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By V. E. Dementiev, V. I. Kulikov, G. I. Voiloshnikov, Yu. O. Fedorov

"The report presents the summary of the JSC Irgiredmet’s activities in the field of preconcentration of ores. As of 2018, the Institute has almost 40-years’ experience in this area. Over the years, Irgiredmet has done a lot of work – from development to implementation of new technologies of ore piece sorting and concentration based on X-ray radiometric separation (XRRS). INTRODUCTION Preconcentration has been a challenging issue of the mining industry over the last decades. The implementation of this technology can significantly increase mining efficiency. The main application of preconcentration is improvement of mined ores quality, however new and more complex issues have arisen with the evolution of the technology. Irgiredmet has started to develop an efficient preconcentration technology for gold-bearing and rare-metal ores 40 years ago. The X-ray radiometric method widely used at that date as a method of elements determination in geology and geophysics become the ground for this work (1). Since that time, the Irgiredmet Institute has developed and significantly improved the technology of piece ore sorting, or XRRS (2-5), that is currently also known as the X-ray fluorescence method. The progress of the XRRS development achieved by Irgiredmet in cooperation with Rados LLC, Tekhnoros LLC (Krasnoyarsk), Rados-Service LLC and CJSC Tekhnogen (Ekaterinburg) has proved efficiency and applicability of the XRRS technology for processing a wide range of minerals and solving of various technological problems (7-9) compared to other radiometric methods (6). Furthermore, obtained results are supported by numerous studies, trials and implementations. The significance of ore preconcentration for greenfield and brownfield projects determined the establishing a new subdivision of Irgiredmet, the XRRS Technology Center (XRRS TC), that has provided the Institute with a completed range of processing technologies, from preconcentration to producing final products. Over the past few years, the XRRS Technology Center has carried out studies and testing of a numerous (more than 100) projects, mines and deposits of gold-bearing ores, rare metal ores (Be, Ta, Nb, W, Mo), base metal ores (Cu, Sb, Zn, Pb), ferrous metal ores (Fe, Ti, Cr), rough diamonds and coal. The XRRS Technology Center performs various specific studies and testing not only in Russia, but as well as in Kazakhstan, Georgia and Mongolia. Mines and companies from Chile, India, China, Iran and other countries also take an active interest in the XRRS technology."

Jan 1, 2018

By Nn Li

Energy consumption in commercial buildings has been increasing rapidly in the past decade. The knowledge of future energy consumption can bring significant value to commercial building energy management. For example, prediction of energy consumption decomposition helps analyze the energy consumption patterns and efficiencies as well as waste, and identify the prime targets for energy conservation. Moreover, prediction of temporal energy consumption enables building managers to plan out the energy usage over time, shift energy usage to off-peak periods, and make more effective energy purchase plans. This paper proposes a novel model for predicting heating, ventilation and air conditioning (HVAC) energy consumption in commercial buildings. The model simulates energy behaviors of HVAC systems in commercial buildings, and interacts with a multiagent systems (MAS) based framework for energy consumption prediction. Prediction is done on a daily, weekly and monthly basis. Ground truth energy consumption data is collected from a test bed office building over 267 consecutive days, and is compared to predicted energy consumption for the same period. Results show that the prediction can match 92.6 to 98.2% of total HVAC energy consumption with coefficient of variation of the root mean square error (CV-RMSE) values of 7.8 to 22.2%. Ventilation energy consumption can be predicted at high accuracies (over 99%) and low variations (CV-RMSE values of 3.1 to 16.3%), while cooling energy consumption accounts for majority of inaccuracies and variations in total energy consumption prediction.

Aug 1, 2013

By K Jupp, T J. Howard

Cliffs Natural Resources Pty Ltd (CNR) operates iron ore mines in the Koolyanobbing region of Western Australia. Ore is mined from three locations, separated by many kilometres. The ore is stockpiled at these locations, according to an in-house ore classification system (based on grade and source) and then trucked to the crushing and screening plant at Koolyanobbing. Lump and fines products are railed to Esperance for ship loading and export to Asian customers. CNR prides itself on the relatively low inter-shipment grade variability of the products. The Koolyanobbing crusher is fed using a daily blend plan, generated to maintain lump and fines product grades within acceptable tolerance ranges around targets. Achieving low variability requires predicting lump and fines grades as accurately as practical from the estimated head grades of the ROM ores potentially going into the blend. The grade prediction model may be either a direct prediction of crushed lump and fines grades and lump percentage, or be split into two stages: the bias between blasthole estimated head grade and crusher head grade and then the lump-fines algorithm for splitting the head grade between lump and fines products. The lump-fines algorithm comprises the percentage of lump and the difference between the lump and fines grades. We describe a weighted least squares (WLS) regression model for predicting crusher grades and lump proportion from the estimated head grade for Fe, P, SiO2, Al2O3, Mn and S. The method is applied to CNR production data, where the regression model explains approximately 60 per cent of the variance in the crushed ore grade, for both lump and fines. A further small but significant improvement in prediction can be achieved by including the ore classification data in the model. The regression errors exhibit strong positive serial correlation, indicating trends in grade error across multiple blend records. To compensate for the longer-term error, an exponentially smoothed model was developed and applied to the daily grade blend errors. This gave an increase in the longer-term variance explained and therefore an improvement in grade prediction.

Jan 1, 2009

By S. Makni, A. Faucher, F. Robichaud, A. Bouajila

"Optimizing the ball charge in a grinding mill may be needed to maximise throughput or alternatively, to achieve proper product size in more challenging situations. Efforts to optimise the ball charge however are essentially empirical and suffer from the lack of appropriate, accessible and reliable tools. To address these limitations, a new model-based technology was developed that relies on 3D Discrete Element Method and population balance techniques: it takes on the form of a simulator that aims to significantly decrease the time required to optimise the size distribution and the grinding media load within a ball mill. This paper summarizes the research work related to the development of this simulator. The calibration of the different constituting sub-models will be highlighted. The successful use of the simulator to predict the effect of ball make-up on the grinding product size distribution in one plant is also reported.INTRODUCTION Adjusting the characteristics of the grinding media charge in grinding mills holds significant potential for optimisation of mill performance. For example, properly adjusting the ball size distribution in a ball mill can help achieving specified targets for final product size distribution and/or throughput capacity. However, several problems appear when reviewing the process and the available tools to optimise ball mill load: • The current empirical simulation tools are lacking with regard to the ability to predict the performance of grinding when changes to mill ball make-up are made; • Generally, these tools estimate the top size of the charge so it is difficult to predict the effect of mixed ball make-up; • As the quality of prediction of these tools is low, the operators try to optimise the ball charge by a ""trial and error"" method and proceeding with conservative changes. The influence of these changes on grinding performance is often less than the measurement precision and the improvements then remain imperceptible; • A change in ball make-up may require an average of about 6 months waiting period before reaching the stationary state of mill ball load. This exercise is due to be costly if applied change decreases the mill performance. In its effort towards the comminution process optimisation, COREM R&D portfolio had addressed the herein described opportunity during the last five years This paper describes the technology already developed for the optimisation of ball charge. It takes on the form of a simulator that aims to predict the evolution of the grinding media load, the grinding energy available in the ball mill and the final product size distribution. The simulator was first validated in a pilot scale ball mill and then applied in an industrial case."

Jan 1, 2012

By S. C. Suboleski

In a high risk venture such as mining where capital is committed and contracts are signed on the minimum of information, decisions are based primarily on production forecasts derived through consideration of such factors as management-labor relations, mining practice, variations in physical conditions and the equipment applied. Among these factors, the physical conditions offer the least opportunity for control and, due to the wide range of mining conditions that may be experienced, little effort has been made to develop objective methods for measuring their effects on mine out- put. The aim of this paper is to demonstrate a method for assessing these relationships that can be applied under a wide range of conditions both in new mines and in working sections where there is a need to determine the impact of proposed operational modifications. psing empirical data from active underground mines, a mathematical model was developed to derive a set of regression equations for predicting production as a function of mining conditions

Jan 1, 1980

By D. B. Mazzinghy, D. C. Rocha, H. B. Miller

"The use of ball mills for fine grinding is an inefficient process and has contributed to the increasing popularity of vertical stirred grinding mills in the minerals industry. Over the last decade, the performance and energy efficiency of stirred milling technology has become a preferred alternative to ball mills for fine and regrinding operations. The difficulty encountered in fine grinding is the increased resistance to comminute small particles when compared to coarse particles. Therefore, increased energy inputs are then necessary to raise the number of stress events in a mill to contribute to the comminution of fine particles. This work discusses the effect of operating conditions on the amount of fines produced and torque readings in a screw type batch laboratory vertical stirred mill. A time-based population balance model (PBM) was used to empirically analyze the performance of a vertical mill and to calculate mill breakage parameters for the different operating conditions tested. The results indicate the possibility of applying population balance model to the vertical stirred mill to predict product size distribution with acceptable accuracy. The obtained breakage function shows that the main breakage mechanism in this vertical stirred mill is by attrition, and that the selection function changes with experimental conditions within the mill. Higher agitator velocities are also seen to promote an increase in the degree of attrition between grinding media hence particle selection and fines generation increase.INTRODUCTION Stirred milling technology has been firmly established in the last 20 years as superior to ball mills for fine and regrinding operations due to its superior energy efficiency (Jankovic, et al., 2006). Stirred mills are now commonly used in many sectors of the mining industry, though they have been used in other industries for many years (Stehr & Schwedes, 1983). This technology has proven to be more energy efficient with greater opportunities for future optimization in both fine and coarse grinding."

Jan 1, 2018

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 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 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 R. Froidevaux

Geostatistical estimation techniques were customized to enable forecast of production figures at the Silver Bell uranium mine (Uravan District). Surface drill hole data were used to provide a block model of kriged estimators of average uranium grades. The recoverable figures, such as ore-waste ratio and ore grade, are then deduced from regressive curves previously obtained from underground information and production data. Cross-validations of the entire model were performed and were found positive.

Jan 1, 1981

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. Myllykoski, J. Nylander, A. S. Korhonen, J. Larkiola

The coefficient of friction and the deformation resistance have been determined from the measured rolling parameters by applying the Bland-Ford-Ellis rolling force model and the artificial neural network model (ANN). The dependence of friction on the parameters such as reduction, rolling speed, front and back tensions, contact pressure and deformation resistance have been studied by the ANN model. Measured data of over 10 000 coils have been used in the training stage. Various dependencies have been examined and the results show that the friction coefficient does not depend much on the rolling speed. The reduction and deformation resistance seem to have the strongest effect on the friction coefficient. A friction model based on neural computing has been included into the existing rolling force model.

Jan 1, 1994

By Quin Dennis

Process Optimization ?What is it really? It is NOT ?a larger fan to increase draft through a process ?a larger pump on a wet circuit ?a wider conveyor belt for solid materials ?a larger feed elevator into or out of a process These relieve individual constraints ??bottlenecks??and allow operation to the next constraint in the process ?It is also NOT about automating the operator ?which captures consistency but is not continuous optimization

Nov 1, 2011

By Greg Partington, Darryl Thorburn, Charlene Wildman, Elisa Puccioni, Connie Payne, Campbell McKenzie

"Mineral prospectivity modelling of polymetallic nodule deposits has been completed over the Cook Islands Exclusive Economic Zone (CIEEZ) using the GIS based Weights of Evidence modelling technique. Polymetallic nodules, also known as manganese nodules, have been explored as a possible resource for a number of metals including cobalt since the early 1970s. Recent data on the nodule composition and abundance in the CIEEZ has led to a renewed interest in the prospectivity for manganese nodules in the region. The predictive modelling has used the most recently accepted mineral model for polymetallic deep-sea nodule deposition to identify factors that are most likely to map the presence of this type of mineralisation in the CIEEZ.Manganese nodules form on the deep seafloor as concretions formed by concentric layering of iron and manganese hydroxides around a core and they grow at a very slow rate, on the order of millimeters per million years. The available data for the CIEEZ indicates a greater abundance in the area of nodules formed by hydrogenetic processes, which are the result of slow precipitation of metallic components from seawater. The environment in which the nodules are most abundant is at depths between 4,000 m and 6,000 m in areas of low sedimentation rate. Hydrogenous nodules commonly grow on siliceous and pelagic clay sediment, they are less common on other types of sediment."

Sep 1, 2014

By M. Sadegh Safarzadeh, Stanley M. Howard

The two-dimensional predominance area (Kellogg) diagram (PAD) surfaces bounding the three-dimensional Cu-As-S-O system were constructed at 900 K. The computations employed gases As4O6(g), O2(g), and SO2(g) as the independent coordinate species to generate diagrams of As4O6(g) − O2(g),O2(g) − SO2(g), and As4O6(g) − SO2(g), while the third gas (As4O6, O2, or SO2) was fixed. The results indicate that there is no shared boundary between enargite (Cu3AsS4) and copper sulfate (CuSO4); however, at PO2 < 10−6 atm, PAs4O6 < 10−10 atm, and PSO2 > 10−4 atm, CuSO4 is the stable phase at 900 K. The chemical driving force for oxidation of intermediate phases between enargite and copper sulfate is substantial except for basic sulfate (CuO · CuSO4).

By M. Sadegh Safarzadeh, Stanley M. Howard

The two-dimensional predominance area (Kellogg) diagram (PAD) surfaces bounding the three-dimensional Cu-As-S-O system were constructed at 900 K. The computations employed gases As4O6(g), O2(g), and SO2(g) as the independent coordinate species to generate diagrams of As4O6(g) − O2(g),O2(g) − SO2(g), and As4O6(g) − SO2(g), while the third gas (As4O6, O2, or SO2) was fixed. The results indicate that there is no shared boundary between enargite (Cu3AsS4) and copper sulfate (CuSO4); however, at PO2 < 10−6 atm, PAs4O6 < 10−10 atm, and PSO2 > 10−4 atm, CuSO4 is the stable phase at 900 K. The chemical driving force for oxidation of intermediate phases between enargite and copper sulfate is substantial except for basic sulfate (CuO · CuSO4).

By David J. Kinneberg, Barbara E. Mangion, Arnold M. Savolainen

Analytical laboratories require a qualitative or semi-qualitative method of determining major and minor constituents in "unknown" samples to select optimal analytical techniques. This is exceedingly important in precious metal assay laboratories where the precision and accuracy requirements are exacting (routinely within 0.02%, absolute basis). This paper describes the use of an x-ray fluorescence spectrometer with a specially designed software package to select optimal analytical procedures and specify relevant analytical parameters. A wavelength dispersive XRF spectrometer is capable of quick and accurate analyses of properly prepared samples without extensive standardization. When coupled with a specially designed software package, this preliminary assay system is applicable to a wide variety of sample types including gold and silver bullion, karat gold and karat PGM alloys, high silver and high copper metallic samples as well as particulate samples of ores and sweeps. The system relieves the assayer of tedious calculations for silver inquartation and proofing, minimizes human error and standardizes selections over time. Most importantly, the system allows for independent verification of final assay results.

Jan 1, 1999

By Christopher Gammons

In developing countries throughout the world, gold ores are being processed by mercury amal-gamation, a technique long banned in the U.S. - unless a retort operation is used for mercury recovery - due to mercury toxicity and its effects on the environment. Amalgamation is a simple process that involves contacting a ground, slurried concentrate or ore with mercury in a slightly agitated vessel, usually for several hours, The amalgamated mercury is separated by gravity and then filtered through a fine cloth to collect the gold amalgam as a sponge, which is then fired to remove the final remnants of mercury and produce high quality gold. However, in Peru and other developing countries in South America and throughout the world, tailings are simply discarded into uncontrolled drainages and ponds and the sponge is fired in the open air. Clearly, in this case, environmental friendly and, to make matters worse, is typically conducted by family members of all ages without proper protection. Furthermore, the technique is inefficient, yielding approximately 50% gold recovery. For the past two years, faculty members from Montana Tech in Butte, MT, USA and the Universidad Nactonal del Altiplano in Puno, Peru have teamed to study the La Rinconada Mine Complex located in southern Peru approximately 100 kilometers north of Lake Titicaca and 25 kilometers west of Bolivia. The mining complex is over 5,000 meters above sea level and exists at the foot of a receding glacier in the Andes Mountains. A suite of soil and water samples collected in 2001 documented extensive Hg contamination in the Rinconada area [1]. The present paper summa¬rizes a follow-up investigation in July-2002, in which water samples were collected at numerous locations along the 200 km length of the Rio Ramis, from the Rinconada mine com¬plex to Lake Titicaca, In addition, we report new results of Hg analyses of fish from Lake Titi¬caca, The results of this study have relevance to safety and health concerns for the miners as well as people in downstream communities.

Jan 1, 2003

By L. J. Hoover

The objective of this study was to assess the health and environmental impacts of fluidized-bed combustion (FBC) of coal, specifically as applied to baseload generation of electrical energy by utilities. The study* was a short-term effort that based its analyses on information derived from the experience of the group or quickly obtained from the literature. The approach was to compare Atmospheric Fluidized-Bed Combustion (AFBC) and Pressurized Fluidized-Bed Combustion (PFBC) with two current technologies: low-sulfur coal combustion (LSC) and flue gas desulfurization (FGD) used with high-sulfur coals. A wet-limestone process was selected as the FGD technology. The impacts compared involved not only health and environment but also sociology, resource use, and dollar cost. Conditions for comparison were centered around a nominal date of 1988, when initial operation of commercial AFBC plants may occur. The PFBC has a later introductory date, a nominal 1995 (its impacts relative to other competitive technologies now in the R&D stages were not compared.)

Jan 1, 1978

By J. Payton

Public Service Company of Oklahoma began burning sub-bituminous coal in December, 1979. Initially PSO had a single source coal supply from Jacobs Ranch Mine, and in 1982 added deliveries from Clovis Point mine. Both are Powder River Basin (Wyoming) coal mines. In 1986 PSO began burning Oklahoma coal to meet Oklahoma&apos;s 10% native use law. PSO experienced random s lagging during certain blends of these coals. PSO installed a boiler performance system to help control the slagging problems from the various coal blends, to improve boiler efficiency, and increase total coal consumption.

Jan 1, 1990