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By J. Warmbrodt, D. Apel, D. Nutakor, L. Grayson, M. Hilgers

MinerSIM is an augmented reality system with integrated hypermedia that is suitable for training underground miners in the basics of using a jackleg drill to install rock bolts. While statistical evidence shows that rock bolting with such a drill has an inherent level of risk, it is conjectured that this can be mediated with adequate safety training outside of the actual mine environment using a variety of educational media including interactive three-dimensional images, games, animations, and videos to describe the mechanics of rock bolting and its principles. Ultimately, trainees will install rock bolts in an immersive environment mixed with real and virtual images generated via a gaming graphics engine. This paper will discuss considerations, implementation issues, and evaluation methodologies of the MinerSIM system.

Jan 1, 2007

By A. Noble

The design of separation circuits can be a complex, labor-intensive and costly process. While the engineer?s experience along with extensive data sets and simulation are crucial tools for determining the final solution, a more fundamental approach is suitable to compare preliminary options and reduce the number of potential alternatives. In light of this need, the authors have developed the Circuit Analysis Reduction Tool (CART?). This software package relies on the fundamental principles of linear circuit analysis; however, the solution methodology has been streamlined to automatically incorporate stream splitting and unique separation performance for each unit. The resulting tool allows preliminary analysis of circuit designs without the need of detailed feed characterization. In addition to the basic analytical approach, this paper supports the veracity of the methodology with several simulated examples for various separation models.

Feb 27, 2013

By William Gleason

The Society for Mining Metallurgy and Exploration (SME) has a long and proud history of being the world?s leading resource for the dissemination for technical information regarding the fields of mining and mineral extraction and processing. That reputation was met, and maybe even exceeded, with the programming for the Society?s 2014 Annual Meeting in Salt Lake City, UT Feb. 23-26. The meeting drew more than 6,700 attendees to the three-day conference that featured more than 90 technical sessions with 670 presentations. These sessions covered the breadth of the mining and minerals industry, but it was the so-called ?softer issues? that were discussed in the keynote session that kicked off the meeting. The keynote session, ?Community Engagement: Building Partnerships for Mining,? brought together some of the leading voices from the mining industry, as well as some of the top voices from nongovernmental organizations (NGOs) that work in the mining sector. The common ground between the panelists was their dedication to working to ensure a social, economic and environmental balance in the development of mines. ?We wanted to bring these NGOs in to begin a dialogue to see how we can work together,? said SME President Jessica Kogel. ?This is a space that SME has not typically operated in, but one in which SME can bring a technical, scientific voice to the discussion. SME wants to play a leadership role in creating partnerships between the technical, social and economic areas that are crucial to the success of any mining project.? In today?s environment, finding mineral deposits and extracting the minerals in an economically viable manner is just one piece of an increasingly complex puzzle. Earning and maintaining a social license to operate requires careful consideration of local and global impacts. The industry often comes under intense scrutiny when a new project is proposed and, therefore, it must strive to meet the highest ethical and environmental standards. Success requires cooperation and collaboration between the industry, community and NGOs.

By W. R. Reed

The National Institute for Occupational Safety and Health (NIOSH) uses light-scattering dust monitors (nephelometers) in its research to develop dust controls to reduce respirable silica dust overexposures in miners. Recently, the model 1500-pDR, an active nephelometer, was introduced by Thermo Scientific. Testing was completed to ensure compatibility with the metal/nonmetal mine dust personal sampling unit (M/NMDPSU). Results of testing demonstrated that gravimetric concentrations measured from the 1500-pDR are comparable to the gravimetric concentrations measured using the M/NMDPSU, without need for correction, under commonly observed dust loading conditions.

Jan 1, 2012

By Yuting Xue, Danqing Gao, Brijes Mishra

Heterogeneity and discontinuity significantly affect rock strength. For accurate stability prediction, intact rock behavior is imperatively included in rock mass behavior. However, past research largely used arbitrary scaling approaches to produce rock strength. This paper considers a stochastic approach in order to determine the strength of a rock. Based on the laboratory data, a MATLAB® with extreme value stochastic model generates a database for each physico-mechanical property. Then FLAC® simulates laboratory-sized rock specimens. The grids developed in the numerical model can in turn develop random material properties in MATLAB®, which researchers then applied to the final FLAC® model. Model runs simulate the approach performed in the laboratory. The results from the model indicate that a stochastic approach produces strengths that are lower than a deterministic approach. Failure modes for each specimen are different, similar to observations in the laboratory. In addition, random density also influences the failure mode, highlighting the importance of stochastic analysis in rocks.

By Yuting Xue, Danqing Gao, Brijes Mishra

Heterogeneity and discontinuity significantly affect rock strength. For accurate stability prediction, intact rock behavior is imperatively included in rock mass behavior. However, past research largely used arbitrary scaling approaches to produce rock strength. This paper considers a stochastic approach in order to determine the strength of a rock. Based on the laboratory data, a MATLAB® with extreme value stochastic model generates a database for each physico-mechanical property. Then FLAC® simulates laboratory-sized rock specimens. The grids developed in the numerical model can in turn develop random material properties in MATLAB®, which researchers then applied to the final FLAC® model. Model runs simulate the approach performed in the laboratory. The results from the model indicate that a stochastic approach produces strengths that are lower than a deterministic approach. Failure modes for each specimen are different, similar to observations in the laboratory. In addition, random density also influences the failure mode, highlighting the importance of stochastic analysis in rocks.

By David C. Girard, Larry Williamson, Leonard R. Benson, Ronald E. Bizzarri

On the east side of Washington DC, the DC Water & Sewer Authority is developing a Facility Plan for the Anacostia River CSO Control Projects, including 8 to 12 miles of CSO storage/conveyance and flood relief tunnels and associated facilities. The project includes major technical and non-technical challenges, including: completion under a Federal Consent Decree schedule; large diameter (estimated 25 to 35 ft) soft ground tunnels and shafts up to 200 ft depth; operations without use of active flow control systems; and close coordination with several major public and private construction and development projects that are being advanced in the project area.

Jan 1, 2007

By Paul B. Queneau

Formulation and commercial utilization of solid-waste incinerator slag by-product is the focus of this paper. Particular attention is given to iron aluminosilicate melts having compositions similar to that of nature's basalt The earth?s crust can be viewed as an environmental laboratory for predicting stability of various silicates; small-scale laboratory experiments are necessary to confirm findings there from. An ideal slag consumes flux additives at acceptable cost, is compatible with furnace refractory, flows readily from the furnace, and has physical properties suitable for its commercial utilization -all within the critical constraint that the slag is environmentally stable. Examples of successful solid waste slagging practice, including tonnage, utilization and pricing, are provided from metallurgical and waste treatment operations of North America. Western Europe and Japan.

Jan 1, 1991

By B. Samanta, S. Bandopadhyay

Ore grade modeling of a placer gold deposit is considered a challenging problem even today. Typically, gold-bearing deposits show extremely erratic and unpredictable grade variation. This is principally because of isolated occurrences of gold metal within a few high-grade pockets. Because of sporadic fluctuation of high-gold-grade distribution, the overall spatial continuity of the deposit becomes poor. This type of variation is often described by a lognormal or highly skewed frequency distribution, and the spatial continuity of the deposit is characteristically represented by a variogram model that exhibits a high nugget component. Further complicating the matter is the sparse availability of drillholes to capture such erratic variation. Due to the prohibitive cost of drilling, gold grade and reserve estimations are typically carried out using insufficient exploratory data. Use of a traditional estimation technique on limited data often produces an unreliable ore grade model. Kriging and its nonlinear variation, lognormal kriging, are frequently used in gold deposit modeling (Rendu, 1979; Journel, 1980); however, kriging is flawed by the smoothing effect. Moreover, though kriging is known to be globally unbiased, it is not free from conditional bias. As a result, if a deposit is modeled using the traditional kriging technique, a high-grade zone can be predicted to be a low-grade zone and vice versa. Predicting high grade as low grade results in a missed opportunity to exploit profitable ore. On the other hand, prediction of low-grade ore as high-grade ore might result in financial loss for a mining operation. Thus, the use of kriging for ore grade mapping of a gold deposit may not be recommended. Estimation techniques (including kriging) can produce an estimate with minimum error in a minimum-error variance sense. However, no matter which estimation technique is used for grade modeling of a highly erratic deposit like gold, the error margin is bound to be high. Therefore, any grade prediction made for an unknown location is associated with high uncertainty. Since various mine-planning operations, including derivation of grade tonnage curve, pit design and economic analysis of the deposit, are based on estimated grade rather than true grade, a mining project evaluation that depends upon estimation will be subject to considerable risk. Thus, the successful design of a mining project not only depends upon accurate grade estimates, but also upon accurate assessment of uncertainty, for predictive grade is equally important. Although the kriging standard deviation is used as an indicator of uncertainty for prediction, it is flawed by characteristics related to a data-independence property. This study, therefore, investigates the stochastic simulation technique of conditional simulation for ore grade modeling of a placer gold deposit at Nome, Alaska. It is expected that the research will provide a better solution to ore-grade deposit modeling than the kriging technique because (1) conditional simulation preserves spatial continuity as well as reproduces the data histogram, thus avoiding the smoothing problem; and (2) generation of multiple realizations helps to accurately quantify the uncertainty about grade values in the deposit.

Jan 1, 2009

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 Meisam Ghiasi, Mohammadreza Khalesi, Mahmoud Abdollahy

In the current research, isothermal experiments of kinetic analysis were performed at different temperatures (800–1050 °C) and particle sizes (885 to 10,763 μm) to investigate the calcination kinetics of high-purity limestone. Thermal analyses were carried out in a zirconia crucible, 1 cm in height, for different temperatures and particle sizes. The reaction rate coefficients were varied in the 2.2 × 10−5-1.62 × 10−3-m0.6.s−1 range. Moreover, various isothermal kinetic analysis methods were applied to assess the decomposition mechanism and the calcination function governing the process. The modified shrinking core model was found as the best representation of the high-purity limestone kinetic data. The activation energy was evaluated using the Arrhenius curve, and an average value of 86 kJ.mol−1 was obtained.

Sep 15, 2020

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

Flawed mining studies have been major contributors to poor investment decisions in mining for many years, contributing to the long period of poor industry profitability. Most of the major mining houses have now adopted quite formal processes and quality standards for mining studies to reduce the potential for poor investment decisions in the future. Other organisations such as the World Bank also have specific requirements for particular types of studies, such as bankable studies. This increasing requirement for rigour and discipline means a highly structured and phased sequence of studies is now required along with the development and adoption of industry-wide standards in mine ventilation studies. New terms in the study process such as ?independent peer review? and ?hold and review? are assisting in this process. More traditional terms such as ?feasibility study? and ?pre-feasibility study? now have much more precise technical definitions. Specific standards for the ventilation components of the various phases of a mining study are proposed in this paper.

Jan 1, 2009

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 D. Brün, T. W. Nattkemper, T. Kuhn, T. Schoening

Underwater exploration for marine resources using camera-equipped devices (OFOS, ROV, AUV) is receiving growing attention. This development is creating a continuously growing pile of digital underwater images leading to a serious bottleneck in the analysis. However, any harvesting strategy must be coupled to an efficient and effective assessment of the biodiversity in the area of interest and in nearby control areas. To integrate manual image and computational image interpretation on different levels (i.e. regarding geology and environmental sciences and taxonomy), sophisticated software support is required, which is not yet offered explicitly, neither by commercial software companies nor by academic or other publicly founded institutions. Here, we present the first version of a new digital asset management system that offers functionalities for easy data management, sharing, manual annotation and integration of computational modules for image enhancement/pre-processing and interpretation. The functionality is demonstrated with data from the CCZ provided by the BGR Hannover.

Sep 1, 2014

By Adam Shang Robert Fu

The Yung-Chung-Tunnel in Taiwan, constructed for the Taiwan-East Railway Bureau, collapsed during construction when a water bearing, fractured marble zone was intersected. The inflow was approximately 4,000 liters/second. In spite of 30 relief holes the total inflow into the tunnel remained constant. The pre-excavation grouting through the re-aligned tunnel had to be conducted under extreme flow-conditions. A hot bitumen grouting program was selected for technical and economical reasons out of 13 international proposals. The technical challenges were: grouting under severe flow conditions high formation water pressures to be injected with hot bitumen at high temperatures and pressures The hot bitumen grouting program resulted in a dramatic reduction in the hydraulic conductivity and stabilization of the formation and facilitated a problem-free excavation.

Jan 1, 2007

By R. R. Oder, R. E. Jamison, E. D. Brandner

This paper presents the preliminary test results obtained using a 0.38-kg/s (3,000-lb/hr) beta prototype MagMill. In processing Upper Freeport coal, the beta prototype recovered 82 % of the weight of the feed and 91 % of the heat content while reducing the potential emissions of sulfur by 61%. Pyritic sulfur in the MagMill product was reduced by 78% compared with that in the feed. For all runs, the mill product particle size was controlled to between 70% and 80% -741m (200 mesh). Recoveries of mercury, arsenic and selenium ranged from 35% to 45% of the amounts found in the feed. Power draw was reduced by 26%, and mill throughput was increased by 9% compared to the pulverizer operating with no magnetic separator attached.

Jan 1, 2002

Mining steeply dipping coal seams is a difficult task in the mining industry. Prior to 1996, fully mechanized longwall mining methods along the seam strike direction were tried in China and other countries. Due to its larger coal reserve in steep seams, China made more but still limited progresses on mining in such seams than the other major coal-mining countries. In the last two decades, accelerated research efforts have been made to improve the mining technology in steeply dipping coal seams. Based on these works, a dynamic model of ?R-S-F? system under asymmetrical constrains in mining steep seam is established and the theory of strata control and hazard prevention begin to be formed. The key technologies for mining steep coal seams include: global and regional strata control methods in longwall face, methods for the longwall face machines to sustain static and dynamic loads, and flexible protection technology. These theory and technologies have been successfully applied to mining of steep coal seams of varying thickness and hardness, with hard and soft roof and floor, and with high potential of spontaneous combustion in China. In the recent years, the technology has been introduced to Russia, India, Uzbekistan and other countries where steep coal seams are mined.

Jan 1, 2012

By William F. Daly, William H. Hansmire

Installation of initial tunnel support is often the most uncertain element of work in the design of, and a contractor bidding on, construction of a rock tunnel. The risks the construction contractor and owner assume are delineated to a great extent in the technical specifications portion of the contract documents. It is intended that this paper identify current practices for specifying initial tunnel support and the impacts each case has on the assignment of risks associated with providing the initial tunnel support. Examples of recently completed tunnel designs are given.

Jan 1, 1985