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By Rainer Kahrger

This paper is a follow-up to the paper presented at the SME meeting in April of 1996. Since then, the El Abra facility has been started up, 9 months ahead of schedule, and has processed about 45 million tons of ore and produced over 700 million pounds of copper. For those unfamiliar with the El Abra materials handling and leaching facilities, a brief overview of the facility is provided. The paper will then deal in detail with such aspects of Conveyor 103, the long regenerative overland conveyor, including: actual running resistance starting and stopping procedures emergency brake test at 10,000 t/h Additionally, we shall take the opportunity to report on a catastrophic culvert collapse in October 1996, which stopped the conveyor abruptly at full speed and under high load condition, causing a belt breakage. We would like to use this opportunity to thank the management of El Abra and Cyprus Amax for providing assistance and allowing us to present this paper. The El Abra team deserves a great compliment for building this one billion dollar facility in record time in a remote area of a high-altitude desert with no existing infrastructure, and for bringing it so quickly up to full operating capacity. The El Abra management had to assemble a completely new operator team. Considering the above circumstances, it took a great effort by all involved to achieve success. The official performance test which was required by the lending banks was successfully concluded in November 1997.

Jan 1, 1998

By W. G. Pariseau

Conventional barrier pillars in underground coal mines are intended to protect mains and sub-main entries for relatively long periods of time. Inter-panel barrier pillars that may be used in especially deep coal mines, say, below 800 m (2,400 ft), are intended to protect longwall panel faces and adjacent panel entries for the life of nearby panels. Barrier pillar failures have serious consequences, especially when failure is sudden and catastrophic. Design of barrier pillars is thus of considerable importance to safety and efficiency of operations. Locally, failure occurs at the limit to elasticity when stress tends to exceed strength. Strength of rock is stress dependent, so an analysis of stress is central to rational design of barrier pillars. There are several approaches to stress analysis for coal mine pillar design that range from the simplified but popular tributary area method including variations that use empirical definitions of the tributary area (volume) to more sophisticated numerical methods such as the boundary element method and the finite element method. Despite ease of use, empirical methods are limited and always suspect when applied to conditions beyond their scope of definition, while boundary element methods do not generally include pillars in the solution domain. The finite element method is not so restricted and thus is a natural choice for conventional and inter-panel barrier pillar safety analyses. Caving of roof strata certainly affects the distribution of stress about longwall faces and nearby barrier pillars. Conventional wisdom that considers roof strata to respond as cantilever beams indicates the longer the span the greater are loads on longwall faces and face supports. Failure of roof beams, caving, shortens spans and relieves face and support loads. The same view is applicable to barrier pillars in that long roof spans outside of barrier pillars leads to higher pillar loads than short spans. Hence, caving should be beneficial to barrier pillar safety. However, the benefit may be small depending on the extent of caving and only in the form of a slight reduction in overburden weight transmitted to the barrier pillar, especially in case of inter-panel barrier pillars. FINITE ELEMENT MODEL Finite element models for stress analysis in rock mechanics are formulated in consideration of physical laws, kinematics, and material laws. These models meet the essential requirements for equilibrium of stress, satisfy strain displacements relations, and in a general sense, relate stress to strain through material laws, often referred to as constitutive relations. The last may be complex and replete with nonlinearities. A de facto engineering material law is the elastic model in the form of Hooke?s law for linear, homogeneous materials that may be anisotropic. A limit to elasticity is imposed by strength in the form of a failure criterion or yield function that accommodates triaxial stress states. Examples used in rock mechanics are the well-known Mohr-Coulomb (MC)criterion, the popular Hoek-Brown (HB) criterion, and the Drucker-Prager (DP) criterion. The first is linear in stress, while the second is nonlinear. Both do not include any effect of the intermediate principal stress. The last is also linear in stress but includes the intermediate principal stress. All show an increase in the major principal stress at failure with confining pressure. In the UT2/3 finite element programs, the failure criterion Y is a nonlinear, anisotropic form and is also the plastic potential [1]: [YJI=+ 11NYJI=+- (1) ] where N is an exponent, usually 2, and J2 and I1 are nonlinear anisotropic forms of the second invariant of deviatoric stress and the first invariant of principal stress. The form (1) reduces to DP when N=1and isotropy prevails. When Y = 1, the limit to elasticity is reached and plastic deformation is possible. The material constants that enter (1) are all computed from unconfined compressive, tensile, and, in case of anisotropy, shear strengths. These latter strengths may be estimated from conventional laboratory test data. Of course, joints in field-scale rock masses induce different values. How different is often a matter of conjecture. For comparative studies, laboratory rock properties seem adequate. Inelastic, that is, plastic behavior occurs with strain beyond the elastic limit. Strain hardening, ideal plasticity, and strain softening are possibilities. Ideally brittle behavior with complete loss of strength is an extreme form of strain softening [2]. Caving may also be considered as strain softening with a less drastic reduction of material properties. As intact roof strata fail, fall, and form a rubble pile below, a new material is formed with greatly reduced elastic moduli and strengths, say, 1/100th of the original intact moduli and strengths. From another viewpoint, caving is simply a natural cut and fill process. Input for stress analysis by the finite element method includes: 1. Preexcavation stress state 2. Geology (stratigraphic column) 3. Structure (major faults, joint sets) 4. Elastic moduli 5. Strengths, and specific gravities of each rock type 6. Excavation sequence Output from an analysis includes distributions of: 1. Stress 2. Strain 3. Displacement 4. Local factor of safety (element fs) The last is defined as the ratio of strength to stress and in view of the failure criterion (1), is the ratio [fsJstrengthJstress=] where the numerator is the maximum possible value and the denominator is the actual value of the square root of the second invariant of deviatoric stress. This invariant is a measure of shear stress intensity but also reduces to uniaxial tensile and compressive strengths as the case may be. An fs greater than 1 indicates an elastic state of element stress; a value of 1 indicates the limit to

Jan 1, 2009

By A. Yazadni-Chamzini

Considering the nature of open pit mines, harvest volume, it usually is required to remove a lot of waste to access to mineral planned grade. So, one of the most important part of open pit mines design, is waste dump site selection. Many factors are effective in waste dump site selection. These factors are sometimes in conflict with each other. So selecting the desired location for waste dump is a process complex and multi-criteria decision making. There are a variety of methods for decision making under complicated condition, such as fuzzy, Delphi, multi-criteria decision making and Expert system methods can be hinted. VIKOR method, which is one of the decision making multi criteria methods, is useful tool for decision-making. On the other hand with regard to uncertainty in decision-making, fuzzy approach is a useful tool for this purpose. This article has tried to select the best waste dump site in Sari Gunay Gold Mine by Fuzzy VIKOR. The results show that C position has a higher priority than other positions.

Jan 1, 2012

By Verya Nasri, Scott Thorburn

The City of Toronto and the Toronto Transit Commission (TTC) have conducted an Individual Environmental Assessment (EA) for a 6.2 km, 4-station underground extension of the Spadina Subway from Downsview Station to Steeles Avenue. This Environmental Assessment Study was performed in three phases including routes and general station locations, alignments and station concepts and detailed assessment of the effects of the undertaking. URS Canada Inc. has led the consultant team for this Study. The anticipated total duration of the project is approximately 6 years and its estimated total cost is about $1.4 billion. This paper presents the planning process of the project, the environmental and engineering challenges, and the measures taken to address them.

Jan 1, 2007

By Gordon T. Clark, James R. Struthers, Celal Kirandag

INTRODUCTION Project Background The Washington State Department of Transportation (WSDOT) hired the Seattle office of Parsons Brinckerhoff to lead a team of consultants to produce an Environ-mental Impact Study and perform conceptual and preliminary engineering. The pur-pose of the Alaskan Way Viaduct and Seawall Replacement project is to replace the existing earthquake damaged and aging viaduct and sea wall, adjacent the downtown waterfront of Elliott Bay, with structures that have improved earthquake resistance and that maintain or improve mobility and accessibility for people and goods along the existing corridor. With an estimated replacement cost over $4 Billion and construction duration exceeding 8 years, it is one of the largest transportation design projects on the West Coast of the United States today. Seattle, Washington is a city of over 2 mil-lion people in the Northwest corner of the United States. Ever since the Klondike Gold Rush in 1897, Seattle has been considered a departure point to Alaska. Because of this, the street along the waterfront was named the Alaskan Way in 1930. Alaskan Way Viaduct and Seawall The Alaskan Way Viaduct (AWV) carries State Route 99 along the shoreline of Elliott Bay through downtown Seattle and is a vital part of Seattle’s highway system. The viaduct carries approximately 110,000 vehicles per day or 25% of all north-south traffic through Seattle (Figure 1). It is 3.4 km (2.1 mile) long with 3 lanes in each direction and was constructed of cast-in-place reinforced concrete between 1952 and 1956. The wear and tear of daily traffic, salty marine air, and several earthquakes have taken their toll on the facility. Studies in the mid-1990s provided early evidence that the viaduct was nearing the end of its useful life. The viaduct’s increasing age and vulnerability was apparent by crumbling and cracking concrete, exposed rebar, weakening column connections and deteriorating railings. In early 2001, a team of structural design and seismic experts began work to determine whether it was feasible and cost-effective to strengthen the viaduct by retro-fitting it. In the midst of this investigation, a 6.8 magnitude earthquake shook the Puget Sound region (the Nisqually Earthquake, located 56 km (35 miles) from Seattle and deep below the surface) caused moderate damage to the reinforced concrete structure. WSDOT closed the viaduct for inspection and repairs intermittently for several days over a period of several months.

Jan 1, 2007

By Carmel Bofinger, Maureen E. Hassall, David Cliff, Eric Stemn

e Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

By Carmel Bofinger, Maureen E. Hassall, David Cliff, Eric Stemn

e Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

By Bhaskar B. Thapa

The design of the Caldecott 4th Bore, located along State Route 24 in Oakland, California, is based on the principles of the New Austrian Tunneling Method (NATM). Typical NATM initial support design practices used in Europe were adapted for this project to account for U.S. conditions and requirements, such as degree of experience with NATM construction, the prevailing contractual environment, and preferences for contractual simplicity. Key design features are: (1) support selection criteria based on ground behaviors and ground conditions; (2) a prescriptive design with allowance for support adjustments based on observations during construction; and (3) organization of support requirements into only four major support categories, while permitting some adjustment for variations in ground behaviors and conditions using a few subtypes and additional support measures.

By Hyung Jeek Kim, Jongmin Joo, Jonguk Kim, Jai-Woon Moon, Kyeong-Yong Lee

"Co-rich ferromanganese crusts (Fe-Mn crusts) distributed on seamounts in the western Pacific are potential economic resources for cobalt, nickel, platinum, and other rare metals in the future. Evaluation and selection of a mining site can be established based on abundance and grade of Fe-Mn crusts in the site as well as topography that should be smooth enough for mining operations. Therefore, acquisition of shipboard echo-sounding and acoustic backscatter data are prerequisite to the selection of potential mine sites in addition to visual and sampling operations. Acoustic backscatter data can be used to locate crust-covered areas on a regional scale with the understanding of acoustic properties of crust through its correlation with visual and sampling data.During an expedition that took place from January to March 2014, KIOST collected geophysical and geologic data to assess the resource potential for Fe-Mn crusts on three seamounts (guyots) in the Western Pacific. In OSM11, one of the three surveyed seamounts, three camera tows were performed to observe the distribution of Fe-Mn crusts on the summit and slopes of the seamount. Although sediments of various thicknesses generally cover most of summit region of OSM11, several regions with high backscatter signals occur on the periphery of the summit. The occurrence of Fe-Mn crusts, observed during the camera tows, on those high backscattered regions suggests that the backscatter signals of shipboard multi-beam sonar can reflect changes in the geology of the seafloor from sediment layer to Fe-Mn crust deposits. The Fe-Mn crust deposited around the summit region is worthy of notice because of its topographic characteristics, including shallow depth, flat or gentle inclined surface, and smooth relief, which are more suitable for mining operation compared to the flanks of seamount."

Sep 1, 2014

By Joel Lööw, Jan Johansson, Lena Abrahamsson

Industry 4.0 offers new possibilities to combine increased productivity with stimulating workplaces in a good work environment. Used correctly, digitalization can create attractive jobs in safe control room environments, which provide space for the employee’s full expertise and creativity. This is true also for the mining industry. But, to succeed, it is important to analyze the development from a worker’s perspective. What will happen to their work? What skills will be needed in the mine of tomorrow? We must also consider the risks, such as privacy issues, increased stress, and work-life boundaries. These questions must be understood if we are to create workplaces that can attract a young and diverse workforce to tomorrow’s mining industry. In this article, we try to illustrate what the new technology can mean for the individual miners. We formulate the notion of Mining 4.0 (Industry 4.0 in the mining industry), where we try to create an image of how the future might look from a miner’s perspective and how mining companies may navigate their way to a future that works for all miners. To illustrate the range of possible outcomes, we formulate two scenarios: one utopian and one dystopic. At the end of our article, we bring forward six recommendations that can be considered a beginning of a road map for the human side of Mining 4.0.

By Joel Lööw, Jan Johansson, Lena Abrahamsson

Industry 4.0 offers new possibilities to combine increased productivity with stimulating workplaces in a good work environment. Used correctly, digitalization can create attractive jobs in safe control room environments, which provide space for the employee’s full expertise and creativity. This is true also for the mining industry. But, to succeed, it is important to analyze the development from a worker’s perspective. What will happen to their work? What skills will be needed in the mine of tomorrow? We must also consider the risks, such as privacy issues, increased stress, and work-life boundaries. These questions must be understood if we are to create workplaces that can attract a young and diverse workforce to tomorrow’s mining industry. In this article, we try to illustrate what the new technology can mean for the individual miners. We formulate the notion of Mining 4.0 (Industry 4.0 in the mining industry), where we try to create an image of how the future might look from a miner’s perspective and how mining companies may navigate their way to a future that works for all miners. To illustrate the range of possible outcomes, we formulate two scenarios: one utopian and one dystopic. At the end of our article, we bring forward six recommendations that can be considered a beginning of a road map for the human side of Mining 4.0.

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By Helmut Westermayr, Michael Tergl

DESCRIPTION OF PROJECT Geographic Setting The Kops II plant is a pumped storage scheme of the hydroelectric power producer ‘Vorarlberger Illwerke AG’ which is currently under construction in the Austrian Province of Vorarlberg. The plant is located at the end of the Montafon valley and will be fed with water coming from the Silvretta mountain range (Figure 1) Description of Plant The Kops II plant shall be operated as a pumped storage plant with three highly flexible and quickly controllable power generating units. Each unit shall have a capacity of 150 MW and shall be equipped for both turbine operation and pump operation. The Kops II plant uses the existing Kops Lake as upper storage reservoir and the existing Rifa balancing reservoir as lower storage reservoir. All major plant components of the Kops II scheme are located below ground. Total investment costs areapprox. 360 million Euro. Construction Lots The construction works for the Kops II plant, which were subdivided into three lots, were launched in September 2004. It is planned that the first power generating unit shall go on line in the year 2007. The completion of the overall project and the operation start-up of the second and third unit are envisaged for the year 2008. Lot 1—Pressure Tunnel. The 5.5-km-long pressure tunnel forms the connection between the Kops Lake and the beginning of the pressure shaft. The tunnel was excavated by the use of a double-shield TBM. Lot 2—Pressure Shaft and Surge Chamber. The approx. 1.1-km-long pressure shaft was excavated by TBM, advancing from bottom to top. Featuring an inclination of80%, the pressure shaft overcomes a difference in height of approx. 700 m. Lot 3—Power House Cavern and Tailrace Structure. The power house cavern, which is being built approx. 150 m inside the mountain, forms the core of this plant. The power house is designed to accommodate three power generating units, and the transformer cavern is forseen to accommodate three transformer units. The tailrace structure serves the purpose of conveying the water to the lower storage reservoir during turbine operation and as water intake during pump operation (Figure 2).

Jan 1, 2007

By James J. Meadows, Jason D. Pampena, Emanuele G. Cauda, Lauren G. Chubb

Exposure to respirable crystalline silica (RCS) can cause serious and irreparable negative health effects, including silicosis and lung cancer. Workers in coal mines have the potential of being exposed to RCS found in dust generated by various mining processes. The silica content of respirable dust in one single mine can vary substantially over both time and location. The current monitoring approach for RCS relies on the use of traditional air sampling followed by laboratory analysis. Results generated using this approach are generally not available for several days to several weeks after sampling, and this delay prevents timely and effective intervention if needed. An alternate analytical method is needed to reduce the time required to quantify the RCS exposure of mine workers. The National Institute for Occupational Safety and Health (NIOSH) has developed a new method using commercially available portable infrared spectrometers for measuring RCS at the end of the sampling shift. This paper will describe the application of the new field-based RCS analytical process for coal mines, including the use of the new method with the existing Coal Mine Dust Personal Sampler Unit. In a case study conducted by NIOSH with a coal mine operator in West Virginia, field-based RCS analysis was completed at a mine site to evaluate the new technique. The RCS analysis results obtained by the field-based method in this case study showed sufficiently strong correlation with results obtained by the MSHA standard laboratory analysis method to allow the mine operator to use the field-based method for evaluating process improvements.

The schlieren technique describes an optical analysis method designed to enhance light distortions caused by air movement. The ability to visualize air flow has significant implications for analyzing underground mine ventilation systems, including the enhancement of surveys and models. Currently, traditional schlieren methods are impractical underground. Background oriented schlieren (BOS) provides a solution to this problem. BOS requires two primary components, a professional quality digital camera and a schlieren background. A schlieren background is composed of a varying contrast repetitive pattern, such as black and white stripes. This background allows the camera?s sensor to capture minor light diffractions, such as those caused by air flow. Although BOS shows great potential for ventilation analysis, sensitivity is an issue. This paper seeks to validate the BOS technique for imaging flow through a regulator by comparing BOS images with traditional schlieren images. This paper also outlines initial experimental efforts used for the validation.

Jan 1, 2011

By Steve Polegato, J. Coady Marsh, Gary Landry

The Donkin-Morien Mine in Cape Breton, Nova Scotia, has successfully completed the excavation of a 7.6m (25-ft) diameter access decline over a distance of 3.5km out under the Atlantic Ocean. The tunnel, completed in December 1984, was driven through a sedimentary sequence of sandstone, siltstone, mudstone and various gassy coal seams prior to intersecting the Harbour Coal Seam where development work will commence. The tunnel was driven by a Canadian prototype tunnel boring machine (TBM) manufactured by Lovat Tunnel Equipment, Inc., Toronto, Ontario. The 7.6m (25-ft) diameter full-face shielded TBM operated at various grades from 0-20%. This paper outlines the TBM design, excavation, support and backup system utilized in the drivage. Problems encountered and drivage rates will be addressed.

Jan 1, 1985

By R. E. Mclvor

This is an update of an original dissertation on this topic by Lavallee, McIvor and Stolovitch (1992). A step-by-step, technical procedure used to measure and improve the performance of plant grinding circuits was adapted into a training program. ?Systematic Design of Instruction? was applied to: ? Determine if training was a suitable way to deliver this new technology; ? Define the technical content of the program; ? Select program specifications based on learner and context characteristics; ? Design, create and test prototypes of the training modules; and, ? Establish a process for plant implementation. The training program covers numerous skills that are extremely valuable for plant personnel, not only in the grinding area, but also for many other parts of the plant. This paper describes how new skills are brought into the workplace through designed instruction can be an effective alternative to hiring during severe skilled labor shortages.

Jan 1, 2008

By J. Bertisen, G. Davis

Previous analyses of small samples of mining projects have found that feasibility studies tend to well under-estimate the actual capital costs of the project. Our review of 63 mining and smelting projects completed over 4 decades confirms that as-built capital costs are, on average, 25% higher than as estimated at the bankable feasibility study stage. There appears to be little attenuation over time of this bias in capital cost estimation, at first appearing to reflect an absence of learning on the part of the consulting engineer. We instead argue that this persistence of bias is intentional, driven by a scarcity of project financing and the need to inflate the project economics in a bid to secure financing. Around this intentional bias is a considerable amount of scatter. Roughly half of all projects’ as-built capita costs fall outside of the expected ±15% of the feasibility study capital cost estimate, even after allowing for intentional estimation bias. Cost overruns of 100% or more happen in roughly 1 out of 13 projects. The data reveal that a shifted lognormal probability distribution should be used when modeling mining project capital costs in a Monte Carlo analysis.

Jan 1, 2007

By James McNally, Adam Stremcha, John MacGregor

With 13.7km of TBM tunneling in Atlanta’s hard gneiss well under way, drill and shoot work continues on several sites throughout the city. In order for the City of Atlanta to meet the consent decree imposed by the federal government, an aggressive construction schedule was a necessity. Construction consists of two deep, large diameter tunnels, four construction shafts, a pumping station, one overflow shaft, three large intake structures, and two connecting tunnels. Due to the multitude of blasting insensitive urban environments, a high standard of seismic and air-overpressure criteria, coupled with time restrictions, was adopted for the project. At any given time, drill and blast operations were under way at four of the seven sites requiring a certain amount of coordination between the TBM excavation, surface work, and the forces of Mother Nature. This paper addresses the challenges faced and the techniques used to safely and successfully complete the rock excavation of the West Area CSO Tunnel and Pumping Station project.

Jan 1, 2007