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By P. K. Kankar, Manoj Khandelwal, Ramesht Shukla

One of the utmost severe mining catastrophes in underground hard rock mines is rock burst phenomena. It can lead to damage to mine openings and equipment as well as trigger accidents or even threat to life as well. Due to this, a number of researchers are forced to study some easy-to-use alternative methods to predict the rock burst occurrence. Nevertheless, due to the extremely multifaceted relation between mechanical, geological and geometric factors of the mines, the conventional prediction methods are not able to produce accurate results. With the expansion of machine learning methods, a revolution in the rock burst occurrence has become imaginable. In present study, three machine learning methods, namely XGBoost, decision tree and support vector machine, are utilized to predict the occurrence of rock burst in various underground projects. A total of 134 rock burst events were gathered together from various published literatures comprising maximum tangential stress (MTS), elastic energy index (EEI), uniaxial compressive strength and uniaxial tensile stress (UTS) that have been used to develop various machine learning models. The performance of machine learning methods is evaluated based on the accuracy, sensitivity and specificity of the rock burst prediction.

Mar 17, 2021

By P .. F. Ziemkiewicz, T. E. Rymer, J. J. Renton

Prediction and quantification of acid mine drainage (AMD) from a given rock unit is in its infancy. Acid Base Accounting is the current procedure. II is a useful screening procedure and is designed to indicate whether a rock unit will or will not produce acid. In this sense, Acid Base Accounting is qualiwtivc. Researchers at West Virginia University arc developing a prediction method to estimate how much acid will be produced over the life of a rock unit's AMD production. TI1c AMD prediction procedure can also evaluate the required rates and effectiveness of various AMD control amendments. This presentation discusses the WVU AMD prediction procedure in the context of historical approaches and indicates the mechanics and applications of this new technology.

Jan 1, 1991

By S. P. Banerjee

There has been a phenomenal increase in production of coal from opencast mines in India. At the same time environmental problems caused by mining are receiving greater atttention. Deterioration in ambient air quality due to increased concentration of suspended particulate matter (SPM) in and around an opencast project is a major problem. Some measured values of SPM level around opencast mines in diff coalfields show that in many cases the TLV of 500 ug/m^3 is exceeded. The impact of dust emission from a mining project on surrounding areas are estimated by using computer models for air pollution dispersal but such treatment suffers from errors in predicting the dust load and failure to take into account the terraced nature of the opencast mine site. The haul roads have been identified as the most prolific source of dust and some recent trials on haul road dust consolidation in Indian mines are mentioned in the paper. Statistics regarding pneumoconiosis cases in Indian coal mines for the last decade are presented to show an increase in reported cases and a gist of the recently amended regulations on the subject of precaution against dust is mentioned.

Jan 1, 1991

By Shosei Ph. D Serata

The Stress Control Method of mine design provides enhanced engineering control over the behavior of underground structures in comparison to conventional mine design methods. The same Method can be applied to achieve design control of surface subsidence. The basic mechanism relating undergroued deformation and surface subsidence is disclosed by mine simulations, using the REM (Rheological Element Method) computer code, whose predictions have been validated by field measurements. The key components of the underlying mechanism of surface subsidence have been shown to be the stress envelopes formed in the process of underground excavation. It has also been demonstrated that significant control of surface subsidence can be achieved by designing the geometry and timing of underground excavation to regulate the formation of stress envelopes. A field example is given in this paper to illustrate this application of the Stress Control Method.

Jan 1, 1986

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 Paktunc. A. Dogan, Nand K. Davé

Unsegregated pyritic uranium mill tailings from Elliot Lake, Ontario, with and without limestone amendment, were subjected to column leaching experiments for the purposes of predicting the onset of acidic drainage and the magnitude of metal and radionuclide release under various treatment and control strategies. The unamended tailings produced acidic drainage after approximately one and a half year. The tailings mixed with various grain-sized limestone did not produce acidic drainage during the study period. The tailings consist essentially of quartz, K-feldspar, muscovite and pyrite. The unsegregated tailings amended with very fine limestone displayed the least amounts of pyrite loss whereas those without limestone amendment had the greatest pyrite losses. Predicted onset of acid generation varied from 16 to 75 years for the top sections and in most cases greater than 100 years for bottom sections of the unsegregated tailings with limestone amendments. Unsegregated tailings mixed with fine- and very fine-grained limestone proved to be the most effective in controlling or delaying the onset of acidic drainage under unsaturated conditions.

Jan 1, 2000

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 M.P. ROY, ASHISH K. VISHWAKARMA, A.K. MISHRA, P.K. SINGH, VIVEK K. HIMANSHU

Principal component analysis (PCA) is one of the dimension reduction techniques widely used to classify data based on features. Ground vibration is a major hazard arising from rock blasting operations, and accurate prediction of the vibration is necessary for designing controlled blasting parameters. Most of the widely accepted predictors of ground vibration consider the maximum explosive charge weight per delay (MCPD) and distance as the parameters responsible for ground vibration, but mining sites with bigger production targets have varying geometrical parameters to suit the excavator utility. Accordingly, other blast design parameters will also have impacts on ground-vibration intensity. A blast vibration predictor considering all the blast design parameters would be complicated, and some of the parameters will have overlapping contributions to ground-vibration intensity. Data classification using PCA is a feasible solution, and regression analysis may be performed to develop predictors using the classified input data. In this study, PCA was used along with multivariate logarithmic regression to predict ground vibration, and the performance of this technique to predict ground vibration was compared with the performances of various existing empirical predictors. The evaluation suggests that the predictor with logarithmic regression followed by PCA performs better than the existing empirical predictors.

Nov 1, 2022

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

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

Jul 30, 2022

By Shiwei Wang, Ziwen Li, Chenhu Zhang, Peng Chen, Chengyong Wang

Accurate prediction of the partition coefficients in coal gravity separation is key to improving the preparation efficiency of coal and promoting its clean utilization. In China, the approximate formula method (AFM) has been applied to the calculation of coal gravity separation partition coefficients for decades, but its accuracy is limited. To improve the accuracy of the predicted partition coefficients, and thus the product yield of coal preparation plants, the present study proposes a modified hyperbolic tangent model to derive direct calculation formulas for the heavy medium and water medium separation partition coefficients. Four groups of coal samples were used to verify the accuracy of the direct formulas, and their predictions were compared with those of the AFM. The results showed that the partition coefficients and partition curves predicted by the direct formulas were closer to the actual values than those predicted by the AFM. Further, when the cleaned coal ash content was basically the same, the cleaned coal yield predicted by the direct formula was lower than that predicted by the AFM, and was also closer to the actual value. These results demonstrate that the direct formula produces more accurate results compared to the conventional AFM. As this formula has a reasonable theoretical basis, is simple to apply, and produces accurate results, it is expected to help improve the design and management level of coal preparation plants.

Oct 15, 2022

By R. H. Mullennex

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

Jan 1, 1986

By Theodore Triplett

To assess the value of various subsidence mitigation techniques, twelve linear foundations were constructed above a longwall mine. The structures were monitored during and after undermining, and footing curvatures at the time of cracking were compared with predicted values. An unreinforced concrete footing sustained substantial damage. Other footings received varying degrees of damage, with inclusion of a sand layer significantly affecting performance. A post-tensioned concrete foundation suffered minimal cracking. Also, a technique developed by the Bureau of Mines is presented for determining the subsidence, slope, curvature and strain of the ground surface.

Jan 1, 1986

By Manuel Gomez

This report presents prediction equations for eleven factors indicative of metallurgical coal quality which have been developed from data obtainable during exploration. Five coke strength parameters and six carbonization product yields have been predicted for coking coals having volatile matter contents in the range 16.3 to 42.1 percent, dry basis. The prediction models developed contain information from the proximate and ultimate analyses, the size consist, and the petrographic composition of coking coals carbonized in BM-AGA retorts at 800°, 900°, and 1,000°C. The equations reported have been evaluated with independent data derived from the 900°C carbonization of 33 binary blends. Present results show that metallurgical coal quality can be predicted ahead of mining. Capability to forecast coal quality is useful in mine planning and should provide basic information for optimization of blending and crushing techniques, leading to the production of uniform coke.

Jan 1, 1968

By Kerry Burns

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

Jan 1, 1982

By A. Vargiu, R. Ciccu, G. Massacci

Based on the current results of field practice and on experimental data obtained in the laboratory with a suitable testing apparatus, the industrial operation of diamond wire cutting can be simulated by means of a mathematical model capable of predicting the cutting velocity and the wear rate of the tool, and thence the cost figures, achievable for a variety of conditions (kind of rock, size and shape of the cut, position of the equipment) according to a predetermined setting strategy (peripheral velocity, pull- back force). The paper gives a short outline of the model and discusses the simulation results obtained in a number of cases aiming at singling out the most favourable conditions for a cost-effective use of diamond wire.

Jan 1, 1996

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 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

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 Charles S. Robinson

INTRODUCTION Geology, the science of the earth, is the fundamental science in the construction of a tunnel. The approximate site of a tunnel is determined by its purpose. The geology of the tunnel site will determine the cost--or feasibility of a tunnel--the specific alignment to accomplish the purpose of the tunnel, the design of the tunnel (within the limits of the purpose of the tunnel), and the methods of construction. The more accurately the geology of a proposed tunnel can be depicted, the more accurately can the cost of a tunnel be estimated. The factors that should be defined for tunnel design and construction are the physical characteristics of the material in which the tunnel is to be constructed. The physical characteristics of the material are determined by the genesis of the material, and subsequent geologic processes that have affected the material. The geologic materials in which tunnels are constructed can be broadly classified as unconsolidated and consolidated. The unconsolidated materials include chiefly deposits of recent geologic time that occur near the surface. Because these deposits occur near the surface, and tunnels constructed in them will be at shallow depth, methods of physical exploration such as geophysical methods, trenching, and drilling will give more data at relatively low cost--therefore the physical exploration is generally, or should be, quite extensive--and the

Jan 1, 1997

By Ernesto Maldonado, Jesus Romero Benitez, Zach Agioutantis

Numerous researchers worldwide have investigated the prediction of ground movements due to underground coal mining utilizing different analytical, empirical, and numerical models. These studies have primarily focused on the development of prediction methodologies for either flat or gently dipping seams under variable topography, and only a few studies are available that have investigated the prediction of ground movements over inclined seams. Although most inclined coal seams are in China, India, and other countries worldwide, a few inclined coal seams (with a dip of 10 degrees or greater) are also present in the US. Currently, the prediction of ground movements for inclined coal seams using empirical methods utilizes the same methodology for horizontal seams. It consists of dividing the inclined seam into horizontal segments, calculating deformations due to each segment, and superimposing the calculation results. This paper presents a new tool that provides a methodology for modeling subsidence under inclined seam conditions. Examples based on subsidence measurements available in the literature are presented. The goal is to implement this methodology into the Surface Deformation Prediction System (SDPS).

Jun 25, 2024