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By M. P. Roy, P. K. Singh, A. K. Mishra, Ashish K. Vishwakarma, Vivek K. Himanshu

Ground vibration is one of the major hazards produced by rock-blasting operation. The accurate prediction of vibration is necessary for designing controlled blasting parameters. The existing vibration predictors consider maximum explosive charge weight per delay and distance as the parameters responsible for ground vibration. These predictors are based on the assumption that the geometrical parameters of the blast will be constant for a site. However, the mining sites with bigger production targets have varying geometrical parameters to suit the excavator utility. Accordingly, the other blast design parameters will also have an impact on ground vibration intensity. A principal component analysis is a dimension reduction technique. This technique along with multivariate logarithmic regression has been used in this paper to predict the ground vibration. The technique has classified the blast design parameters into four principal components. The regression with the scores from these principal components has been carried out. The evaluation of the model performance of predictors along with the existing empirical predictors has been carried out using R2 and RMSE values. The evaluation suggests that the predictor with logarithmic regression followed by principal component analysis gives better performance with respect to the existing empirical predictors.

Jul 30, 2022

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 H Khoshrou, A Siamaki

Blast designs can have productive and non-productive impacts on downstream stages, mine productivity and operating costs. On the other hand, ground vibration, fragmentation, and back break caused by blasting impose damage and financial penalties and which must be controlled by blast design. One of the significant variables in blast design is the burden. In this study, the potentials of artificial neural network are investigated in prediction of burden in the Sungun copper open-pit mine. Input data were assembled through 18 blasting blocks according to different levels and experimental geomechanical investigation. To construct the model blastability index, uniaxial compression strength, hole diameter, specific weight of rock, rock quality designation and cohesion strength are taken as input parameters, whereas, burden is considered as an output parameter. Mean square error was used as the performance function and back propagation algorithm as the training function, containing four hidden layers and 14 data sets. Four sets of data were used to make sure that correct training had been carried out. This produced the coefficient correlation of 0.662.

Sep 26, 2011

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 R. H. Mullennex

Application of depositional analysis concepts is becoming an ever-increasingly more important and more useable tool in exploration and development of coals in the Appalachian basin. Over the past decade, a rather large number of studies, papers, and publications have addressed various aspects of depositional environments of coals and, to some extent, applications to development. As would be expected as regards a subject so complex as Pennsylvanian sedimentation in the Appalachian basin, certain academic studies have produced conclusions at variance in some aspects to those of other studies. Overall, however, there has been a building- block progression and general refinement with time of understanding of the depositional settings and other factors controlling Appalachian coal distribution, quality, and other minability parameters. Most attempts to explain coal seam characteristics have revolved around a basic deltaic model. Some have attributed certain seam attributes to upper delta plain deposition, other attributes to transitional-lower delta plain settings, and yet others to lower delta plain environments, and so on. While these approaches have provided valuable insight into some general coal characteristics, they are somewhat incomplete and are, in a sense, too broad for specific mine-scale applications. Further, it is apparent that in order for widespread peat accumulation to occur, there must be a drastic decrease in the energy of the depositional system and amount of sediment being brought in, compared to the active deltaic and coastal processes responsible for deposition of the large volume of clastic sediments that dominate the Pennsylvanian system of the Appalachians. Consideration of this fact implies that peats (coals) may not necessarily reflect depositional settings that are directly coincident with those associated with adjacent rocks. Cecil and Englund (1985) address this point, and quite correctly state that "the primary controls on major stages of peat formation are allocyclic processes involving paleoclimate, eustatic changes in sea level, and tectonics." While this statement is inarguable, it does not negate the importance and usefulness of depositional analysis in predicting reserve characteristics that may impact mining and marketability.

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 Yukihito Sasaki

Sumitomo Metal Mining Co. Ltd. planned an expansion program for the Toyo smelter and refinery in order to increase the production capacity of electrolytic copper to 450,000 tpy in 2007. Regarding the flash smelting furnace, a drastic increase in the average concentrate smelting capacity from 2,300 tpd to 3,950 tpd was required to achieve the plan. It was necessary to examine the performance of the Sumitomo concentrate burner when the feed rate was considerably increased. The authors developed a mathematical model to describe the combustion phenomena in the Toyo flash smelting furnace. This model was developed incorporating the fluid flow, heat and mass transfer, and chemical reactions of the copper concentrate and ancillary fuel. The copper concentrate was considered to mainly comprise chalcopyrite (CuFeS2). The reaction of CuFeS2 was assumed to consist of two steps, namely, the decomposition of CuFeS2 and the oxidation of the resulting pyrrhotite (FeS) and sulfur (S). The combustion phenomena in the furnace at the increased feed rate were predicted using this model. It was found that the Sumitomo burner was capable of enhancing the smelting capacity. This is attributed to the wide dispersion of the concentrate particles caused by an increase in the particle mass and a long residence time in the reaction shaft; this is due to the low temperature of the reaction air. However nonuniformity of the reaction in the reaction shaft was enhanced with the increased feed rate. In order to improve the nonuniformity of the reaction, an increase in oil-burner oxygen and an enlargement of the diameter of the dispersing cone were useful. By combining the expertise of the Toyo smelter staff and the calculation results, the concentrate smelting capacity of the Toyo smelter has been stably increased to 3,600 tpd thus far, and further improvements of the smelting performance are still being carried out.

Jan 1, 2006

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 Kerry Burns

Contrary to active subsidence, which occurs concurrently with mining operations, or is completed within a few days following coal extraction, delayed subsidence may take many years to appear at the surface after coal mines are abandoned. There are two principal morphological types of delayed subsidence: troughs, which are shallow depressions, and sinks, which are steep-sided crown pits. Both types are damaging to surface structures, and a variety of methods have been introduced to deal with the problem, ranging from subsidence insurance to site restitution. In planning insurance or restitution measures, a predictive model is of value in estimating the magnitude of the problem and the size of long-term budgetary commitments. Only one model is known, which was developed for the Bureau of Mines by GAI Consultants of Monroeville (l,2,3). The GAI model is presented in qualitative terms. This report develops a formal basis for the model and tests a numerical implementation on one of the best-described study areas, Allleqheny County in Pennsylvania.

Jan 1, 1982

By A. B. Holland-Batt

Deposition velocities play an important role in many fields of engineering and an impressive range of measured data has accumulated in the literature. Numerous workers have addressed the problems that are associated with the prediction of deposition velocity because of its particular relevance to the design of pipelines and pumping stations. However, despite this extensive effort, the calculation of friction heads still requires reference to experimentally based graphs to determine Durand factors and there is still scope for improvement in the prediction of the deposition velocity at different solids concentrations. Equations to characterise the relationship between the Durand factor and the volume concentrations of solids in the slurry are presented. A correlation for the prediction of the deposition velocity is also developed and tested against some of the classical experimental data. The application of predicted values of deposition velocity in assessing the potential for the sanding-up of spiral separators is then described and a case study is presented.

Jan 12, 1992

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 Ernesto Maldonado, Zach Agioutantis, Jesus Romero

Reliable prediction of dynamic deformations is important when planning to undermine important structures that cannot tolerate large relative deformations and or large horizontal strains. This paper presents examples of dynamic deformation profiles that include subsidence, horizontal displacements, and horizontal strain for a number of points over a retreating longwall panel in the eastern United States. The prediction points are located at different distances from the excavation rib and therefore present a different response in terms of dynamic movements. The formulation is based on the influence function method as implemented in the Surface Deformation Prediction System (SDPS). Results show that the subsidence development curve may be reliably predicted for surface points in the middle of the panel. However, in cases where points may be affected by the magnitude of the edge effect offset, subsidence predictions may be very conservative, that is, higher than actual movements.

Jul 1, 2023

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 C. M. Chen

Friction stir welding (FSW) is a pure solid-state joining process, which has been widely used in joining aluminum alloys with improved properties. This paper describes a three-dimensional simulation of FSW process, running the ANSYS package of finite element analysis to study the evolutional stress in the butt-welding of aluminum alloy 6061-T6. The model incorporates the mechanical effect of the tool and thermomechanical process of the welded material. The heat source involves the friction between the material and the probe and the shoulder. Thermal history and the evolution of longitudinal, lateral, and vertical stress in the friction stirred weld are simulated. The relation between the calculated residual stresses of the weld and the process parameters such as tool traverse speed is presented. Keywords: Fiction Stir Welding, Finite Element Analysis, Thermomechanical Process, Evolutional Stress, Residual Stress.

Jan 1, 2003

By C. Mick Lownds, Dale S. Preece, Ali Bhuiyan

FDM (Fracture Density Model) is a three-dimensional mechanistic model of blast induced rock fragmentation. FDM uses several computational mechanics algorithms to simulate the effect of blasting in different rock types. Earlier, FDM was successfully exercised to simulate 29 small scale shots from the United States Bureau of Mines (USBM), and 6 full-scale bench blasts at the Bararp dimensional stone quarry in Sweden. Excellent agreement was obtained for those shots, and the results were documented in earlier publications. One of the drawbacks of previous ver- sions of FDM was its inability to predict the fines, specifically in Bararp quarry simulations. Ac- curate predictions of fines can be very useful in reducing energy consumptions during down- stream comminution processes and improve the mine-mill operation efficiencies. In this paper, we propose a newer algorithm that can predict the fines as well as the coarse fragments in Bararp with reasonable accuracy. The model was also applied to an open-pit Copper mine with heavily jointed rocks, and it produced very good fragmentation predictions for the full range of fragment sizes. Comparisons with the sieved fragmentation data (for both Bararp stone quarry and the open- pit Copper mines) show great potential for this updated version of FDM in modeling the entire range of fragment size distributions in mining and quarrying applications.

Feb 6, 2023

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 R. H. Snow

Although industrial size reduction methods have an energy efficiency of only about 1 percent, methods of size reduction have not changed much for many years. One reason for slow progress has been the oversimple viewpoint that a single law should exist to relate size reduction to energy input. Modern simulation methods decompose the grinding process into a grinding rate function (selection function) and a breakage function. The breakage function is difficult to measure, and it usually requires tracers if it is determined from milling experiments. Prediction of breakage functions from basic principles is one objective of this paper. In this study we focus attention not on the gross energy input to the experiment, but on the spatial distribution of stress energy within the particle. We are led to this viewpoint by experimental observations of a few previous investigators (Bergstrom2, Rumpf3, Axelson4) and our own observations. Oka and Hiramatsu recently used their calculations of stress within particles for prediction of breakage, but again they tried to correlate the size of the fragments with the total stress energy, rather than the approach we propose. We assume that the stress energy is stored in the interior of the particle as the load is increased, until the particle breaks. We assume that each element of the particle breaks into fragments of a mean size that depends on the locally-stored stress energy. The size distribution of fragments is the computed from maps of the stress-

Jan 1, 1972