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Combine the MSHA and OSHA versions of the HazCom Helper into one easy-to-use software tool.

Jan 6, 2007

By T. Ruff

Researchers at the National Institute for Occupational Safety and Health, Spokane Research Laboratory, studied technology and methods that could reduce accidents involving surface mining equipment that collides with other vehicles or workers, or drives over an unseen road edge. These accidents are partially attributed to the lack of full visibility around these large pieces of equipment. Blind areas can be extensive and this report presents plots of blind areas for five pieces of surface mining equipment. Several technologies designed for detecting obstacles in blind areas and providing a warning to the operator were evaluated on off-highway dump trucks. These proximity warning systems included radar, sonar, GPS, radio transceiver tags, and combinations of radar and cameras. A summary of test results is presented in this report, along with guidance on effective proximity warning technology, installation and maintenance considerations, and recommendations for effective implementation. This study found several commercially available systems that could effectively warn an equipment operator of an impending collision. Several new technologies also show promise for reducing these accidents. In most applications, it is recommended that sensor-based systems be combined with video cameras to provide important alarming functions along with an actual view of the blind area.

Jan 6, 2007

By Nikolaos Polysos, Holger Witthaus

INTRODUCTION The classification system for German coal mining is the result of approximately 100 years of experience in roadway development and longwall mining. It is also based on different research projects covered by national and European research programs. Over the past 30 years, more then 600,000 m of road-ways have been driven and employed for mining activities. To properly describe the German rock mass classification system, therefore, it is useful to take a look at the main geomechanical preferences and common support systems. The decision about the most effective development technique and support system is based on a synthesis of rock mass classification and geomechanical analysis. The properties of surrounding rock, the in situ stress, and the influence of mining activities in several seams at each German mine must be considered for the evaluation of the expected deformation of the roadway. The mine layout, the requirements of ventilation and fire prevention, as well as the need to maintain emergency escape routes for the miners, require that the gate roads remain usable after the passage of the longwall face in most cases. Moreover, the gate roads must be maintained despite the high stresses that are applied during longwall retreat mining. Therefore, gate road design must address a broad spectrum of potential deformation environments. In the past, when gate roads were supported solely with yielding steel arches, lithologic descriptions of the surrounding strata conditions were adequate for the dimensioning of support and the prediction of the roadway deformation. The current conditions of multiple-seam mining at depths of up to 1,700 m require combined support systems, including pattern bolting and backfilled steel arches. Rock bolt support is used for development, after which (typically 50–100 m outby the face) the steel arches are installed and backfilled with building material (concrete) in order to achieve an optimized development rate. The rock mass classification system described below was developed especially for the conditions of German hard-coal mining. It includes the stress distribution caused by multiseam workings (including crossing goaf edges of former longwalls), as well as in situ stresses due to greatdepth and the presence of tectonic faults. It is based on the evaluation of four parameters: • Geotechnical analysis of drill cores • Geotechnical observation of the development face • Geotechnical classification of tectonic structures (faults) • Standard classification derived from geotechnical assessment and evaluation of stress conditions (using numerical modeling for stress calculation) ROCK STRENGTH One of the most important input parameters for describing strata conditions is the strength of the rock. The German classification system is based on a description of lithotypes. This method has been used successfully since the 1950s and is based mainly on the uniaxial compressive strength (UCS) of the material. An evaluation of the rock strength observed in a survey of approximately 82,500 samples of rock core yielded the results shown in Figure 1. The three most common coal measure rock types are mudstone, siltstone, and sandstone. Each shows a specific mean UCS level and a different spread between the minimum and maximum values. Sandstones, in particular, have a wide spectrum of compressive strength, ranging from approximately 40 MPa to greater than 130 MPa, with an average of 85 MPa. The causes of this wide range include different sedimento-logical preconditions, facies, and digenetic processes. [ ]

Jan 5, 2007

By Z. T. Bieniawski, Benjamín Celada

After emphasizing the importance of quantitative rock mass classifications in mining, originally directed to selection of rock support measures, but subsequently to estimates of rock mass properties such as rock mass strength and rock mass modulus of deformation, current attention calls for a classification specifically for rock mass excavability by tunnel boring machines (TBMs), which are used extensively in tunneling as well as in the mining industry. This paper introduces the Rock Mass Excavability (RME) index for predicting excavability of rock masses by TBMs using a quantification of machine performance and rock mass conditions. The RME index is based on five input parameters aimed at relating rock mass behavior and machine characteristics: (1) uniaxial compressive strength of the rock material, (2) drillability/abrasivity, (3) rock mass jointing at mine drift face, (4) standup time of the excavation, and (5) groundwater inflow. Development of the RME index entailed the collection of extensive data from more than 28 km of tunnels and some 400 case records from projects in Spain involving double-shield TBMs. In the process, a number of statistical correlations have been established between RME and such output parameters as degree of machine utilization, advance and penetration rates, thrust and torque of the cutterhead, and the specific energy of excavation. It was found that the RME index provides a particularly significant correlation for predicting the average rate of advance (m/day). In essence, the RME index is a classification system that features interaction of rock mass conditions with boring machine characteristics for use in the early stages of a project. It should be noted that the RME index does not replace the Rock Mass Rating (RMR) or Q-systems as used in mining and tunneling; indeed, one of the RME input parameters, standup time, is determined from the RMR. However, the approach presented introduces a specialized tool relevant to excavating tunnels and drifts. Possible applications to hard-rock mining are explored.

Jan 5, 2007

By Gabriel S. Esterhuizen, Jarek Jakubec

In 2000, Laubscher’s Mining Rock Mass Rating (MRMR) classification system was updated and published. The new system brought a few fundamental changes that were in direct response to the challenges and problems encountered when applying the classification system in the mining environment, specifically caving operations. The fundamental changes introduced into the MRMR system in 2000 were the abandonment of the Rock Quality Designation (RQD) as an input parameter, accounting for healed and cemented joints, and the concept of rock block strength. The objective of this paper is not to discuss the role and usefulness of classification systems; the fact that classification systems are widely used in every stage of mining projects speaks for itself. This paper discusses some of the experiences gained with the MRMR 2000 system in various mining projects and shows how the changes to the system have resulted in improved assessment of rock mass conditions. Issues related to core logging for rock mass assessment are also presented.

Jan 5, 2007

By R. Karl Zipf

A method is presented for creating realistic numerical models for practical coal mine ground control. The method includes procedures to collect the necessary mechanical input parameters from a geologic core log, procedures to set up a model, and procedures to interpret calculation results. The input parameters come from a detailed geologic core log and extensive point load tests of estimate rock layer strength. A suite of material property input parameters is proposed that allows the user to go from core log to numerical model inputs. Rock bolt anchorage properties are also linked to the material properties of each geologic layer in the model. Following this procedure leads to very realistic calculations of the rock failure process and rock support system behavior. These calculations in turn enable realistic comparison of the effectiveness of alternative rock support systems.

Jan 5, 2007

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 Max F. Lee, Warren A. Peck

The applicability of the Q-system [Barton et al. 1974] to Australian underground metal mines is discussed with reference to two common design issues: ground support for horizontal mine development, and assessing the stability of bored raises. Installed ground support in mine development is com-pared to empirical estimates using the Q-system and associated support capacity calculations. Data are graphically presented from 59 specially selected sites at 15 contributing mines. The actual performance of large-diameter raise-bored shafts is also compared to empirical stability assessments using a modified version of Q (Qr, after McCracken and Stacey [1989]). Lower-bound Qr values are plotted against raise diameter for 47 selected sites at 23 mines in Australia and Papua New Guinea. The influence on Q and Qr of some geotechnical aspects of the Australian landscape, the dynamic nature of mines (compared to civil construction), and occupational health and safety regulations are discussed. Stability and support assessments that are based just on Q or Qr are not always conclusive. It is often necessary to consider other rock mass parameters, the regulatory environment, and risk issues. These results are interim; further data collection and analysis are required with regard to comparing actual performance versus empirical assessments.

Jan 5, 2007

Rock mass classification is widely used throughout the underground mining industry—in both coal and hard-rock mines. It is used in all stages of the mining process, from site characterization to production operations. The goal of the International Workshop on Rock Mass Classification in Underground Mining was to provide a forum for leading practitioners of rock mass classification to come together and share their methods and experiences with the technique. The workshop was held in Vancouver, British Columbia, Canada, on May 31, 2007. It was co-chaired by Christopher Mark, Ph.D., P.E., National Institute for Occupational Safety and Health, Pittsburgh, PA, and Rimas Pakalnis, P.Eng., University of British Columbia, Vancouver, Canada. The proceedings of the workshop contain 16 invited papers from 9 countries, reflecting the international depth and breadth of current practice. Applications in both hard-rock and coal mining are well represented. Some of the topics that were addressed at the workshop include: • Major rock mass classification systems used in mining and their variants • Collection of input data through observation, rock testing, and geophysics • Design of mine layouts and rock support systems using classification • Estimation of rock mass strength and other input parameters for numerical models from classification • Applications in weak rock, raise boring, cavability assessment, and other special topics • Risk assessment using rock mass classification

Jan 5, 2007

By Terry P. Medhurst, Stuart A. MacGregor, Peter J. Hatherly

In addition to fractures and joints, compositional factors and bedding influence the strength of clastic sedimentary rocks. Rock mass rating schemes must therefore consider all of these factors. In this paper, a rating scheme for clastic sediments based on geophysical measurements is described. Geo-physical logging allows an approximation of rock com-position to be obtained and an assessment of bedding frequency and laminations. Velocity measurements incorporate the effects of fracturing. The rating requires scores for the intact rock, bedding/cohesion, and defects. These are combined to yield a Geophysical Strata Rating (GSR). Determination of the GSR is objective and repeatable. GSR values are typically between 20 and 80 and can be related to the Coal Mine Roof Rating.

Jan 5, 2007

By David Hill

The Australian underground coal mining industry has made extensive use of the Coal Mine Roof Rating (CMRR) classification system for a diverse range of purposes in recent years. These include mining method selection, and coal pillar and roof support design. This paper outlines a series of case histories, from large-scale feasibility studies to local support design investigations, that collectively illustrate the broad applicability, advantages, and usefulness of the methodology, as well as some of the current limitations. The key role of the CMRR in an overall hazard definition methodology is demonstrated for a major Australian project, and some ideas with regard to the future application of the CMRR, in the context of geotechnical risk management within a progressive, highly productive extractive industry, are put forward.

Jan 5, 2007

By Radford B. Langston, John A. Marjerison, Graham C. Howell, Hendrik A. D. Kirsten

Probabilistic design is gaining wider acceptance in the rock engineering community since it allows more rigorous determination of risk relating to ground fall or excavation instability. Risk analysis can be conducted by various means, but the basis is formed by either objectively or subjectively determining probability of occurrence of an event. In the case of rock engineering, this event is either instability or excavation failure. Rock mass classification systems provide objective analysis of data collected on a typically subjective basis that also relate closely to excavation stability. A probabilistic analysis technique is presented that uses statistical distributions of rock mass and material properties, ground support fixture specifications, stress conditions, opening geometry, and ground support installation quality to more rigorously determine probability of failure for an underground opening and the subsequent risk to personnel.

Jan 5, 2007

Multiple-seam interactions are a major ground control hazard in many U.S. underground coal mines. In some U.S. coalfields, particularly in central Appalachia and the West, the majority of today’s mines are operating above and/or beneath previously mined seams. The effects of multiple-seam interactions can include roof falls, rib spalling, and floor heave. These can seriously disrupt mining operations and threaten the safety of miners. In early 2006, a West Virginia coal miner was killed by rib roll that occurred in a high-stress zone beneath a remnant structure in an overlying mine. Fortunately, not every multiple-seam situation results in hazardous conditions. Indeed, the vast majority do not. For the past several years, the National Institute for Occupational Safety and Health has been conducting research to develop better techniques for predicting the location and severity of multiple-seam interactions. During this investigation, more than 50 mines were visited across the U.S. coalfields. Nearly 300 case histories were collected and analyzed using multivariate statistical techniques. The study also employed the numerical model LaM2D to estimate the multiple-seam stress, the Analysis of Longwall Pillar Stability (ALPS) and the Analysis of Retreat Mining Pillar Stability (ARMPS) programs to determine pillar stability factors (SFs), and the Coal Mine Roof Rating to measure roof quality. The study focused on the two most common types of multiple-seam interactions: • Undermining, where stress concentrations caused by previous full extraction in an overlying seam is the main concern; and • Overmining, where previous full extraction in an underlying seam can result in stress concentrations and rock damage from subsidence. The study confirmed that overmining is much more difficult than undermining, and isolated remnant pillars cause more problems than gob-solid boundaries. For the first time, however, it was possible to quantify these effects in terms of the equivalent thickness of interburden needed to compensate for them. The study also found that pillar design is a critical component of multiple-seam mine planning. Many of the failed cases involved pillars whose SF seemed inadequate once the multiple-seam stresses were accounted for. Weaker roof was also found to significantly increase the risk of multiple-seam interactions. The most important result of the study is an equation that predicts the critical thickness of the interburden required to minimize the likelihood of a multiple-seam interaction. This equation was incorporated into a step-by-step methodology that allows mine planners to evaluate each potential interaction and take steps to reduce the risk of ground control failure. Such measures could include installing cable bolts or other supplemental support, increasing the pillar size, or changing the mine layout to avoid the remnant structure entirely. These Proceedings also contain several previously published papers that cover other facets of multiple-seam mining research. Two papers describe the LaModel family of software developed by Professor Keith A. Heasley of West Virginia University. The LaModel programs were designed for calculating the stresses and displacements in coal mines or other thin, tabular seams in layered media. The original three-dimensional version of LaModel is essential for detailed analyses of complex multiple-seam scenarios. LaM2D, by contrast, implements a simplified two-dimensional model that is suitable for quick approximations of the multiple-seam stresses and strains. Three additional papers in these Proceedings describe the extensive multiple-seam experience of the Harris Mine, examples of extreme multiple-seam mining from the central Appalachian coalfields, and longwall mine experiences in Pennsylvania, West Virginia, and Utah. The final paper reports on a numerical modeling study that provided some insight into the mechanics of multiple-seam mining.

Jan 5, 2007

By Rimas Pakalnis, Andrea M. Ouchi, Thomas M. Brady, Mary M. MacLaughlin, Cristian Caceres, Paul Hughes

A major focus of ground control research presently being conducted by the Geomechanics Group at the University of British Columbia, Canada, in conjunction with the National Institute for Occupational Safety and Health’s (NIOSH) Spokane Research Laboratory, is the development of design guidelines for underground mining within weak rock masses. The study expands upon the span design curve for man-entry operations and the stability graph for nonentry operations developed at UBC by extending the application to weak rock masses. The original database has been augmented by weak rock mass information from mines throughout the United States, Canada, Australia, Indonesia, and Europe. The common factor in all of these mines is the presence of a weak back and/or walls. This paper expands on the North American database and how the design curves have been employed at mining operations throughout the world. The definition of a weak rock mass for this study has been defined as having an RMR76 under 45% and/or a Q-value under 1.0.

Jan 5, 2007

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 Murali M. Gadde, John A. Rusnak

Rock mass classification systems are extremely useful for site characterization and have been employed by the rock mechanics community for several decades. While empirical in nature, the classification systems provide a viable means to quantify the nature of rock mass, which is necessary for stability analyses. In U.S. coal mines, the Coal Mine Roof Rating (CMRR) is the most widely used classification system for several purposes, including sup-port selection, chain pillar design, assessing the stability of extended face cuts, etc. The Analysis of Roof Bolt Systems (ARBS) is an empirical method developed from the CMRR to guide selection of roof bolts as the primary support system in U.S. coal mines. In this paper, the experience of Peabody Energy in applying ARBS to sup-port design is discussed. In general, data from the Peabody mines show that ARBS predictions match well with field conditions. Peabody, however, does not use ARBS as the stand-alone methodology for support selection. Peabody uses a two-pronged approach in which the support requirement is initially estimated from the classification method, and then numerical modeling is used to select the proper reinforcement system. Such an integrated approach is necessary, as ARBS suggests only the “amount of steel” that may be used to support the roof and does not specify which type of roof bolt to use. A case study is used to demonstrate the usefulness of ARBS and Peabody’s integrated approach to support design. Also, the application of ARBS at several Peabody mines showed a very good correlation with support cost. The correlation indicated a direct relation between bolting cost and the ARBS value.

Jan 5, 2007

By Gregory M. Molinda

The Coal Mine Roof Rating (CMRR) was developed 10 years ago to fill the gap between geologic characterization and engineering design. It combines many years of geologic studies in underground coal mines with world-wide experience with rock mass classification systems. Like other classification systems, the CMRR begins with the premise that the structural competence of mine roof rock is determined mainly by the discontinuities that weaken the rock fabric. However, the CMRR is specifically designed for bedded coal measure rock. Since its introduction, the CMRR has been incorporated into many aspects of mine planning, including longwall pillar design, roof support selection, feasibility studies, extended-cut evaluation, and others. It has also become truly inter-national, with involvement in mine designs and funded research projects in South Africa, Canada, and Australia. This paper discusses the sources used in developing the CMRR, describes the CMRR data collection and calculation procedures, and briefly presents a number of practical mining applications in which the CMRR has played a prominent role.

Jan 5, 2007

By Jeremy P. Doolan, Leigh B. Neindorf, Geoff W. Capes

The development and use of rock mass classification tools have been a key component for improving stope design over the past 4 years at the Xstrata Zinc George Fisher Mine in northern Queensland, Australia. In 2003, stope extraction data from 3 years of open-stope mining provided an excellent situation to review the assumptions in the feasibility study. Extracted stope profile information, drillhole geotechnical data, underground observations, and oral and written communication were used to develop a thorough stope reconciliation performance database. With-out collecting the back analysis data and presenting the data in a usable format, engineers are left to debate opinion instead of engineered judgment. This can lead to biased and uninformed design parameter choices with the potential to repeat poor design. This paper demonstrates some effective, practical examples of empirical data collection where rock mass classifications tools were developed and used to create improved confidence in predicting stope stability and failure profiles. The work contributed to design changes that resulted in a reduction in stope hangingwall dilution and an increase in head grade while continuing to ramp up production from 2003–2005.

Jan 5, 2007

By Douglas Milne

Most empirical and numerical approaches to design in rock mechanics incorporate rock mass classification. Numerical design methods generally use classification values to calculate input parameters for stress-based failure criteria. Empirical methods use classification to allow comparisons between similar rock mass conditions, generally based on a graphical design technique that differentiates stable and failed opening geometries. Classification systems are the best tool available for assessing rock mass properties; however, there are problems with classification systems that should be high-lighted. Rock mass performance can only be realistically estimated by coupling a unique description of the rock mass with known loading conditions. Current classification systems cannot provide a unique classification value. The weightings applied to quantify rock mass properties for classification can result in significantly different rock masses having the same classification values. These weightings have been proven effective for tunnel design and support, but classification systems are now used for many more applications. Rock classification systems evolved from a quick and easy field tool for estimating tunnel stability and support requirements. The need for a rapid field tool means that rock mass classification is relatively insensitive to improved methods of measuring rock mass properties. Problems with classification systems and their application are highlighted in this paper. These problems must be recognized and documented before improvements can be made. An understanding of the evolution of classification systems and their application for both numerical and empirical design approaches is invaluable in highlighting current shortcomings.

Jan 5, 2007

By Paul G. Marinos, Vassilis Marinos, Evert Hoek

The Geological Strength Index (GSI) is a system of rock mass characterization that has been developed in engineering rock mechanics to meet the need for reliable input data related to rock mass properties required as input for numerical analysis or closed-form solutions for designing tunnels, slopes, or foundations in rocks. The geological character of the rock material, together with the visual assessment of the mass it forms, is used as a direct input for the selection of parameters for predicting rock mass strength and deformability. This approach enables a rock mass to be considered as a mechanical continuum without losing the influence that geology has on its mechanical properties. It also provides a field method for characterizing difficult-to-describe rock masses. Recommendations on the use of GSI are given and, in addition, cases where the GSI is not applicable are discussed.

Jan 5, 2007