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By Mei Long, Tawum Juvert Mbah, Jianhua Zhang, Haiwang Ye

There have been many improvements and advancements in the application of neural networks in the mining industry. In this study, two advanced deep learning neural networks called recurrent neural network (RNN) and autoregressive integrated moving average (ARIMA) were implemented in the simulation and prediction of limestone price variation. The RNN uses long shortterm memory layers (LSTM), dropout regularization, activation functions, mean square error (MSE), and the Adam optimizer to simulate the predictions. The LSTM stores previous data over time and uses it in simulating future prices based on defined parameters and algorithms. The ARIMA model is a statistical method that captures different time series based on the level, trend, and seasonality of the data. The auto ARIMA function searches for the best parameters that fit the model. Different layers and parameters are added to the model to simulate the price prediction. The performance of both network models is remarkable in terms of trend variability and factors affecting limestone price. The ARIMA model has an accuracy of 95.7% while RNN has an accuracy of 91.8%. This shows that the ARIMA model outperforms the RNN model. In addition, the time required to train the ARIMA is than that of the RNN. Predicting limestone prices may help both investors and industries in making economical and technical decisions, for example, when to invest, buy, sell, increase, and decrease production.

Jan 6, 2021

This paper presents the latest developments in the flotation model being developed collaboratively between the Julius Kruttschnitt Mineral Research Centre in Brisbane, Australia, and the Mineral Processing Research Unit of the University of Cape Town in South Africa as part of the Australian Minerals Industries Research Association (AMIRA) P9 Project. It includes: - characterisation of flotation cells using the bubble surface area flux, Sb; - relationship of Sb to the overall flotation rate constant; - determination of the froth recovery factor; - evaluation of ore floatability; - modelling of entrainment - development of the Floatability Characterisation Test Rig (FCTR); - use of the model in design and optimization of flotation plants; and - current and future work.

Jan 1, 1999

By Pratt Rogers, Aaron Young

This paper considers the mining industry’s need for digital transformation (DT) and presents a three-part review of the foundational components of the DT process: ubiquitous data, connectivity and decision-making. It also provides a discussion on the future of DT in mining as well as a research direction, which identifies the need of academia to provide support for mining companies in the form of both research and the education of digitally literate, dynamically capable mining engineers into the coming decades.

By Harold J. Schock

The cases of no auxiliary ventilation and ventilation with tubing were mathematically modeled, using a turbulent dispersion model. The scooptram that is used to load is modeled as a variable-speed, variable-strength source of pollutants moving in and out of the dead-ended drift. Model predictions are compared to experimental measurements. A parametric analysis was performed to determine the effect of exhaust pipe location and time spent out of the drift, as well as to determine if a relationship existed between CO2 and NO levels. It was concluded from this analysis that when modeling a load-haul-dump cycle, it is necessary to use a model that has the capability of predicting changes in source strength as well as source location. It was also determined that four relevant factors include effective heading height, apparent longitudinal diffusion coefficient, transverse concentration gradient at the face, and average dispersion width of the exhaust jet. As these factors change with heading geometry and ventilation configuration, they were determined experimentally, Carbon dioxide was used as a tracer to calibrate the model; since, knowing the fuel flow rate, it is possible to calculate CO2 production. The above four factors in the computer model were calculated using a regression analysis, comparing predicted local concentrations to measured local concentrations. The model was then verified after this calibration process using additional experimental results. With the calibrated model, it is possible to predict pollutant concentrations at any location in the heading using an engine map and the previously calculated flow field. A parametric analysis shows that the exhaust pipe location can have a significant impact on operator exposure to exhaust gases. It was also shown that NO concentration varies directly with C02 levels. Predictions using the dynamic model are contrasted with constant source strength (pollutant flow rate) results. An analysis of these predictions for computing time-weighted average NO shows the dynamic model predictions of operator exposure to this pollutant to be less than one-half of the value predicted using a constant source model.

Jan 1, 1981

By W. Miola

The MSHA prescribed method for the determination of quartz in airborne respirable dust samples from underground coal mines is the P-7 method, a combination of low temperature radio-frequency ashing (LTA) and infrared analysis (lR). There is no prescribed procedure for quartz analysis in bulk samples of coal and host rock. Dispersive Infrared (IR), Fourier-transform Infrared (FTIR), and X-Ray Diffraction (XRD) methods are most commonly used for quartz analysis in powders. Several aspects of the experimental procedures such as the analysis sample preparation from bulk samples, ashing techniques, scanning procedures, peak measurement location, calibration techniques, sample amounts, size consist, and data interpretation affect differently the results from each of the methods. Significant differences in analysis results from X-ray diffraction (XRD) and infrared spectroscopy (IR) on the same samples are reported. All these studies point to the need for reliable quartz analysis methods. In a recent research, a procedure for preparing bulk coal and host rock samples for quantitative quartz analysis was developed. Further the results from X-ray diffractometry and infrared spectroscopy for quartz content on identical samples were compared. Calibrations with pure and mixed standards were used to assess the influence of particle size distribution, matrix, and calibration on analysis results. In this paper, several issues with the measurement of quartz in the samples of coal, host rock, and airborne respirable dust from mines are outlined and quantified.

Jan 1, 1994

By Santosh Kumar Ray, DEBASHISH MISHRA, Niroj Kumar Mohalik, SOMU MANDAL, Jai Krishna Pandey, Asfar Mobin Khan

Coal is a low-cost and high-calorific-value fuel. The coal mining industry worldwide has been suffering from severe accidents due to coal dust explosion hazards since its inception. Statistically, it was observed that 12,489 fatalities had occurred in 104 reported mining accidents from coal dust explosions during 1900–2020. There are numerous methods for detection, prevention, and control of coal dust explosions in mines. The underground mining environment is unpredictable and has an array of variables. These undulating factors make it difficult to prevent or control the coal dust explosion hazard. However, coal mining is done aggressively throughout the world, especially in developing countries as coal is a major source of thermal energy used in power plants contributing to about 38% (IEA, (2019), World Energy Outlook, IEA, Paris https:// www. iea. org/ repor ts/ world- energy- outlo ok- 2019.) of world electricity. Worldwide, coal dust explosibility studies are carried out in experimental mines, laboratories, and simulations. The complexity, lack of proper infrastructure, and unavailability of laboratory equipment sometimes make it difficult to study coal dust explosibility. The authors have discussed in detail and proposed that the CFD modelling can be a viable option for studying and evaluating coal dust explosibility.

Jun 29, 2022

By Jens Classen, Martino Gatti

"GENERAL PROJECT DATAThe Sparvo Tunnel is part of the “Variante di Valico” project, a new 65km (40mi) highway link between Bologna and Florence, designed to renew the existing A1 route which connects Bologna and Florence. It is composed of 2 x 2,5km (1,55mi) twin tunnels excavated inside a complex geological context, characterized by the presence of a series of surface landslides and methane gas.The inclination is 2,6 % and the minimum radius is 1.400m (4.600ft). The two tunnel tubes were excavated by a 15,6m (51ft) diameter EPB-TBM from summer 2011 to summer 2013. The internal diameter of the concrete lining is 13,6m (44,5ft), made up of precast concrete segments 2m (6,5ft) long and 70cm (28”) thick, being the largest and heaviest segments ever produced. Excavation went smooth apart from initial problems concerning clogging problems and a main bearing damage of the TBM, which are discussed in a further paper during the congress. No structural damage was observed until the end of the TBM drives.SITE OBSERVATIONS DURING THE POST-EXCAVATION PHASEThe first evidence of the stress state of the segmental lining appeared on November 20, 2013 inside the northern tube (1st drive). Ring No. 884 showed obvious signs of overstress, resulting in spalling and crushing of the concrete, and the subsequent bending of the reinforcement, as visible in figure 1.At this time the tunnel invert was already partially backfilled, and construction traffic was running through the tunnel. First safety measures included closing of the tunnel, and initial measurements of the displacements."

Jan 1, 2016

By Onur Golbası, Berk Gokce

Investment decisions in the mining industry are complicated by sector-specific uncertainties. This study presents a multi-submodule system dynamics model to capture the dynamic complexities of decision-making across mineral property development stages. The model includes five interconnected subsystems: valuation, production, growth strategy, demand, and finance. Developed through system decomposition, expert input, and literature, the model is tested on a hypothetical copper mine with 850 ktpa capacity and 1% cu grade. Simulated over five years with quarterly steps, it estimates an enterprise value of $78.9 million and a target growth rate of 11.2%. Results highlight the significant effects of operating costs, capital policies, and inflation on free cash flow, and the critical role of mineral reserves in sustaining growth. This model supports strategic investment analysis across different minerals and development phases, offering mining investors a robust tool for optimizing decisions.

Feb 22, 2026

By d&apos, L. F. G. Assumpcao

Kaolin samples from Rio Capim resources were treated in conventional and superconducting magnetic separators to study the main variables that influence the color removal process. Coating clays and delaminated clay were tested. Retention time (or pulp injection velocity), magnetic field intensity and matrix type were the' variables studied. The feed brightness ranged from 84.7 to 87.6 % ISO for the coating clays and from 80.7 to 85.4 % ISO for the delaminated clay. The results showed unleached brightness values higher than 88 % ISO for coating products and higher than 87 % ISO for the delaminated product, using a conventional magnetic separator with an applied field of 1.5 to 2.0 Tesla. With a maximum field intensity in the superconducting machine of 5.0 Tesla, unleached brightness values higher than 88.5 % ISO for both coating and delaminated clays were attained.

Jan 1, 1995

By J. A. Madonna

Independent prospectors and small to large-scale exploration company personnel have requested, and are in need of, guidance in geochemical field sample collection methods which will provide the most reliable results during chemical analysis. In cooperation with analytical laboratories, experienced geochemical exploration scientists and mining companies a systematic collection procedure has been developed. The procedure consists of collecting uncontaminated, water, sediment and rock chip samples of the appropriate quantity and/or dimensions to meet the needs of analysis.

Jan 1, 1999

By James R. Walpole

Less than 100 years ago the first major federal regulatory agency, the Interstate Commerce Commission was established (in 1887), and since that time literally hundreds of other federal agencies have been created. The regulations set by these agencies tremendously affect the individual citizens of this country as well as U.S. institutions. A few examples of the myriad agencies established include the Food and Drug Administration. (1907), the Bureau of Mines (1910), the Federal Reserve System (1913), the Federal Trade Commission (1914), the Tennessee Valley Authority (1933), the Securities and Exchange Commission (1934), the National Labor Relations Board (1935), the Small Business Administration (1953), the Federal Maritime Commission (1961), the Equal Employment Opportunity Commission (1965), the Farm Credit Administration (1971), etc., etc. Eight years ago, on December 2, 1970, still another federal agency was established by the reorganization plan of President Nixon -- the Environmental Protection Agency (EPA). The Administrator of EPA was given authority to regulate certain activities affecting the environ-ment, which were formerly within the jurisdiction of the Department of Interior, the Department of Health, Education and Welfare, the Federal Radiation Council, the Atomic Energy Commission, the Department of Agriculture, etc. Within weeks after the formation of this Agency, Congress began to enact legislation which would be administered by EPA. Over the last eight years a considerable number of such laws have been passed, a few of which include: the Clean Air Act (1970), the Noise Control Act (1972), the Federal Water Pollution Control Act (1972), the Marine Protection, Research, and Sanctuaries Act (1972), the Federal Insecticide, Fungicide and Rodenticide Act (1973), the Safe Drinking Water Act (1974), the Toxic Substances Control Act (1976), the Resource Conservation and Recovery Act (1976), the Clean Air Act Amendments of 1977, etc. It may be helpful to review, in a summary fashion, the major provisions in some of these statutes, and accompanying regulations, as they relate to water quality control in the mining industry. The Safe Drinking Water Act and the Federal Water Pollution Control Act contain provisions to be examined, as well as the Resource Conservation and Recovery Act and the Toxic Substances Control Act. One other law, the Surface Mining Control and Reclamation Act (1977), is not administered by EPA although it does contain many provisions related to environmental control, and it will also be dis-cussed because of its importance to the mining community.

Jan 1, 1978

By H. B. Oblad

Coal/pyrite fines were froth floated in a laboratory cell to examine the rate of pyrite recovery during conventional coal flotation. The effects of collector, particle size and carbon to total sulfur ratio on the kinetics of recovery were investigated. These data coupled with microscopic examination suggest that miniscule amounts of coal that remain attached to the pyrite surface affect the rate of flotation of pyrite.

Jan 1, 1985

By D. K. DeForest

The olfactory system (sense of smell) is crucial to the ability of fish to avoid predators, recognize kin, and synchronize reproduction (Baldwin et al. 2003). Copper (Cu) has been shown to impair olfaction in juvenile freshwater life stages of salmonids (including Pacific salmon and trout) in some laboratory experiments; and in the United States, public concerns have been expressed that current regulatory criteria for Cu in fresh water are not adequately protective of olfactory function in salmonids (e.g., OSU 2007; Pearson 2007). These concerns have largely been raised because some Cu concentrations that have caused olfactory impairment in salmonids in the laboratory are less than Cu concentrations that have been shown to reduce salmonid survival, growth, or reproduction (the effects endpoints that are typically considered in deriving ambient water quality criteria). However, two important and interrelated points that must be considered: (1) freshwater Cu criteria are "driven" by the sensitivities of several invertebrate species that are more sensitive than the olfactory impairment threshold in salmonids when (2) the influence of water chemistry on Cu bioavailability is properly considered in deriving Cu criteria. Bioavailability refers to the ability of various chemical forms of Cu to interact with receptors on the surface(s) of organisms and thus directly cause toxicity or uptake by the organisms. The toxicity of Cu and other metals to aquatic organisms is a function of water chemistry. For example, acute Cu toxicity in fresh water generally decreases as pH, water hardness (Ca2+ and Mg2+), alkalinity, and dissolved organic carbon (DOC) concentrations increase (Meyer et al. 2007). The U.S. Environmental Protection Agency (USEPA) has recommended hardness-based freshwater aquatic life criteria for Cu and other metals since the 1980s (e.g., USEPA 1985); and hardness-based metals criteria decrease (i.e., become more restrictive) as water hardness decreases. More recently, the USEPA has recommended freshwater aquatic life criteria for Cu based on the biotic ligand model (BLM; USEPA 2007), which accounts for the influence of multiple water chemistry parameters, including DOC, pH, alkalinity, Ca2+, Mg2+, and several other cations and anions. The BLM-based Cu criteria generally decrease as DOC concentration, pH, alkalinity, and water hardness decrease. Because DOC has a stronger influence on Cu bioavailability than water hardness, hardness-based and BLM-based Cu criteria can differ considerably. For example, in water that has low DOC and high hardness, the hardness-based Cu criterion would be relatively high (because it is driven by the high hardness) but the BLM-based Cu criterion would be relatively low (because it is driven by the low DOC). Thus, any evaluation of the protectiveness of Cu criteria against a given effect, such as olfactory impairment, must properly account for the chemistry of the exposure water. Meyer et al. (2013) compiled data on Cu-induced olfactory impairment and olfactory-induced behavioral effects from tests in which BLM parameters were measured. They demonstrated that the USEPA's BLM-based freshwater life criteria for Cu are protective against olfactory impairment, because it adequately accounts for water chemistry (whereas the USEPA's hardness-based Cu criteria are not consistently protective). Olfactory impairment by Cu is now receiving increased attention in Canada and Europe (e.g., Wall 2013; Stang 2013). Accordingly, in this paper we have expanded the analysis of Meyer et al. (2013) to consider copper guidelines from various other countries and whether these guidelines are protective against olfactory impairment.

Feb 23, 2014

By David Wright, Jerome Chamfray, Anthony Harding, Brian Boye

Conway’s Law states that unless we intentionally design automation tools around what we need, we will simply replicate our existing processes. While we may achieve some savings this way, there is an opportunity for greater benefits if we re-imagine the way we, as an industry, perform design. This paper examines current technology and shows how even small departures from merely encoding what we currently do could reap significant benefits. From these examples a framework is developed for a new and innovative approach tvo automation that will allow us to design more quickly, to a higher quality, and communicate outcomes more effectively.

Dec 1, 2022

By Alan Boughey

The world's largest grinding mill operates at the Cadia Hill Mine in Australia. Svedala Industries supplied the 12.2-m- (40-ft-) diam, 20-MW Cadia gearless, semiautogenous grinding mill (SAG). This was a leap of more than 40% above the largest operating SAG mill. This article reviews the significant items involved in the development, design, manufacture, installation and operation of this mill. Description of the Cadia project The Cadia Hill Mine is located 25 km (15 miles) southwest of Orange, in the Central Tablelands of New South Wales, Australia. The mining lease covers about 3,100 hm2 (7,660 acres) of the Cadia Valley. The Cadia deposit is a large, homogeneous, low-grade, porphyry-type, gold-copper resource. Current reserves stand at 202 Mt (222 million st), grading 0.73 g/t (0.02 oz/st) gold and 0.17% copper. They contain 146.2 t (4.7 million oz) of gold and 347 Kt (382,500 st) of copper. The operation consists of openpit mining and ore processing to produce gold bullion and a gold/copper concentrate. The operation processes 17 Mt/a (19 millon stpy) of ore to produce 91 kt/a (100,300 stpy) of concentrate and 9.1 t/a (293,000 oz/year) of gold. The plant operates two 12-hour shifts a day and had a targeted availability of 94%. The plant facilities include a copper concentrator, o water supply system, an openpit mine, tailings pipeline and dam, and a concentrate pipeline and dewatering facility located in Blayney, about 35 km (22 miles) from the concentrator. Significant features of the process plant include o primary crusher and stockpile, a reclaim conveyor system feeding, the Cadia SAG mill (Figs. 1 and 2) and two 6.7-m- (22-ft-) diam ball mills (Fig. 3). A portion of the gold is extracted in a gravity circuit. The balance is extracted with the copper in the flotation section of the plant. Concentrate is thickened and piped about 35 km (22 miles) to the filter plant and rail loadout facility located in Blayney. Tailings are pumped to a tailings dam and process water is reclaimed from the tailings dam. The water system is designed to control and capture available runoff from local creeks, and to store these waters in dams and weirs. In addition, a major portion of the water for the process plant is treated effluent from the city of Orange and a smaller portion from Blayney Mill selection. The low-grade ore posed a dilemma for Cadia. To achieve a satisfactory economic operation, large-scale processing was required. The selection of the mills, equal to the largest designed and operated at the time, gave a plant configuration consisting of two 11.1- x 5.8-m (36- x 19-ft) SAG mills and three 6.1- x 9.1-m (20 x 30-ft) ball mills. This configuration did not provide the most satisfactory economic model for the project. A review of the single line configuration indicated that a significant reduction in the overall capital cost of the plant could be achieved by increasing the size of the mills and reducing the quantity. Increasing the size of the mills,

Jan 1, 2001

By Howard Brown

High purity, high brightness limestone deposits in the San Bernardino Mountains and Mojave Desert region occur in upper Paleozoic carbonate rocks which are part of an upper Precambrian and Paleozoic sequence that unconformably overlies crystalline basement. The Paleozoic strata are divided into formations and members, and correlated with strata of the inner Cordilleran miogeocline. The region has been affected by multiple Mesozoic intrusive, contact, and regional metamorphic events. Structure is complex, and includes polyphase Mesozoic folding and thrusting, and complex Cenozoic structures. The area continues to be seismically active. High brightness (white), high purity crystalline limestone deposits are uncommon because their formation is dependent on several geologic processes which include; 1) depositional environment, 2) contact and or regional metamorphism, 3) folding and faulting, 4) uplift and erosion, and 5) preservation through geologic time. The complex geologic history of the San Bernardino Mountains and Mojave Desert region has allowed the formation of several large high brightness, high purity limestone deposits which are currently being mined or will be mined in the future. Specialty Minerals, Inc. (formerly Ptizer), Pluess-Staufer (California), Inc. and Partins Limestone, Inc. produce high brightness, high purity limestone from several quarries in the San Bernardino Mountains. These active mines combined with undeveloped deposits controlled by Pluess-Staufer in the San Bernardino Mountains, New York Mountains, and Bristol Mountains in the Mojave area, contain proven and or indicated reserves sufficient to sustain production through the 21st century Detailed geologic mapping, intimate knowledge of stratigraphy, recognition of complex structures, sampling, drilling and assay data, are proven tools in the discovery and delineation of high brightness, high purity limestone deposits in the San Bernardino Mountains and Mojave Desert region of southern California.

Jan 1, 1995

By Rong Lu, Hao Wu, Bing Dai, Guoyan Zhao, Li Cheng, Weizhang Liang

Affected by the disturbance of blasting activities, deformation instability and rock dynamic disasters are prone to occur in deep hard rock roadways. Thus, it is particularly necessary to understand the failure behavior of rocks and roadways under dynamic loads. In this study, a series of impact loading tests were carried out on sandstone samples with and without a circular cavity by a modified split Hopkinson pressure bar (SHPB) test system. The mechanical properties and energy evolution of the samples were systematically investigated, and the effect of cavity size was analyzed. The results showed that the presence of the cavity in the samples weakens the dynamic compressive strength by more than 10%, and the peak strain and brittleness are also reduced to varying degrees. Under dynamic loading, spalling cracks occur first on the roof and floor of the cavity, and then different numbers of shear cracks are formed on the sample diagonals. The eventual shear failure mode is the result of the connection of the shear cracks and the cavity. As the cavity radius increases, the dissipated energy density and fractal dimension both grow accordingly, leading to smaller and smaller rock fragments. The dynamic failure behavior of the circular cavity can be well explained based on the dynamic stress distribution law. Overall, this study can provide a reference for the study of the mechanism of rock burst in deep roadways.

Feb 18, 2021

By S. Middlemiss

The Indentation Fracture technique is being developed as a tool for use in comminution and mineral liberation analysis. Fracture toughness measurements for a number of mineralogical materials were made and comparisons were drawn between these and properties measured with the Ultrafast Load Cell drop weight apparatus. The technique has also been used as a probe to quantify differences in fracture properties at different areas in the microstructure of a material. In both a Utah limestone and a South African quartzite, material near a grain boundary fractures very differently to that in the bulk. Ongoing work is ultimately aimed at producing a comprehensive fracture model for a multi-mineral system based on its micro-fracture characteristics.

Jan 1, 1994

By Charles H. Wells

This paper describes a commercial installation of a sophisticated instrumentation and control system designed to maximize the performance of heavy medium cyclones. Samples of plant feed and its products were collected and analyzed for ash content so that measures of efficiency could be determined for plant operation under (1) manual control and (2) automatic (computer) control. The heavy medium cyclone control strategy and its digital computer implementation are discussed in detail. The sample results are analyzed and the economic benefits of automatic control are discussed. Results from the initial data sets quantify the economic benefits of automatic closed-loop control; viz, increased recovery and reduced clean coal variability have been clearly demonstrated.

Jan 1, 1981

By S. M. Hossaini, M. Ataei, H. Moosavi

The abstract highlights the importance of pillar stability in underground coal mines and the influence of rock mass strength and joint orientation on pillar behavior. The study employs numerical modeling using the distinct element code (UDEC) to investigate the impact of these factors on pillar stability. The research considers different joint orientations and varying rock mass strengths, analyzing parameters like stress distribution, displacement, and failure patterns. The findings reveal that both joint orientation and rock mass strength significantly affect pillar stability, with specific combinations leading to reduced safety factors and increased deformation. The study concludes by emphasizing the importance of considering these factors in pillar design for safe and efficient mining operations.

Apr 4, 2022