gold recovery has increased with 4.2 - 4.7 %, copper recovery with 3.3 % and rhenium recovery with 15.5 %. A number of new flotation reagents have been recommended, such as: diethyldithiophosphate, (C2H5)2NCH2CH2OC(S)SNa, (C4H9NH)2P (S)SNa and also (C2H5)2P(S)ONa and (C2H5)2 P(O)S Na. Keywords: flotation, molecular modeling, design, orbital?s

Sep 1, 2012

By Haile Manteqi

In longwall coal mines, estimation of roof strata condition, sequence of loading, and supporting requirements are of a high degree of importance, and they are directly related to production and safety. Also, a prediction of the initial caving distance is rather complicated to calculate, because there are many parameters that effect caving process?roof and floor strata conditions, thickness of immediate roof, depth of cover, excavation geometry, and magnitude, and direction of principal stresses. This paper presents the results of 3D numerical modeling of the initial caving mechanism using the finite difference code FLAC3D at the E1 longwall panel of the Parvade 1 underground mine located in the Tabas area in the central part of Iran. The initial caving distance obtained was 10.4 m. Also, the results of numerical modeling have been compared to the analytical methods, such as Peng?s method. The results show good agreement with each other.

Jan 1, 2012

By A. Jahedsaravani, M. Massinaei, M. Zarie

Deep learning is a subset of machine learning that uses artificial neural networks for extracting high-level features from image data. In the present study, a soft sensor is proposed for the prediction of the flotation performance through froth features generated by the use of pre-trained convolutional neural networks. Several state-of-the-art convolutional neural networks (AlexNet, GoogLeNet, VGGNet, ResNet, and SqueezeNet) pre-trained on the ImageNet database are used to predict the metallurgical performance of two flotation systems. The first case study is a batch copper flotation system video-captured over a wide range of process conditions. The second case study is an industrial coal flotation column equipped with a continuous video recording system. The pre-trained networks are used to extract features from the froth images, and these features are subsequently used to predict the flotation conditions and performance. The prediction results by the pre-trained algorithms were compared with the traditional image processing algorithms. This demonstrates the ability of the pre-trained structures to generalize to images outside the ImageNet database. GoogLeNet outperforms other network architectures and provides more accurate predictions of the flotation process behavior and performance.

May 5, 2023

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 Charles S. Robinson

INTRODUCTION Geology, the science of the earth, is the fundamental science in the construction of a tunnel. The approximate site of a tunnel is determined by its purpose. The geology of the tunnel site will determine the cost--or feasibility of a tunnel--the specific alignment to accomplish the purpose of the tunnel, the design of the tunnel (within the limits of the purpose of the tunnel), and the methods of construction. The more accurately the geology of a proposed tunnel can be depicted, the more accurately can the cost of a tunnel be estimated. The factors that should be defined for tunnel design and construction are the physical characteristics of the material in which the tunnel is to be constructed. The physical characteristics of the material are determined by the genesis of the material, and subsequent geologic processes that have affected the material. The geologic materials in which tunnels are constructed can be broadly classified as unconsolidated and consolidated. The unconsolidated materials include chiefly deposits of recent geologic time that occur near the surface. Because these deposits occur near the surface, and tunnels constructed in them will be at shallow depth, methods of physical exploration such as geophysical methods, trenching, and drilling will give more data at relatively low cost--therefore the physical exploration is generally, or should be, quite extensive--and the

Jan 1, 1997

By R. K. Sinha, B. S. Choudhary, Desh Deepak, A. K. Mishra, Hemant Agrawal, Shankar Kumar

There are several methods (empirical, statistical, and machine learning tools) to calculate blast-induced ground vibration. Still, due to complications in the blasting procedure, under varying blasting loads and strata conditions, it is not easy to predict and simulate blast vibration precisely. Therefore, a study was conducted to simulate the field blast data in Ansys software using explicit dynamics. For this study, monitoring of ground vibration for 20 single hole blasts was carried out. The density of emulsion explosives was in the range of 0.9 to 1.15 g/cc. In the laboratory, rock properties were determined from the rock sample collected from the mine site before blasting. The in-hole velocity of detonation (VoD) and the density of the emulsion explosive were also determined. These parameters were used for numerical analysis to know the ground vibrations at specified points. The results of ground vibration predicted by the model are validated using field data.

By R. K. Sinha, B. S. Choudhary, Desh Deepak, A. K. Mishra, Hemant Agrawal, Shankar Kumar

There are several methods (empirical, statistical, and machine learning tools) to calculate blast-induced ground vibration. Still, due to complications in the blasting procedure, under varying blasting loads and strata conditions, it is not easy to predict and simulate blast vibration precisely. Therefore, a study was conducted to simulate the field blast data in Ansys software using explicit dynamics. For this study, monitoring of ground vibration for 20 single hole blasts was carried out. The density of emulsion explosives was in the range of 0.9 to 1.15 g/cc. In the laboratory, rock properties were determined from the rock sample collected from the mine site before blasting. The in-hole velocity of detonation (VoD) and the density of the emulsion explosive were also determined. These parameters were used for numerical analysis to know the ground vibrations at specified points. The results of ground vibration predicted by the model are validated using field data.

By R. K. Sinha, B. S. Choudhary, Desh Deepak, A. K. Mishra, Hemant Agrawal, Shankar Kumar

Despite several methods (empirical, statistical and machine-learning tools) to calculate blast-induced ground vibration, it is not easy to predict and simulate blast vibration precisely under varying blasting loads and strata conditions due to complications in the blasting procedure. In this study, field blast data were simulated in Ansys software using explicit dynamics, and ground vibrations for 20 single-hole blasts were monitored. The densities of emulsion explosives were in the range of 0.9 to 1.15 g/cm3. In the laboratory, rock properties were determined from rock samples collected from the mine site before blasting. The in-hole velocity of detonation (VoD) and density of the emulsion explosive were also determined and used in numerical analysis to know the ground vibrations at specific points. The results of ground vibrations predicted by the model were validated using field data.

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 S. A. Suhler

The detection of hazardous geological anomalies through remote sensing techniques is the subject of current research efforts sponsored by the U.S. Bureau of Mines. In this review, hazardous geological anomalies are discussed with respect to the "view" presented along with potential operational concepts for each technique. The design and development of a borehole radar is described with emphasis on the potential range and resolution capability of the system under realistic underground conditions. Results of field tests at two coal mines and at a hard rock future subway location are presented.

Jan 1, 1978

By B. Misra, B. S: Sastry, Kollu S. Rao

"This paper reports the results of a finite element study of the geothermal heatflow into dry mine airways. For isotropic and unsteady state conditions the heatflow into mine airways is studied for a range of surface heat transfer coefficients between rock and air, and age of the airway. Dimensionless temperature gradient values are presented in tables for different values of Boit and Fourier numbers and the results are compared with Starfield tables and Gibson algorithm. It is found that Starfield tables have consistently over-predicted the G values with errors ranging from 2% to 10%. The differences between results obtained from the finite element study and the G values calculated from Gibson's approximation method are mapped. The small error values over a large range of Fourier and Biot numbers confirm the suitability of Gibson's algorithm to rapidly calculate G values for estimating the heat transfer from surrounding rock to mine air.IntroductionIn many underground mines heat is a major problem, and the provision of acceptable working conditions requires considerable expenditure on ventilation systems. The rational design and operation of these systems depend upon an understanding of the various sources of heat in the mine. The natural source, i.e. geothermal heat, contributes up to 80% of total heat added to mine air and it is difficult to analyze and predict the heat owing to a number of influencing variables. The problem of geothermal heat flow has been studied by many investigators (Goch, 1940; Starfield, 1966; Hemp, 1987; Amano et al., 1982; McPherson, 1986).The primary concern of this paper is to develop a better ready reference dimensionless transient temperature table for estimating heatflow at any stage of mine airway life."

Jan 1, 1994