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By Yuanbo Zhang, Helei Zhang, Heng Yu, Guanghui Li, Zhengwei Yu, Tao Jiang

"Composite agglomeration process (CAP) is an innovative method for preparing blast furnace burden. For CAP, the classified raw materials of pelletizing feeds and matrix feeds are mixed, charged and sintered. The characteristics of these two kinds of feeds obviously affect the permeability of per-ignition bed, as well as the sinter productivity and quality. In this study, the Ergun equation is proposed to predict the pressure drop of CAP bed using the particle size distribution. The calculation process indicates that the Dv and the Em are the two tuning parameters. The results show that there is a gap between the calculated values by Ergun equation and the measured results by pressure drop testing facility. Eliminated this error by modified the Ergun equation and then validated it through experimental studies using simulated CAP mix and test facility. Therefore, the modified Ergun equation can be used to predict the permeability of CAP bed.IntroductionThe sintering process is one of predominant agglomeration processes for preparing ironmaking burden from iron-bearing materials. Sinter accounts for 70-80% of the blast furnace burden in China and the continuous improvement of sinter quality provides a guarantee to anterograde production of blast furnace. Sinter productivity and quality are strongly related to the permeability of the bed during sintering, which is dependent on the structure of the bed before ignition in the early stage [l]. The size distribution, the shape of granules and the bed voidage are the primary affecting factors to pre-ignition permeability."

Jan 1, 2013

By Jie Long, Zijie Liu, Pu Liu, Bo Li, Menghua Li, Qiang Wu

During coal mine operations, roadways may be located close to faults. When designing these roadways, it is important to determine the width of the rock mass between a roadway and a fault area to prevent water inrush. In this paper, the Xintian Coal Mine in the northern Guizhou Province of China is selected as a typical case. Through numerical simulation based on orthogonal tests, range analysis, and multiple linear regression (MLR) analysis, the process of water inrush from faults in excavation roadways is studied. The results show that the influencing factors of the safe width of a rock mass preventing water inrush (RMPWI) can be ranked according to the degree of influence from large to small as follows: the hydraulic pressure of the fault, the surrounding rock grade, the overburden depth of the roadway, the cross-section height, and the dip angle of the fault. Among them, the dip angle of the fault, the cross-section height, and the surrounding rock grade are negatively correlated with the safe width, while hydraulic pressure of fault and overburden depth of roadway are positively correlated with safety width. The predicted value for the safe width based on MLR is greater than the measured value of the width of the RMPWI when water inrush occurs, but less than the calculated value based on the empirical formula in the standard, which proves the accuracy and practicability of the prediction method. This research provides a certain basis and reference for the prevention and control of water inrushes in mines.

Jul 5, 2023

By M R. Asef

Although generation of environmentally harmful hydrogen sulfide is considered to be related to sour gas fields, sweet gas reservoirs and waste fluids, travertine springs and geothermal fields may also produce acid gas (H2S and CO2) under certain conditions. The potential parameters influencing such a possibility need to be fully investigated to evaluate the extent of the consequences and predict hydrogen sulfide generation accordingly. Reports on hydrogen sulfide production at different regions and fields were gathered worldwide for the cases when some of them did not have such a problem previously. In order to inspect different aspects of these case studies, some other regions with no hydrogen sulfide content were selected as control. In all cases water samples were taken carefully for chemical analysis in the laboratory. Besides, mineral compositions were characterised in some cases for better evaluation. In order to give a thorough prospect of hydrogen sulfide production, a geochemical model was prepared. In situ engineering geological conditions, especially pressure and temperature, were assigned in the model to investigate the possibility of H2S generation using PHREEQC software. The results of modelling revealed that although many similarities existed between mineral compositions of the cases, certain formations were particularly prone to hydrogen sulfide generation. For better evaluation, important exchangeable cation ratios such as potassium/sodium, calcium/magnesium and ion proportions like sulfate and chloride were calculated as trends of the formations. As expected, the model could successfully monitor a higher ratio of SO42- and Cl- in potential H2S generator formations. Wide variation in percentage of HCO3- was considered as a secondary observatory parameter for better estimation. In addition, it was noticed that higher anion content created an environment ready to absorb any cations and this makes H2S generation easier. Finally, using correlations between predictors and estimators for low depth and deep samples defined the degree of effectiveness for every sample.

Sep 26, 2011

By J. A. Procarione, M. K. McCarter, Bradley C. Paul

A numerical technique is described which can be used to model the quantity and distribution of air flow through broken rock. The method can also describe gas concentration and temperature distribution. A computer code implementing the numerical approach was developed to assist in determining the feasibility of a proposed modified in-situ leaching method for extracting copper from sulfide porphyry deposits. This mining method requires air to be forced through cells of rubblized ore. The flow serves to supply oxygen for the leaching reactions and to dissipate heat that would other-wise build due to the exothermic reactions. The method substitutes the Carman equation into the Laplace equation. The solution of the resulting non-linear formulation is done on a finite difference grid using SOR with iteration improvement of coefficients. This procedure yields the required air flow pattern and pressure drop. An equation for advection with absorption is then solved over the same grid using explicit schemes to yield oxygen concentration. Finally, a similar technique is applied to the convective heat transfer formula to yield the temperature profile. The model is potentially applicable to such mining problems as the prediction of leakage through caved ground, the prediction of methane concentration in gobbed ground, and the prediction of heat build-up in caved workings.

Jan 1, 1989

By E. Anelli

Based on experimental continuous cooling transformation (CCT) diagrams, an artificial neural network has been trained to predict the amount of microsturctural constituents and hardness resulting from and controlled cooling at rates from 150 to 0.015 K/s. It can be applied to quenching and normalizing processes of low-alloy steels with 0.05-0.30 C% and 0.4-2.0% Mn -with possible microalloying additions. Examples of the good predictive capabilities about 15 Vickers standard deviation for hardness and a few percent for volume fraction of phases) are reported' Keywords: Austenite decomposition, low. And medium-carbon steels, artificial neural networks

Jan 1, 2003

By Emad Farouz, Ehab S. Shatnawi

"The increasing demand for small deformations and high-capacity drilled shafts without enlarging drilledshaft diameters has motivated the development and increasing use of a base grouting (BG) technique. This technique has been demonstrated to improve drilled-shaft capacity, especially for shafts tipped into loose cohesionless soils. Nevertheless, there remains considerable uncertainty in predicting the performance of base-grouted shafts, particularly for shafts tipped into cohesive soils. To date, there are only two documented design methods for estimating the axial geotechnical resistance of base-grouted shafts: Tip Capacity Multiplier (TCM) and Axial Capacity Multiplier (ACM) methods. A comprehensive test program was carried out during the design phase of the Wisconsin Zoo Interchange project to help optimize the flyover ramp’s foundation design. The test program included installing and testing one base grouted shaft and one ungrouted shaft at two sites with different ground conditions. Based on test results, it was concluded that prediction of the TCM method is well correlated with the measured values for both cohesive and granular soils; however, both methods tend to underestimate the axial resistance. Results also highlighted the importance of the base-grouting criteria in taking full advantage of the base grouting.INTRODUCTIONBase-grouted drilled shafts (BGDS), also known as post-grouted drilled shafts, consist of conventionally installed drilled shafts that contain access grout tubes placed within the shaft during construction. After installing the drilled shaft and achieving the pre-established concrete strength, grout is injected at the shaft tip through the access grout tubes to improve soil behavior around the drilled-shaft base. The tip grout injection improves the overall shaft capacity and reduces settlement through Densifying the in situ soils, compressing any debris left by the drilling process, preloading the soil beneath the tip to mobilize the shaft base resistance within service limits, increasing the tip area, and increasing the side resistance in the lower portion of the shaft."

Jan 1, 2016

By T. G. Sitharam, P. B. Choudhury

Prediction of ground vibration (peak particle velocity, PPV) and frequency is an important task in geoscience. Till date, many empirical equations are derived from conducting trial blasts in the mines, to arrive at attenuation predictors. These predictors are usually site dependant and hold good for one particular type of rock/strata. These predictors cannot be used for geologically different rocks/strata. This paper presents the application of support vector machine (SVM) model, for predicting blast induced ground vibration and frequency, using a one comprehensive model for three different types of rock. Inputs to the SVM model formulation involve twenty one parameters consisting of geotechnical properties of the rock mass, blast design geometry and explosive properties, and the output of the formulated model is peak particle velocity and its associated frequency. The data has been acquired from eight limestone mine, five coal mine and two manganese mines. The comprehensive SVM model is formulated using 400 datasets and tested with 143 datasets. The performance indicators to the model not only justify its formulation but also the advantages it has over site specific predictor models. The SVM model not only predicts PPV, with higher correlation coefficients as compared to predictor equations, but also the associated frequency.

Jan 1, 2010

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 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 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 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 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 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