Search Documents

By C. Özgen Karacan

Methane emissions from a longwall ventilation system are an important indicator of how much methane a particular mine is producing and how much air should be provided to keep the methane levels under statutory limits. Knowing the amount of ventilation methane emission is also important for environmental considerations and for identifying opportunities to capture and utilize the methane for energy production. Prediction of methane emissions before mining is difficult since it depends on a number of geological, geographical, and operational factors. This study proposes a principle component analysis (PCA) and artificial neural network (ANN)-based approach to predict the ventilation methane emission rates of U.S. longwall mines. Ventilation emission data obtained from 63 longwall mines in 10 states for the years between 1985 and 2005 were combined with corresponding coalbed properties, geographical information, and longwall operation parameters. The compiled database resulted in 17 parameters that potentially impacted emissions. PCA was used to determine those variables that most influenced ventilation emissions and were considered for further predictive modeling using ANN. Different combinations of variables in the data set and network structures were used for network training and testing to achieve minimum mean square errors and high correlations between measurements and predictions. The resultant ANN model using nine main input variables was superior to multilinear and second-order non-linear models for predicting the new data. The ANN model predicted methane emissions with high accuracy. It is concluded that the model can be used as a predictive tool since it includes those factors that influence longwall ventilation emission rates.

Building block cave operations involves significant commitments to capital and time before arriving at completion or full scale production. The focus of the mine planners is habitually to minimize the upfront capital and achieve target development rates and construction dates. However, management of the construction of block cave projects requires understanding of the strategic/tactical decisions that the project planners can take to increase the value of the project and cope with schedule risks. As block cave projects involve development of vertical and lateral access to the underground footprint and ore body, more attention to uncertainties is required as most of those projects need to confront delays leading to a decrease in value. The standard process of development and construction scheduling is often not planned with provisions to realise uncertainties in the construction phase. Uncertainties and risks such as poor ground conditions and equipment breakdowns are the primary reasons for schedule slippage. As a result most of these projects experience delays. In order to mitigate risk to the project schedule, we centre our attention on increasing the value of the project by spending more money upfront and improving the schedule rather than focus on minimizing the upfront capital. Scenario-based simulations along with project appraisal methods hold great promise to address those challenges and enable mine planners to make better decision and enhancing project value. This paper will present a hybrid simulation based approach to model the process of development and construction based on discrete event (DES) and continuous based simulations (CBS). Such simulations will be conducted for scheduling multiple development headings (Apex, undercut, extraction, and haulage levels). Two scenarios are utilized to investigate the impact of risks on schedule and how flexibility in construction can be incorporated to minimize delays: (1) The bench mark scenario is created based on actual data from an existing case study. (2) The flexible scenario is an alternative way to use primary production infrastructure (Ore Handling System) including conveyer drifts, conveyer belt, and a gyratory crusher in the construction process and that requires the system to be in place before starting lateral development in the footprint. As a result, a truck-load system versus a conveying system will be studied to observe the gain in construction speed and to estimate the premium cost for mucking rock from headings and drawbells and transporting it to surface. Such strategic flexibility would be part of the original budget to make the tactical flexibility available during construction. Continuous cash flow models are used to evaluate and compare the scenarios. This study is an example of how new techniques in planning can be used to support decision-making processes in block cave design.

Aug 1, 2013

By Lei Wang, Xiancong Zhao, Hongxu Li, Lifeng Zhang

Recovery of Fe from red mud has been studied using statistically designed experiments. The effects of three factors, namely: reduction temperature, reduction time and proportion of additive on recovery of Fe have been investigated. Experiments have been carried out using orthogonal central composite design and factorial design methods. A model has been obtained through variance analysis at 92.5% confidence level.

Jan 1, 2015

By Milind Chikhale, Yogesh Reja, Keshav Tyagi

"Using computer models for process design is a well-established practice in the mineral industry. In recent years, there has been emphasis on modeling of processing plant as a whole. This paper covers development of a model for iron ore processing plant. Basic purpose of this model is to use simulation for efficient plant design and help in minimizing risk at the very initial stage of project. Feed to the plant is Hematite iron ore from a deposit located in Eastern India. Major processes in plant include multi-stage crushing, screening, grinding, classification, gravity and magnetic separation. Models for different process equipment were developed using METSIM and Bruno simulation software. Customized black box models and known mathematical models were used for predicting behaviour of processes. Data needed was identified based on the model type. The required data was arranged as per project requirement and processed for development and validation of model. Equipment models were developed and validated on the basis of process design basis, theoretical and empirical data from technical references, and bench scale and pilot scale testwork results. Validated process circuits were assembled to simulate and represent the entire plant process. The result shows expected variation in plant output as a result of variation in the feed. Study concludes by discussing potential applications of the model in plant design."

Jan 1, 2014

By Autumn Fjeld

The filling and solidification of an industrial scale composite casting has been simulated to investigate the re-melting of the outer shell material during casting. Production of a composite requires a two-step casting process which includes centrifugal casting of a hard outer shell material and subsequent conventional ingot casting of a tough core material into the shell-mold assembly. During casting of the core, a thin layer of the shell material re-melts and mixes with the core material producing a bonding layer of intermediate composition. The present numerical model employs the volume of fluid method and an enthalpy-porosity technique to couple the filling of the core material and re-melting of the shell material. The interface between the two materials is tracked and can be used as a guide to examine the extent of melting and, to some degree, mixing of the two fluids and species diffusion.

Jan 1, 2008

By Venkata S. Buddhiraju

Pelletization of iron ores involves balling on a rotating disc to produce wet pellets and induration of wet pellets on a moving grate to produce fired pellets. The quality of pellets produced and the productivity of the pelletization process depend strongly on the characteristics of the feed to the pelletization disc, especially the particle size distribution and the moisture content. The upstream processes involved in the preparation of pelletization feed include grinding, thickening and filtration of the iron ore slurry. The focus of the present work is the closed circuit wet grinding of iron ores. The circuit consists of a primary ball mill, a regrind mill and a hydrocyclone. A population balance model was developed to predict the grinding kinetics and an empirical model was fitted for the separation of fine particles from the coarse particles in the hydrocyclone. Batch grinding kinetics experiments were performed on a laboratory scale ball mill to obtain the ore breakage parameters which were subsequently used for the simulation of the industrial mills. The models were customized for the industrial operations and the effects of different process variables like feed flow rate, water flow rate, etc., on the size distribution of product from the grinding circuit were studied. Additionally, different circuit configurations were simulated to determine operating conditions that could result in the desirable product particle size distribution. The results of simulation were in close agreement with plant observations and the new circuits explored through simulation have helped in identifying potential opportunities for process optimization and control

Sep 1, 2012

By H. Chaouki

The aim of this work is to simulate the forming process of a green anode. For this purpose, a nonlinear compressible viscoelastic constitutive law is presented. The concept of natural reference configuration is considered. Within an isothermal thermodynamic framework, a Helmholtz free energy is proposed to take into account the nonlinear compressible deformation process occurring between natural reference configuration and current configuration. A dissipation potential is introduced in order to characterize the irreversible aspect of compaction process. Thus, the constitutive law is formulated through two equations: 1) an expression of Cauchy stress tensor and 2) a differential equation characterizing the evolution of the natural reference configuration. Material parameters are assumed to be a function of the bulk density. This allows capturing the micro-mechanical phenomena within the chosen macroscopic approach. An experimental study based on compaction tests is carried out in order to characterize the mechanical behaviour of the anode paste. A user's material VUMAT subroutine for finite element dynamic explicit analysis has been developed and implemented in the ABAQUS commercial software. To evaluate the model predictive capability, numerical simulations of the compaction forming process of anode paste were performed. Simulation results show that the constitutive law predicts the experimental trends and gives interesting physical responses. This constitutes a first step toward making a benchmark with experimental results on the forming process of anode paste.

Jan 1, 2011

By Tad S. Golosinsk

Use of computers for hoist evaluation and design dates back to the early 1960's. Mine hoist production calculations, repetitive in nature, were computerized first. More elaborate modeling of hoist operations followed soon. Typical for this, early period are the models described by Touwen (1973), and by Albert and McIvor (1984). Apart from the simple hoist production calculations, the models were very complex, typically written in Fortran, and often required advanced computing facilities and expertise to run the simulation. The early models were strictly deterministic, with no consideration given to the random nature of hoisting operations. The effects of randomness of the hoisting process on hoist performance were often accounted for by introduction of the deterministic factors, most notably of an "utilization factor" related to the hoist production. The value of the latter was based on observations of actual hoist performance, and could vary in a wide range. For example Harvey (1973) reports values of the "utilization factor" to be between 0.7 and 0.92.

Jan 1, 1989

By Angelus S. C. Owili-Eger

This paper discusses a model for groundwater quantity prediction at operating sections of underground mines. The approach involves the development of a mathematical model for the movement of water through an integrated (unsaturated-saturated) flow domain within a definable watershed. The model is programmed for the IBM 370/168 computer using the method of finite difference approximation coupled with a finite element analysis. The conceptual and computational aspects of the model have been validated with both experimental and field data and applied to an active coal mining operation located in central Pennsylvania.

Jan 1, 1977

In recent years there have been significant advances in computing power and programming technology, enabling more complicated processes to be modelled in greater detail. This has led to increased understanding of these complex processes, including mineral processing circuits. JKSimMet was developed over the past 35 years, incorporating outcomes from various research projects conducted at the Julius Kruttschnitt Mineral Research Centre (JKMRC), part of the Sustainable Minerals Institute at The University of Queensland. It is a steady-state software program that allows the user to mass balance, model fit and simulate crushing, grinding and classification circuits. JKSimFloat has been developed over the past 20 years, incorporating outcomes from the JKMRC and other institutions around the world through the AMIRA International P9 project ? The Optimisation and Simulation of Mineral Processing Circuits. It is also a steady-state software program, similar to JKSimMet, but is focused on analysing flotation circuits. Both programs have been used in a wide variety of optimisation and design projects over many years. This paper provides an overview of both JKSimMet and JKSimFloat and examples of how both programs have been used to better understand, develop and optimise mineral processing circuits around the world.

Feb 27, 2013

By Luis Bernal, Pertti Lamberg

"SkimAir®, Outotec’s Flash Flotation unit, is placed in the grinding circuit to float the valuable liberated mineral particles from the circulating load of the grinding process while still relatively coarse. Esperanza copper-gold deposit located near Sierra Gorda, Chile, hosts 535 Mtn ore grading 0.57 % copper, 0.27 g/t gold. A series of laboratory and pilot flotation tests were conducted to find out the flotation performance of different ore types both with and without the Flash Flotation. This data was used in modeling and simulating to find the optimal flow sheet for the highest Au and Cu recoveries with required Cu concentrate grade. Simulations with the HSC Chemistry 6.1 software showed that with the SkimAir® and Flash Cleaning it is possible to achieve the required copper grade of 27% Cu with 5% higher recovery for gold and 2% higher recovery for copper compared to the circuit without the Flash Flotation. The pilot tests with simulations were the back up for the installation of four Outotec SkimAir® SK 2400 Flash Cells in the Esperanza circuit for the processing 95.000 tpd of copper-gold ore.INTRODUCTIONEsperanza copper-gold deposit is located near the town of Sierra Gorda, 2nd Administrative Region in Chile. Deposit hosts 535 Mtn ore grading 0.57 % copper, 0.27 g/t gold. The main copper minerals are chalcopyrite and bornite. Gold is carried by native gold and solid solution of copper.Antofagasta Minerals S.A. conducted a series of flotation studies at SGS Minerals Services. The studies included both laboratory and pilot scale work. In the pilot scale study the applicability of the Flash Flotation technology was studied with High-grade Andesite and High-grade Porphyry samples (SGS Mineral Services). The Flash Flotation technology gave significantly higher recovery for gold than the conventional flotation circuit. The recoveries for copper were slightly higher using the conventional flotation."

Jan 1, 2009

By V. Buddhiraju

Liberation of valuable minerals from low-grade ores is an important challenge faced by the minerals industry. It is necessary to grind the ore to extremely fine size in order to liberate the mineral from such ores. As it is generally difficult to produce ultra-fine particles of diameter less than 1-10 mm using traditional grinding equipment such as the ball mill and the rod mill, several new types of grinding equipment are being explored to produce ultra-fine particles. The planetary ball mill is promising in that it makes grinding to submicron sizes possible by imparting high energy to the ground powder. It consists of four pots mounted on a disc. The pots and the disc rotate in opposite directions. The high-speed rotation of the pots and the disc makes the grinding media move at high centrifugal velocities leading to high impact energy and thus improving the grinding performance. The planetary mill is currently being explored for its capability to produce ultra-fine particles on a large scale. In this context, there is a need to understand the dynamics of the ultra-fine grinding process within the planetary ball mill. Here, we address this need by studying the movement of media inside the pots and the grinding kinetics, employing both experimental and modeling techniques. The experiments were conducted on a laboratory scale planetary ball mill. The particle size distribution of the powder was monitored to allow an estimate of the grinding kinetics to be made while video images of the media profiles inside the pots were taken to allow quantification of the media movement as a function of process variables such as the media size, percent loading, etc. The population balance modeling (PBM) framework was used to simulate the kinetics of grinding while the discrete element modeling (DEM) approach was utilized to simulate the media motion. The parameters in the population balance model, namely, the specific breakage rate and the breakage distribution function were determined by fitting the batch grinding equation to the experimental data. The predicted powder size distributions were found to be in good agreement with the experimental data. The experimental results have shown that the mean size of product powder decreases as the size of the grinding media decreases. Keywords: population balance modeling, grinding, planetary mill, grinding media, grinding equation

Sep 1, 2012

By A. Oleynik

The paper presents the modeling and simulation experience in field of research into the mineral row material separation. Features of the subject domain generate a need of different approaches using for modeling and simulation. The general scheme of separation modeling process and some examples of developed simulators are presented. Due to different features and standards of knowledge, different formal models should be used to describe and analyze separation processes in the frame of general scheme. The main types of simulators are modeling tools based on statistical, analytical or expert (logical) methods. Advantages and disadvantages of each method above are mentioned in the paper. Based on the studies in the field considered, an aggregated mathematical model of a separation process has been generated. The aggregated model is presented by two combined equations. The actual apparatus model is formed by substitution of the particular functional expressions of the forces acting in the apparatus into the aggregated model. The developed simulation tools are based on integration of limited experimental data and on ex-pert knowledge available on separation processes. Simulation does not allow producing an optimal, in terms of mathematics, solution. But it gives an opportunity to produce and compare quite adequate solution variants in real time. The results obtained are the theoretical and methodological base for integrated information technologies to support studies in the field of mineral processing.

Jan 1, 2014

By D. Minson, G. Lindner, S. Miskovic

Thickening is an essential process in the mining industry and currently one of the most costeffective technologies for recovering water from tailings streams. Improved performance of thickeners can lead to significant energy savings, and increased recovery of water close to the mill. Its performance is directly affected by the rheological properties of slurry at the raking zone. To further understand the dynamics of slurry inside thickeners, a multiphase particle-in-cell method (MP-PIC), is used to investigate its behaviour on a sliding channel. Parameters like particle-size distribution (PSD), rheological properties, and domain discretisation were benchmarked to study its influence on highly dense flows. The slurry concentration by weight of the samples ranged between 60 to 70% of solids by mass, under which conditions it is known to behave like a non-newtonian fluid. An experimental flume, 0.2 m wide and 2 m long, was used for validation under different angles and slurry composition. Visual analysis of the slurry height and shape, as well as velocity measurements, were compared with numerical data. The preliminary results show the ability of MP-PIC method to represent different types of highly dense flows, while still being computationally affordable and practical for industrial use. Keywords: High density thickener, CFD, MP-PIC, multiphase-flow

Jan 1, 2020

By Neale R. Neelameggham, Ganesan Subramanian

Anthropogenic Heat Flux (AHF) is defined as heat generated from use of non-renewable energy by humans in residential, commercial and industrial activity. State of the art Global Circulation Models (GCM) used to predict global impacts of climate change to help set related policy do not include this heat flux. AHF is considered to be a much smaller an insignificant forcing, solely based on the global mean values. Various Climate models have discussed the “Heat Island Effect ” in high AHF areas. Through the use of simple climate models, it is shown that significant pockets of AHF can impact climate locally in ways significant enough to impact global climate. Inclusion of spatial AHF distribution, rather than a global mean value is important to accurate modeling either on a regional or global scale.

Mar 1, 2017

By Yinlun Huang, Cristina Piluso

"Industrial sustainability looks to improve material and energy efficiencies, product quality and variety, and productivity within an industrial zone, thus pursuing the long-term sustainable development of the region. This paper introduces a systems-based modeling methodology, which provides industrial leaders with the ability to evaluate future production options to determine the path with the highest positive impact on both their own sustainability and the sustainability of the overall industrial zone. A comprehensive study on sustainable development of an auto-manufacturing focused industrial zone under uncertainty is illustrated. Introduction Sustainable development refers to a continuous process of improvements that must be followed in order to achieve a state of sustainability. In its most general form, a widely accepted definition of sustainable development was identified in the Brundtland Report as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs” [1]. Sustainability will occur when the material and social conditions can be maintained or improved for human health and the environment over time without exceeding the ecological capabilities that support them [2]. An industrial zone is defined as a geographic area comprised of a network of industrial sectors, each composed of a number of entities. Such a zone is highly integrated and complex, and contains numerous uncertainties due to each industry’s extreme dependencies on its suppliers and customers throughout the product supply chain. In the context of an industrial zone, sustainable development refers to the continuous process of advancements in the zone, and the entities that comprise it, creating more value, wealth, and profits (economically viable dimension), providing environmentally benign products with less raw material consumption and waste generation (environmentally compatible dimension), and collaboration and a direct relationship among all involved in the supply chain, i.e. the corporations, employees, suppliers, investors, communities, customers, etc. (socially responsible dimension). These are the triple bottom lines of industrial sustainability. In order for economic, environmental, and social sustainability improvements to be successfully implemented within an industrial zone, the industrial decision makers must possess system-wide analysis abilities. The analysis of the sustainable development of an industrial zone involves decisions at the local, regional, or national levels, which are complex and involves handling of ill-defined parameters with a high degree of uncertainty due to the imperfect understanding of the underlying issues [3]. This work focuses strictly on the uncertainties in future zone planning and a method and a scenario based approach that can be used to evaluate the sustainable development of an industrial zone among these uncertainties."

Jan 1, 2008

By T. Doshi, S. Ennis

The interactions of mineralogy, chemistry and mechanics in an ore concentrator are highly complex, so it can be particularly hard to measure the impact of a specific plant change. This paper describes a method for modeling a baseline metal recovery so that the value of a major process improvement can be measured. This method only considers variables that cannot be optimized, such as mineralogy or equipment availability. Linear regression, random forests, extreme gradient boosting (XGB), and simple two-layer neural network models of process value were tested as candidate baseline model types to assess the impact on throughput and recovery in a copper concentrator. XGB performed the best in terms of accuracy for both throughput and recovery models. Using an XGB model of nonoptimizable process variables provides an accurate, dynamic baseline that can be compared with continuous production data to determine the value added by major concentrator improvements in real time.

Mar 2, 2022

By Cristian Castro, Patricio Gomez, Jason Furtney, Augusto Lucarelli

Understanding the effect of blast-induced damage on wall stability is critical to safe and economical operation of a large open pit mine. In this paper, a numerical modeling methodology is used to investigate damage to rock at distances of greater than 10 m (30 ft) from a blast. Two applications of the model are demonstrated. First, the method is applied at a zinc mine to investigate the effects of pit blasting on underground stopes. The model predictions are compared with the scaled distance formula. Next, the model is used to investigate a common problem in which unfavorable jointing creates a rock wedge on the bench above a blast. The numerical predictions of wedge stability are compared to the wedge energy model described by Wong & Pang (1992).

By Cristian Castro, Patricio Gomez, Jason Furtney, Augusto Lucarelli

Understanding the effect of blast-induced damage on wall stability is critical to safe and economical operation of a large open pit mine. In this paper, a numerical modeling methodology is used to investigate damage to rock at distances of greater than 10 m (30 ft) from a blast. Two applications of the model are demonstrated. First, the method is applied at a zinc mine to investigate the effects of pit blasting on underground stopes. The model predictions are compared with the scaled distance formula. Next, the model is used to investigate a common problem in which unfavorable jointing creates a rock wedge on the bench above a blast. The numerical predictions of wedge stability are compared to the wedge energy model described by Wong & Pang (1992).

Feb 1, 2020

By A. Jolly, A. R. Kumar, T. Novak

"Coal dust in an underground mining environment has always been a health and safety issue, especially with longwall faces. Efforts to integrate a flooded bed scrubber within a longwall shearer are underway at the University of Kentucky (UK) in order to reduce worker exposure. Small scale physical modeling, along with numerical modeling and full-scale experimentation, are engineering tools being used by the authors for simulating operating conditions underground. Recent advances in affordable 3D printers offer a means for fabricating accurate, scale models for obtaining timely insights prior to building large, expensive test setups. Comparing scale-model results with those of numerical modeling, such as computational fluid dynamics (CFD), lends guidance and confidence in a proposed design. This paper discusses the small scale physical modeling of a longwall shearer with an incorporated flooded-bed dust scrubber in its operating environment. A tracer gas was used in the model in lieu of dust to measure dust-capture efficiency. Results obtained from the physical model are presented and compared with those of CFD model. The small scale model and the CFD results demonstrate good agreement. Dust capture results show the usefulness of the approach in advance of actual design implementation. INTRODUCTION Dust generation is an undesirable, but innate, byproduct of all mining processes. It is particularly problematic in underground coal mining, where coal dust poses potential hazards from two fronts – health and safety. Coal workers’ pneumoconiosis (CWP), commonly referred to as black lung, is a chronic lung disease that results from the long-term overexposure to respirable coal dust. Although the prevalence of CWP has steadily and significantly declined over the three decades following the Federal Coal Mine Health and Safety Act of 1969, a study by the National Institute for Occupational Safety and Health (NIOSH, 2008) indicates that significant health hazards associated with respirable dust still exist within the coal mining industry. In addition to being a health hazard, coal dust can also create a potentially catastrophic safety hazard. Dust that is not captured or removed at its source is suspended and transported throughout a mine by the ventilation airstream. This float dust is subsequently deposited on all mine surfaces along its travel path. Without adequate application of rock dust to these surfaces, forces from a localized methane ignition can reintroduce settled coal dust into the airstream creating an explosive mixture. Therefore, capturing and removing coal dust at its source mitigates the probability of two major hazards that continue to plague the mining industry."

Jan 1, 2016