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By G. D. Just

"Extensive mechanization of underground mining operations, improvements in blasting technology and the development of simulation models for systems evaluation has now made it feasible to optimize rock fragmentation and materials handling operations. Methods of achieving these objectives are described in this paper, with particular emphasis on the need to obtain precise field data measurements. Techniques are illustrated with reference to the sub-level open stoping system of mine production. IntroductionThe primary objective to be achieved in any mining system is to deliver a specified grade of ore to the mineral processing plant at a planned delivery rate and at the minimum total mining cost. Design and management of such a system is complicated by the large number of unit operations and the often unknown inter- relationships between the different unit processes. This particularly applies in underground mines, where planning restrictions and unit costs are much greater than in comparable tonnage sur face mining operations. These difficulties can often be resolved by the application of judgment based on extensive experience, but the costly trial -and-error methods required for new technology discourage innovation.Most modern medium- and large-scale mines are now extensively mechanized. Consequently, the performance of each unit operation by individual items of equipment should be predictable for a given set of conditions. An essential prerequisite is that quantitative performance data are available from field measurements. Such information can then be used to optimize the design and management of the complete mining system to achieve the minimum tot al mining cost. One of the most significant factors influencing all unit costs is the degree of rock fragmentation. The importance of this variable is indicated by the fact that opt imization of rock fragmentation implies minimization of tot al mining system costs."

Jan 1, 1980

By R. Simon

Maurer's review1 summarizes quite thoroughly the various theoretical developments and experimental findings that contribute to the knowledge of rock mechanics in drilling. This discussion supplements Maurer's paper by including generalities that either have been incompletely treated in his review, or formulated from new considerations by the discussant and from hitherto unpublished experimental data. These generalities are associated with the observation that all mechanical methods of rock drilling essentially comprise a sequence of indexed, concentrated loadings on the bottom of the hole being drilled. A concentrated loading is defined as a mechanical loading by a tool that contacts at any one time only a small fraction of the surface of the body being worked and penetrates only a small fraction of the body thickness. The surface in this application is the bottom of the hole. The deformation of ductile material by concentrated loading has received considerable attention because of the importance of indentation tests for measuring hardness of metals. Some of the generalities involved in concentrated loadings on ductile materials apply also to concentrated loadings on more brittle materials such as rock. Among these generalities is the applicability of similitude considerations to scaling laws and to force-displacement and energy-volume characteristics for tools of various shapes, as summarized by Tabor.2 Vork on the flow and fracture behaviors of glass loaded with pyramidal and spherical indenters is reviewed by Douglas.3 Maurer refers to the work of Evans and Murrell on wedge loadings on coal and on mixtures of pitch and sand. It is evident from Maurer's paper that a considerable portion of the studies of rock mechanics in drilling, such as crater formation experiments, has involved concentrated loadings on rock.

Jan 1, 1967

By Wilfrid Comeau

While researching for a theme lecture (Comeau, 1993l) on: 'The Mechanics and Physics Explosives', the author of Energy Transfer in Rock Fragmentaion by was confronted with many conflicting concepts regarding: the current explosive rock fragmentation theories, the physical principles governing energy transfers, the mechanical properties of rocks, and observations and data from full scale rock blasting.

Jan 1, 1995

By M. Machina

Anew approach to the use of projectiles for rock fragmentation uses recently-developed technology to optimize projectile shape and composition to achieve the desired type of breakage. Projectiles can also be made of various materials, as determined by the requirements of downstream processes. This paper describes laboratory tests with an 21-mm (8-guage) gun, and field tests with a 60-mm cannon.

Jan 1, 2003

By Cesar Guerra, Alejandro Rojas, Dr. Jhon Silva, Luis Velasquez

The ANN method is applied to predict the P_80 size in one open pit gold mine in Peru. The ANN was implemented in Matlab programming language, and the results from the ANN are compared with data obtained using photo-fragmentation analysis software.

Feb 1, 2020

By Ankit Jha, RICHARD AMOAKO

In this paper, we examine the challenges associated with the use of empirical rock fragmentation models. We highlight key parameters omitted by these models, and propose a machine learning approach that incorporates these parameters, leading to a simple, yet more accurate approach to blast design.

Feb 1, 2020

By YUSONG MIAO, DI WU, XIANRONG YAN, YIPING ZHANG, JIE LIN, KEBIN LI

Rock fragmentation size distribution is often used as an important index to account for the blasting effect because it directly affects the subsequent loading, transportation, and secondary crushing. Due to the mismatching of explosive and rock wave impedance, high boulder yield often occurs which affects the blasting effect. In this study, methods of measuring rock acoustic impedance, rock strength point loading, and detonation wave velocity have been used to obtain more accurate input parameters. Then, in the watershed image segmentation technique, the Gates-Gaudin-Schuhmann and Rosin-Rammler distribution functions have been used to analyze and quantitatively describe the rock fragmentation size distribution in the existing muck-pile. Finally, taking the rock properties, explosive performance, blasting parameters, and system characteristic variable into consideration, support vector machine (SVM) regression model has been analyzed on the learning and prediction of samples. The results show that SVM has a good prediction accuracy, high precision, and strong generalization ability. The optimized matching coefficient of rock and explosive wave impedance K ranges from 2.50 to 2.58 times. This study has developed a series of simple, accurate methods for rock properties analysis, detonation wave velocity measurement, and muck-pile model image processing, and a basis for predicting and evaluating rock fragmentation size distribution and optimizing the matching coefficient before carrying out a blasting operation.

Jan 22, 2021

By C. Perez

In mineral processing plants it is important to estimate rock composition, size and grindability to improve control of the grinding process. It is well known that variation in ore grindability and size distribution directly affects mills power consumption and throughput. This paper extends a general machine vision approach for on-line estimation of rock mixture composition using color information. Our proposed rock lithological recognition method requires the following steps: division of each image into sub-images, color feature extraction using the Binary Quaternion-Moment-Preserving thresholding technique (BQMP) and support vector machines (SVM) for classification. The BQMP thresholding technique splits the image in two and chooses representatives of each half using the histogram as features. The statistical parameters of the color data can be expressed using the quaternion moments into the representatives. This method can be recursively applied to the sub-images, obtaining 5x2n features in n iterations. Once the feature vector has been computed, each vector is assigned to one of three classes using a classifier. The method was tested on a database containing 20480 sub-images (64x43 pixels) of five ore types as follows: massive sulphide (MS), disseminated sulphide (DS), net textured (NT), gabbro (G), and peridotite (P). These ore types were assigned to three grindability classes: soft (MS), medium (DS and NT) and hard (G and P). The database was divided in 2 subsets: 15360 sub-images used for training and cross validation and 5120 sub-images used for test. The classification accuracy was compared with a method previously published based on a mixture of principal components analysis (PCA) for color, and wavelet texture analysis (WTA) for texture feature extraction. WTA-PCA approach reached a 76% accuracy in test while our BQMP method reached 90% of classification accuracy using only color features. Experimental results show that our proposed method yields excellent results compared to previously published results. Keywords: rock classification, lithological classification, grindability estimation

Sep 1, 2012

By S. Goodfellow, J. C. Ordóñez-Calderón, K. Esmaeili, N. Houshmand

A good understanding of the hardness of ore being handled and processed in a mining operation can significantly improve operational efficiencies by providing valuable data to support decision-making through the mining value chain (drilling, blasting, comminution). This study presents the results from the application of Machine Learning (ML) to predict rock hardness using various geophysical and geochemical features. Core samples from a mine site were logged using a multi-sensor core logging system. Measurements including ultrasonic p-wave and s-wave velocity, elemental concentration via portable XRF, and Leeb Hardness, were measured every 2 cm along the length of the core. The ML model was set up to predict the Leeb Hardness using the elemental concentrations and ultrasonic velocities as predictors. The Leeb Hardness values were grouped into three bins and used as a classification target for the ML models. Various ML models, including linear regression, support vector machines, decision tree, XGBoost, Random Forest, K-Nearest Neighbors, and Naïve Bayes were tested. The model performance demonstrated that the Random Forest and XGBoost models produced the highest accuracy of 74-91%. Random forest and XGBoost were then selected to perform regression models to estimate a Leeb hardness value rather than a hardness class. These models were able to estimate the Leeb hardness value by 4.57-4.87 % error.

Mar 2, 2022

By C. A. Perez

Estimation of rock composition in mineral plants is important to determine rock size and grindability which in turn may improve control of the grinding process. Variations in ore grindability and size distribution directly affects mills power consumption and throughput. Therefore, it is desirable to develop new tools to estimate rock lithological composition. In this paper, a new method for lithological classification based on machine vision is proposed. The method is based on a single video camera and employs information about texture using several different spatial scales. Texture information is extracted from rock images using Gabor filters that can be adjusted at different spatial scales and orientations. After feature extraction, rock images are classified using support-vector machine (SVM). The method was tested on a database containing sub-images of 64x43 pixels of five ore types as follows: massive sulphide (MS), disseminated sulphide (DS), net textured (NT), gabbro (G), and peridotite (P). These ore types were assigned to three grindability classes: soft (MS), medium (DS and NT) and hard (G and P). The database was divided in 2 subsets for training, cross validation, and for test. Classification accuracy is compared with previously published results on a dataset with three different classes of rocks according to their hardness. Results show that our proposed method reached significant improvements (between 13%-20%) in classification accuracy relative to previously published results. Keywords: rock classification, lithological classification, grindability estimation, Gabor feature extraction, texture features

Sep 1, 2012

By Bhawani Singh, A. K. Dube, B. Singh

At least three hydroelectric tunnels constructed during the last decade through the lower Himalayan region in India have met with serious problems of supporting in squeezing ground conditions. Steel ribs under went intolerable deformations requiring rectification to provide space for concrete lining which delayed the projects inordinately. In an attempt to choose a rational method of predicting rock load, the authors have compared rock loads estimated from various classification systems and elasto-plastic theory with observed values. The deficiencies of the classification systems have been highlighted to show that the combination of elastoplastic theory and tunnel instrumentation programme provides better guidelines for the design of tunnel supports in squeezing ground conditions.

Jan 1, 1981

By A. Cichowicz

In this study, techniques used to design earthquake-resistant structures are applied to the deep-level mining environment. Earthquake engineers seek to identify the cause of potentially damaging resonance, and design or reinforce structures to reduce these effects. Similar techniques have been used to analyse the dynamic behaviour of the rock mass surrounding a stope in a deep South African gold mine. A three-dimensional seismic array installed in a stope at TauTona Mine (previously Western Deep Levels, East Mine) provided an opportunity to examine the evolution of the wave field close to an underground opening. A set of three-component geophones installed in a borehole above the panel revealed the development of surface waves as wave fronts reached the excavation, and an array of vertical component geophones fixed to the hangingwall provided a two-dimensional map of site effects. While the collected data do not include damaging seismic events, quantitative analysis enabled phenomena which could lead to damage, to be recognized. In the vicinity of the excavation, the energy of the seismic signal is generally transformed from high frequency to low frequency. It was found that seismic events with relatively high corner frequency (150 Hz?200 Hz) usually excite several modes of vibration (30 Hz to 110 Hz), while events with low corner frequency (30 Hz?50 Hz) do not always excite higher modes of vibration in the structure. This implies that the rock mass around the excavation is a complex medium, and should be studied using the multi-degree-of-freedom model. A strong structural effect (due to the excavation shape) was revealed as a low frequency coda wave (at 40 Hz and 60?70 Hz), well developed on the skin of the hangingwall. A strong site effect was revealed by changes in signal properties between hangingwall geophones, exhibiting strong resonances around 160 Hz and in the range 200 Hz to 300 Hz.

Jan 1, 2000

By F M. Weir, M Fowler

The design of excavations in rock must, implicitly or explicitly take into consideration the influence of small- and large-scale geological structures. For most sites the complexity of a fractured rock mass is best captured using a 3D fracture system model based on field data. A discrete fracture network (DFN) approach involves stochastic modelling of the ‘smaller scale’, nondeterministic structures. For slope stability or tunnelling projects DFN modelling provides a valuable geotechnical tool for characterisation of a rock mass and identification of likely failure mechanisms.This paper presents a suite of the DFN modelling undertaken for the design of a large open pit in Australia. The proposed pit is to encounter a 160?m thick, high strength, sheared shale unit, which overlies a crystalline basement. DFN modelling was undertaken separately for both the shale and basement units. While the model inputs and development for each unit are briefly presented, the focus of this paper is on the various applications of the DFN modelling.A key advantage of the DFN approach for design studies is its probabilistic application to structural analyses and results. Multiple realisations of the same model were generated for both the shale and basement units, with the stability analysis carried out on each iteration. The generation of a large number of DFN models and analyses allow assessment of wedge volume, factor of safety and proportion of unstable slope for a range of conditions. The DFN modelling at the case study site was also utilised for a number of other purposes. For example, investigation of likely fault lengths in the shale unit and combined rock mass and defect failure. The development of this tool has been influential in improving our understanding of fracture networks for excavation design.CITATION:Weir, F M and Fowler, M, 2014. Rock mass characterisation and analysis for excavation design – a discrete fracture network approach, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 445–456 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 5, 2014

By Karina Forster

Rock mass characterisation is a critical component of effective stope design. Unexpected excessive stope dilution or uneconomic stope sizes can be the result of rock mass characterisation that is not representative of actual stope conditions. Comprehensive characterisation of the rock forming the stope hanging wall, back, ends and footwall is best done by a rock mechanics or ground control expert, however, this is time consuming and is often limited by available access. There are two general approaches for characterising a stope hanging wall for dilution estimating. Detailed classification and mapping data can be collected in local areas where good exposure is available. Personnel, exposure and time are usually not available to do a thorough analysis for all stopes. The stope hanging walls are then broken into lenses or domains and similar conditions are assumed for each area. The second approach consists of using readily available data such as RQD. Other rock mass properties which influence hanging wall behaviour are estimated based on back analysing a few case histories. Stope design is then based on the variability of the one parameter, such as RQD, that is consistently measured for the rock mass surrounding the ore body. This paper presents a third approach which looks, in depth, at the interpretation of geological core logging data for rock mass characterisation. Several rock mass properties that influence stope design, such as joint alteration, rock mass strength, joint spacing and orientations, have been linked to data collected by the mine geologists. This drill hole logging data was calibrated against underground mapping and used to back analyse the dilution prediction for mined-out stopes.

May 1, 2006

By D. Boreck

The Bureau of Mines is conducting research on the feasibility of incorporating in situ stope leaching into active underground metal mines. Stope leaching, a modified in situ leaching technique, proposes to recover metals by leaching fragmented ore in existing underground openings and collecting and processing the metal-bearing solution to recover the valuable metals. If leaching solutions escape from the stope, either through geologic discontinuities or highly permeable zones in the rock, valuable metals dissolved in the solution may be lost. Escaping solutions may also contaminate ground waters. Consequently, in fractured rock, the characteristics of the fractures in the vicinity of the leaching stope must be understood before introducing actual leach solutions into the stope. Effectively characterizing a rock mass requires the integration of several disciplines including structural geology, borehole geophysics, hydrology, geochemistry, and mining engineering. This paper will focus on the general geologic and geophysical techniques that can be used to characterize the rock mass at an underground simulated stope leaching site. The results of several geophysical logging methods, tested at the site, are compared to the geologic core descriptions. Then, the? effectiveness of the different geophysical techniques in delineating fracture zones will be assessed. Knowledge gained through the geologic and geophysical analyses can be used to supplement results from hydrologic testing. This information can also be utilized in designing blast patterns and developing strategies for controlling or blocking movement of escaping leach solutions.

Jan 1, 1991

By Nick Barton

When the Q-system was launched in 1974, the name referred to rock mass classification, with focus on tunnel and cavern support selection. Besides empirical design of support, the Q-value, or its normalized value Qc, has been found to correlate with seismic P-wave velocity, with deformation modulus, and with deformation. The Q-system provides temporary or permanent support for road, rail, and mine roadway tunnels and for caverns for various uses. It also gives relative cost and time for tunnel construction for a complete range of rock qualities. There are also indications that Q has captured important elements of the cohesive and frictional strength of rock masses, with Qc resembling the product of rock mass cohesion and rock mass friction coefficient.

Jan 5, 2007

By Paul Headland

The Washington Suburban Sanitary Commission (WSSC) has recently completed design for the Bi-County Water Tunnel Project. The project will include a 10-foot diameter, 5.3-mile long hard rock tunnel located within the Piedmont Physiographic Province in Montgomery County, Maryland. The rock formations present along the alignment are comprised of igneous and metamorphic lithologies. This paper presents the steps taken to characterize the complex geology along the tunnel alignment into a single ?Engineering Unit? based upon the intact rock and rock mass properties. The Rock Mass Rating (RMR) system is planned to be used as the basis for dividing the ground into three ?Excavation and Support? classes. This RMR approach was selected to establish contractual baselines as presented in the Geotechnical Baseline Report (GBR) and is intended to facilitate management of the ground support characterization during construction.

Jan 1, 2008

By Ernesto Villaescusa, Andres Brzovic

Rock masses of the primary copper ore at the El Teniente Mine are very competent and massive. The rock mass contains almost no open discontinuities. Nevertheless, there is a high frequency network of small discontinuities coupled with widely spaced faults. A data collection campaign designed to characterize the rock structure was recently implemented. The results show that conventional analysis in terms of discontinuity frequency does not predict differences between two studied sectors. However, when an empirical definition of a weak discontinuity is applied, appreciable differences between the two sectors appear in terms of discontinuity frequency and predicted in situ block size distributions. These differences are in accordance with actual observations at the mine site. Due to the geological features of the primary copper ore, rock mass classification schemes cannot be readily applied to characterize these rock masses.

Jan 5, 2007

By J. A. Siekmeier

The thickness of the laminated beam modeled in this study is based on bridging potential and TDR measurements. The laminated beam stiffness is based on the effective stiffness of an equivalent transformed section. The maximum deflection of this near-surface laminated beam is compared with the maximum measured surface subsidence. The spreadsheet provides a rational technique to graphically display the character of the overburden and potentially allows prediction of a subsidence factor based on boring logs and the proposed mine plan. The U.S. Department of the Interior, Bureau of Mines (Bureau), utilizes a commercially available computer spreadsheet program in combination with a modified version of Bieniawski's Rock Mass Rating (RMR) system to characterize the geology overlying high extraction coal mines. The spreadsheet program calculates a RMR for each bed based on the lithology, thickness, and engineering properties, which are determined from boring logs and laboratory tests. Once the RMR is calculated the spreadsheet has two major functions. First, the spreadsheet calculates values used to graphically represent the character of each individual bed in the overburden. It calculates an in situ deformation modulus using an empirical rela¬tionship between the modulus and the RMR and then uses this effective modulus along with additional parameters that are based on mine geometry to calculate the bending stiffness and bridging potential for each bed. Second, the spreadsheet creates a transformed section that allows groups of beds to be modeled as an elastic beam. It then calculates a bridging potential for the entire rock mass. The bridging potential of the rock mass is a single value that takes into account both the geology of the overburden and the geometry of the mine. It seems reasonable that there would be a strong correlation between the bridging potential, the overburden response to high extraction mining, and the subsidence ratio. The results presented in this paper focus on the relationship between the bridging potential of individual beds and the deformation measured using Time Domain Reflectometry (TOR). Subsurface displacements measured over seven high extraction coal mines in southern Illinois were correlated with the bed stiffness and bridging potential profiles. Based on these correlations it was evident that the process of caving and subsidence over these high extraction mines involved momentary bridging by individual beds or groups of beds and the ultimate development of a laminated beam near the surface.

Jan 1, 1986

By Tyler DB, Thin LGT

Coal mass strength properties must be estimated to obtain realistic estimates of coal pillar strength. The limitations of existing techniques for approximating these properties are discussed. The coal mass is anisotropic. The Hoek and Brown approach to rock mass property estimation is modified to allow for this. This approach requires the Rock Mass Rating (RMR) for the strata. In the normal case where bedding is sub-horizontal, these major planes of weakness have little effect on the strength of pillars. As a result of this the RMR must be measured parallel to bedding. This means that a significantly higher rating than that usually obtained for coal is observed. The use of mass strength property estimates in extant empirical relationships is outlined. At high width to height ratios, an acceleration in the rate of increase in pillar strength with increasing width to height ratio has been observed. The empirical relationship developed by Salamon (the so called squat pillar formula) takes account of this. This relationship was found to have significant limitations with respect to its universal application. Modifications are made to Bieniawski's empirical formula to extend its use to large width to height ratio (squat) pillars. This new squat pillar formula has none of the disadvantages associated with Salamon's relationship. Strain softening was incorporated into non-linear finite difference numerical modelling to estimate pillar strengths. The technique outlined above is used to obtain peak coal mass properties. Modelled pillar strength was found to be sensitive to both peak and post peak mass strength properties. Post peak properties were found to be difficult to obtain and required some back analysis. Modelling results were used to estimate both the strength of squat pillars and parameters for use in a new squat pillar empirical strength relationship.

Jan 1, 1992