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By A. Yadav, B. Behera, G. S. P. Singh

The size of chain pillars in the Indian geo-mining conditions is primarily decided in accordance with the regulatory provisions. These provisions are of little help for deep longwall workings, exceeding the cover depth of 360 m. Furthermore, these provisions are primarily meant to support pillars in bord and pillar workings. They may not be suitable for the chain pillars owing to a significant difference in layouts and functional requirements. Hence, it is imperative to develop a method to evaluate the stability of the chain pillar considering the complex loading and geo-mining conditions. To this end, a machine learning-based model was developed in this study to assess the stability of the chain pillars under high depth of cover considering the field-representative conditions. The data for this work was generated by conducting a parametric study using a field-validated numerical model. The strength and deformability parameters of the caved, fractured, and continuous deformation zones were established by calibrating the numerical model outcomes against the site-specific field observations. The developed ML model was used to evaluate the influence of pillar width, pillar height, cover depth, abutment angle, face length, coal strength, moduli ratio of the roof and floor strata to the coal seam, and the elastic modulus and unit weight of the overburden on the chain pillar stability. An interesting finding of this study showed that the factor of safety of the chain pillar increased with the increasing abutment angle, which may be indicative of the confining effect of the abutment angle on the pillar. Eventually, the ML model was verified by comparing its outcomes with the calibrated numerical model for a typical longwall working from Indian geo-mining conditions.

Oct 18, 2023

By William Gleason

"Sluggish prices for commodities and a glut of oversupply of many commodities did not stop the world’s largest mining equipment makers from showing off their latest and greatest machines and technology starting with the world’s largest equipment trade show, bauma 2016 in Munich, Germany.From April 8-14, an estimated 580,000 visitors from 200 countries visited the show that featured 3,423 exhibitors from 58 countries. While primarily a show for construction equipment, the mining footprint has grown over the years. Among the largest exhibits was that of Liebherr, which brought more than 100 products, had an outdoor exhibition stand, a stand for the components division and a career stand under the motto “Be Part of Something Bigger.” One of the biggest aspects of the exhibit was its mining products where the company staged the first-ever professional table tennis match in the 130 m3 (170 cu yd) dump body of the T 264 mining truck. The top German players Timo Boll and Patrick Franziska with their trainer Jörg Robkopf faced Austria’s singles world champion from 2003, Werner Schlager, and the reigning Team Europe champions Chen Weixing and Stefan Fegerl.“Bauma 2016 was an absolute success for Liebherr. With this year’s appearance we were once again able to show our innovative strength, performance and technological diversity to a very large and international audience from the industry. We conducted interesting discussions with numerous customers and partners from various countries and discussed new projects,” said Stefan Heissler, Member of the board of directors of the Liebherr Group.Likewise, Caterpillar, the world’s largest maker of construction and mining equipment had a large presence at the show with more than 60 products and 12,000 m2 (129,000 sq ft)of exhibit space. Among the iconic yellow mining equipment that was on display was the 6015B hydraulic mining shovel."

Jun 1, 2016

By Kasimcan Koruk, Julian M. Ortiz

Building a geological model is important in resource estimation, as it defines the extent of domains for estimation. Geological models are built by assigning a domain to the samples, based on logging of different features related to lithology, alteration, and mineralization. Then, the extent of these domains is determined using geometric or geostatistical tools. However, these models should account for uncertainty, since the actual extent of these domains is not known and must be extrapolated from the labelled samples. With the availability of geochemical datasets and machine learning techniques, employing multiple variables to build resource models should be considered. This article proposes a two-step machine learning approach with an ensemble implementation to define geological domains and their uncertainties. First, an unsupervised binary clustering method labels the geochemical samples into two domains. These labelled samples are used to inform a geological domain model built by support vector classification. This application is repeated with subsets of variables and subsets of samples, leading to an ensemble learning method. Weak models are produced with each subset of samples and variables, and combined to devise a stronger learner. The final model accounts for uncertainties thanks to the ensemble implementation. The proposed workflow is demonstrated on a dataset from a porphyry copper deposit, applied hierarchically to define four domains. Performance is comparable with traditional methods, but provides the advantage of allowing domain knowledge in the selection of the variables, and generates domain boundaries that can be controlled in terms of their continuity and smoothness.

Oct 11, 2023

By N. Dhawan

With ever-increasing demand, low-grade complex ores and strict environmental regulations, metallurgical processing options have become limited. Heap leach technology provides several benefits to combat these issues including low cost, flexibility and diversified process conditions. This paper provides an overview of heap leaching technology with specific emphasis on chemical aspects. Hence, influencing factors, advantages and disadvantages, testing approaches and some fundamentals will be discussed. Finally, heap leach technology for different ore types (copper, nickel, uranium and gold) will be briefly compared.

Jan 1, 2012

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

By John Marsden, Mike Botz

A variety of modeling techniques can be utilized to forecast metal production at heap leaching operations. These approaches reflect a wide range of complexity, flexibility, time to implement, cost, and accuracy. For many operators, a spreadsheet-based modeling technique is attractive since the calculations are directly accessible, models can often be developed by site staff, and the results are generally easy to extract and interpret. The authors have developed a spreadsheet-based modeling technique that provides a high degree of flexibility, while still considering detailed operating information for ore properties, leach kinetics, scaleup factors, lift height, and in-heap metal inventories. The technique involves establishing kinetic leach curves for each ore type to characterize metal extractions, followed by application of separate metal recovery curves to define the rate at which leached metals exit the heap in pregnant solution, taking into account delays due to the in-heap solution inventory. At any point in time, the difference between total metal extracted and total metal recovered is equal to the in-heap inventory of the leached metal. This modeling technique is particularly useful for larger multi-lift heaps where delays in metal recovery are appreciable due to in-heap solution holdup. The technique is also applicable to sites with multiple heaps, leach cycles, and/or metal recovery plants (e.g., carbon columns for gold; solvent extraction for copper). This paper describes the modeling technique, including input data required and methods for defining kinetic leach curves and metal recovery curves. The technique is compared against an alternative spreadsheet technique using a simplified in-heap solution inventory calculation to forecast metal production, which has proven to be effective at a number of sites.

Sep 3, 2019

By L. Sandbak

The TRJV Mine is located approximately 43 miles northeast of Winnemucca, along the east flank of the Osgood Mountains in the Potosi Mining District, Humboldt County, Northwest Nevada (see Figure 1). The Turquoise Ridge Mine is an underground mine, and is a 25% joint venture partner with Newmont Mining. The TRJV mine utilizes the underhand cut-and-fill mining method due to the relatively low rock quality in the ore zones and the relatively shallow dipping 25-45 degree ore body geometries. This paper defines a rehabilitation risk rating system (RRRS) for prioritizing rehabilitation of drifts damaged in the mining processes including long term development drifts providing access to the mining areas. The ultimate use is as a mine planning tool for the organized scheduling of rehab in a timely manner. A few case studies of the most needy rehab areas identified by the RRRS mapping system is presented, and the type of rehab completed design for these areas. Suggestions on improving the rehab risk mapping system include the use of support history and rock mass strength rating factors.

Feb 23, 2014

By Nilabjendu Ghosh, Satyendra Kumar Singh, Gautam Banerjee, Harshit Agrawal

High-production methods like longwall mining with hydraulic powered supports are necessary to increase underground coal production in India. Longwall mining had a mixed success record for Indian geo-mining conditions. In this paper, an analysis is presented to optimally design an array of chain pillars in multi-seam longwall mining panels in the deepest coal mine in India. The study found that a chain pillar of 80-m width and 195-m length is necessary for long-term stability without any reinforcement. It was also observed that an optimum chain pillar can be designed by providing suitable side reinforcement (side bolting) which will reduce the chain pillar dimensions to 55-m width and 160-m length. Optimum design of chain pillars will reduce the coal locked up in these chain pillars by ~ 77%. This will also reduce the gestation period of longwall mining panel development. This paper also evaluates the maximum tensile subsidence strain induced at the surface and finds that the values are within the safe working limit of 3 mm/m. Thus, this paper finds direct application in the design of future multi-seam retreating longwall mining panels in Indian geo-mining conditions.

By Nilabjendu Ghosh, Satyendra Kumar Singh, Gautam Banerjee, Harshit Agrawal

High-production methods like longwall mining with hydraulic powered supports are necessary to increase underground coal production in India. Longwall mining had a mixed success record for Indian geo-mining conditions. In this paper, an analysis is presented to optimally design an array of chain pillars in multi-seam longwall mining panels in the deepest coal mine in India. The study found that a chain pillar of 80-m width and 195-m length is necessary for long-term stability without any reinforcement. It was also observed that an optimum chain pillar can be designed by providing suitable side reinforcement (side bolting) which will reduce the chain pillar dimensions to 55-m width and 160-m length. Optimum design of chain pillars will reduce the coal locked up in these chain pillars by ~ 77%. This will also reduce the gestation period of longwall mining panel development. This paper also evaluates the maximum tensile subsidence strain induced at the surface and finds that the values are within the safe working limit of 3 mm/m. Thus, this paper finds direct application in the design of future multi-seam retreating longwall mining panels in Indian geo-mining conditions.

By D. Chakravarty, G. Samanta, B. Samanta

The present study highlights the planning and design aspects of a well-known openpit copper deposit in India. The mine has been operational since 1982 and presently reaches a depth of 168 m below the surface. The present planning effort has been given due consideration in view of the recent upsurge of copper prices in the global market. The prime focus of the study has been directed towards examining the possible extent of final pit beyond the current pit outline and generating an extraction sequence of future mining operations. To this end, an orebody model of the deposit has been developed and the optimized pit has been derived using L-G 3D algorithm. A sensitivity analysis has also been performed to scrutinize the possible effects of the changing economic scenarios on the ultimate pit configuration. It has been observed that with the current production rate, mine life can be extended another 40 years. With a five-year production plan, these materials can be extracted in eight push-back schemes. The extraction sequence of these push-backs has been outlined in this paper.

Jan 1, 2011

By Michael McNinch, LaTasha R. Swanson, Jennica L. Bellanca, Justin Helton

Accident data indicates that mobile haulage poses a significant pinning, crushing, and striking risk. Proximity detection systems (PDSs) have the potential to protect mineworkers from these risks. However, unintended consequences of mobile PDSs can undermine the safety benefit they provide. Soliciting iterative user input can improve the design process. Users help provide a critical understanding of how mobile PDSs may hinder normal operation and endanger mineworkers. Researchers explored users’ perspectives by conducting interviews with mineworkers from seven mines that have installed mobile PDSs on some of their haulage equipment. Mineworkers reported that mobile PDSs affect loading, tramming, section setup, maintenance, and general work on the section. Mineworkers discussed the operational effects and increased burden, exposure, and risk. Mineworkers also suggested that improved task compatibility, training, logistics, and PDS performance might help address some of these identified issues. This paper also gives additional insights into mobile PDS design and implementation.

By Michael McNinch, LaTasha R. Swanson, Jennica L. Bellanca, Justin Helton

Accident data indicates that mobile haulage poses a significant pinning, crushing, and striking risk. Proximity detection systems (PDSs) have the potential to protect mineworkers from these risks. However, unintended consequences of mobile PDSs can undermine the safety benefit they provide. Soliciting iterative user input can improve the design process. Users help provide a critical understanding of how mobile PDSs may hinder normal operation and endanger mineworkers. Researchers explored users’ perspectives by conducting interviews with mineworkers from seven mines that have installed mobile PDSs on some of their haulage equipment. Mineworkers reported that mobile PDSs affect loading, tramming, section setup, maintenance, and general work on the section. Mineworkers discussed the operational effects and increased burden, exposure, and risk. Mineworkers also suggested that improved task compatibility, training, logistics, and PDS performance might help address some of these identified issues. This paper also gives additional insights into mobile PDS design and implementation.

By G. W. McMahon

Following the Sago Mine accident, the U.S. Mine Safety and Health Administration (MSHA) asked the U.S. Army Engineer Research and Development Center to study several possible methane explosion scenarios in the Sago coal mine. The study used a 0.3-m (1-ft) resolution map of the mine to produce a 3-dimensional (3 D) model of a portion of the mine, including the sealed area where the explosion occurred. An advanced 3 D computational fluid dynamics (CFD) code was used to calculate the explosion pressures within the sealed area, on the mine seals and in nearby regions of the mine. Based on the best available information on methane concentrations and assumptions on homogeneity and on layering and mix composition, three separate initial conditions of methane-air concentrations and location were studied. This paper discusses the CFD modeling technique, the results of the calculations, the challenges of conducting this type of modeling and the advantages and limitations of CFD modeling of accident investigations of mine explosions.

Jul 1, 2010

By E. Nickel

"Bi- and multilateral banks as well as export credit agencies in the OECD countries, but also numerous commercial banks, last year committed themselves to compliance with the World Bank’s standards. These environmental and social guidelines, also known as the Safeguard Policies, are the strictest international standards in the area of financing of major investment projects. The Safeguard Policies are procedural and quality guidelines by means of which socially and environmentally relevant impacts can be taken into account in the planning and implementation phase of a project. Objectives of the Bank Safeguard Policies are to ensure that environmental and social issues are evaluated in decision-making, to reduce and manage risk of projects and programs, and to provide a mechanism for consultation and disclosure of information. They are often referred to as the "10+1 Safeguard Policies," since ten of the guidelines address environmentally and socially relevant issues, while one guideline is exclusively concerned with public participation ("Public Disclosure"). In the presentation, the transparency of risk management measures and emergency response plans in pipeline projects will be discussed as an indicator of sustainability. The discussion is to be carried out on the basis of the results of an evaluation of several major pipeline projects, which have been financed at least in part by multilateral banks over the past few years. The controversies surrounding some of these projects due environmentally and socially relevant impairments connected with the investments have also been addressed by the Extractive Industry Report of the World Bank. Pipeline construction was the investment type chosen for the examination to be presented here, since pipelines frequently start in remote, unspoiled regions, and their routes often cross various natural zones and areas with various social structures. The question of safety during construction and operation of the line is always central to these projects; not only for the responsible authorities but also for other societal groups involved, such as environmental associations."

Jan 1, 2005

By Jacob Carr, Christopher C. Jobes, Chenming Zhou, LaTasha R. Swanson, Jennica Bellanca, Jingcheng Li

Magnetic proximity detection systems (PDSs) are used with continuous mining machines (CMMs) to protect miners from striking and pinning accidents. Generators are used in a PDS to create magnetic fields covering the space around a CMM. The PDS determines the proximity of a miner relative to the CMM based on the magnetic flux density detected by a miner-wearable component (MWC) and simultaneously alerts the miner and stops the motion of the CMM if the miner is within a proximity that creates a striking hazard. A stable magnetic field is essential to the accuracy of the proximity calculations performed by the PDS. This paper presents the results of a systematic study of the magnetic influence of two types of steel structures found near a CMM— the body of the CMM itself and the wire mesh used for roof and rib control. The results show that the steel of the CMM body can change the magnetic field distribution and also alter electrical parameters of a PDS by changing its generator current. The study also shows that, depending on the distance between the wire mesh and a generator, the magnetic field can also be altered.

By Jacob Carr, Christopher C. Jobes, Chenming Zhou, LaTasha R. Swanson, Jennica Bellanca, Jingcheng Li

Magnetic proximity detection systems (PDSs) are used with continuous mining machines (CMMs) to protect miners from striking and pinning accidents. Generators are used in a PDS to create magnetic fields covering the space around a CMM. The PDS determines the proximity of a miner relative to the CMM based on the magnetic flux density detected by a miner-wearable component (MWC) and simultaneously alerts the miner and stops the motion of the CMM if the miner is within a proximity that creates a striking hazard. A stable magnetic field is essential to the accuracy of the proximity calculations performed by the PDS. This paper presents the results of a systematic study of the magnetic influence of two types of steel structures found near a CMM— the body of the CMM itself and the wire mesh used for roof and rib control. The results show that the steel of the CMM body can change the magnetic field distribution and also alter electrical parameters of a PDS by changing its generator current. The study also shows that, depending on the distance between the wire mesh and a generator, the magnetic field can also be altered.

By Shanming He, Jinliang Wang, Xiaoming Wang, Chunfa Liao

Large amounts of manganese-rich slag were generated from smelting low-grade manganese ore containing high iron and high phosphorus in electric furnace or blast furnace, which contain 25–40 mass% Mn. This paper describes an efficient hydrometallurgical process for the utilization of high manganese slag instead of conventional usage of pyrometallurgical route for manganese recovery. Pressure acid leaching of manganese-rich slag using air as pressurized gas is studied systematically. The effects of mass ratio of manganese-rich slag to pyrite, concentration of sulfuric acid, leaching temperature, partial air pressure, leaching time, and liquid-solid (L/S) ratio on the separation of manganese with other main impurity components were investigated comprehensively. Under the following optimal process conditions, weight of manganese-rich slag powder,100 g; mass ratio of manganese-rich slag to pyrite, 20:1; sulfuric acid concentration of 140 g/L; air pressure of 0.6 MPa; leaching temperature of 140 °C; leaching time of 1 h; L/S of 7:1; ore size of 75–80 μm; and stirring rate of 600 rpm, the extraction rate of Mn reached 94%, and the dissolution percentage of Si, Al, and Fe are as low as 2%, 6%, and 10%, respectively. The leaching slurry presented a good solid-liquid separation characteristic. The silicic acid formed during sulfuric acid leaching manganese silicates was converted to filterable dehydrated SiO2 particles which precipitated in the residue under the condition of higher temperature with higher pressure. The effect of adding pyrite may be to reduced iron ions and decreased the output of iron hydroxide colloid and also reduced MnO2 to manganese sulfate in sulfuric acid leaching. Thus the formation possibility of colloid such as silica gel and iron hydroxide was decreased, and higher yield of manganese sulfate could be achieved.

By Shanming He, Jinliang Wang, Xiaoming Wang, Chunfa Liao

Large amounts of manganese-rich slag were generated from smelting low-grade manganese ore containing high iron and high phosphorus in electric furnace or blast furnace, which contain 25–40 mass% Mn. This paper describes an efficient hydrometallurgical process for the utilization of high manganese slag instead of conventional usage of pyrometallurgical route for manganese recovery. Pressure acid leaching of manganese-rich slag using air as pressurized gas is studied systematically. The effects of mass ratio of manganese-rich slag to pyrite, concentration of sulfuric acid, leaching temperature, partial air pressure, leaching time, and liquid-solid (L/S) ratio on the separation of manganese with other main impurity components were investigated comprehensively. Under the following optimal process conditions, weight of manganese-rich slag powder,100 g; mass ratio of manganese-rich slag to pyrite, 20:1; sulfuric acid concentration of 140 g/L; air pressure of 0.6 MPa; leaching temperature of 140 °C; leaching time of 1 h; L/S of 7:1; ore size of 75–80 μm; and stirring rate of 600 rpm, the extraction rate of Mn reached 94%, and the dissolution percentage of Si, Al, and Fe are as low as 2%, 6%, and 10%, respectively. The leaching slurry presented a good solid-liquid separation characteristic. The silicic acid formed during sulfuric acid leaching manganese silicates was converted to filterable dehydrated SiO2 particles which precipitated in the residue under the condition of higher temperature with higher pressure. The effect of adding pyrite may be to reduced iron ions and decreased the output of iron hydroxide colloid and also reduced MnO2 to manganese sulfate in sulfuric acid leaching. Thus the formation possibility of colloid such as silica gel and iron hydroxide was decreased, and higher yield of manganese sulfate could be achieved.

By J. A. Botín

In modern mining, the core of mine planning and design is the block model, a simplified representation wherein the ore deposit is divided in a number of virtual rock cubes, each characterized by technical and economics parameters. Mining engineers use this model to design the mine and develop production schedules. Traditionally, sustainability issues are not considered in the mine design, planning and engineering processes but rather are incorporated in the later stages of the feasibility evaluation as necessary expenditures and operating costs. This paper describes the results of a research project aiming to develop a methodology to incorporate sustainability parameters directly into the block model, so that they become an integral part of the design, planning and scheduling processes. It is considered that the incorporation of sustainable parameters into the block model would yield a more responsible mine design and improve mining projects sustainability performance

Feb 27, 2013