Search Documents

By Bo Hyun Kim, Mark K. Larson

Fault-slip bursts induced by mining activities can result in severe damage to nearby mine development. In general, engineers designing rock support in burst-prone mines not only need to consider stress redistribution resulting from excavation, but also dynamic loading that results from seismic waves generated by large mininginduced fault-slip events. In this study, we simulated dynamic waves in sedimentary rock from a blasting source and from a mining-induced-seismicity source using a Universal Distinct Element Code (UDEC) model with discrete fracture networks (DFNs). Our purpose was to investigate the stability of openings and the adequacy of existing support systems at an underground limestone mine in South Korea. A baseline model with only static loading was also simulated, which verified observed stability under such conditions. The results indicate that the current support system of shotcrete lining is likely to work well under dynamic loading caused by blasting. However, when the dynamic source was a far-field fault-slip event, the dynamic loading exceeded the support capacity of the shotcrete lining. Thus, if a mine is operating in ground with an elevated risk of mininginduced fault slip, mine engineers should consider seismic wave propagation and ground motion distribution from a remote, mining-induced fault-slip event to determine a suitable support design.

Jul 1, 2023

By Bartłomiej Bursa, Paweł Stefanek, Paweł Stefaniak, Sergii Anufriiev, Wioletta Koperska, Maria Stachowiak

The article presents the main functionality of the DSS class system for monitoring and stability assessment of tailings storage facilities. The presented demonstrator was deployed on the example of the Żelazny Most reservoir - the largest active facility of this type in Europe and the second one in the world. Considered a high-risk structure, it demands a system capable of online analysis of big data from various sources using machine learning, 3D modeling, or GIS mapping with the functions of interactive time-spatial analysis. In this paper, we present a complex calculation module with an integrated user interface.

Jun 25, 2023

By Christopher Mark

Sixty years ago, underground coal mining was the most hazardous job in the United States. Roof falls were a big part of the problem. They killed about 100 miners every year, more than all other causes put together. Fast forward half a century to 2016, which is the first year ever with zero roof fall fatalities. Just three miners were killed by roof falls during the following 6 years. How was this historic goal achieved? This paper starts with a modern analysis of the causes of the roof fall fatalities in 1968. Then it follows the reductions over time by category, using snapshots of the fatalities occurring in subsequent decades. Along the way, it evaluates the influence of the regulatory environment, changing mining methods, and better ground control technology. The paper shows that in 1968, more than half of roof fall fatalities at large mines were attributable to an inadequate safety culture. The immediate effect of the 1969 Coal Mine Health and Safety Act was to reduce the riskiest activities, like needlessly going under unsupported roof. Other hazards, like large roof falls, required technological developments before they were brought under control. Roof control plans, which the U.S. Bureau of Mines had been advocating since the 1920s, played a significant role throughout the process.

Jul 1, 2023

By Kate Willa Brown Requist, Eric Lutz, Moe Momayez

As air quality sensor networks become increasingly popular in underground coal mines, it is important to generate paradigms for the application of the collected data. To date, air quality sensing has been primarily used as an early warning system for hazardous air conditions. Using data collected from a network of sensors in a US underground coal mine, we have created multiple visualization methods to show the interactions of carbon monoxide evolution with ventilation airflow. These visualization methods can allow for further analysis of the source of contaminant, as well as better data resolution across the area of concern within the mine. By utilizing univariate spatial interpolations, we present methods for identifying the movement of carbon monoxide at one-minute intervals. The resulting visualizations display the evolution of carbon monoxide concentration across a sizeable study area over a period of 14 minutes.

Jun 25, 2023

By Alper Kirmaci, Taghi Sherizadeh, Dogukan Guner, Samuel Nowak, Khaled Mohamed, Morgan Sears

Coal ribs present a major safety hazard in underground mines, and there is currently no unified approach for their design in the United States. To tackle this issue, this study investigated the stability of underground coal pillar ribs under development load. Utilizing over a thousand 3DEC models, a framework for calculating coal pillar rib rating (CPRR) was developed. A detailed step-by-step method was outlined for computing the CPRR based on a 3DEC analysis, which was then validated with various 3DEC models, demonstrating a strong correlation between the two models. The results demonstrated that the rib factor of safety (RibFOS) under development load is directly proportional to CPRR, coal mine roof rating (CMRR), and floor strength, and inversely proportional to the overburden depth and rib height. Moreover, a regression equation was formulated to predict the RibFOS based on the aforementioned parameters. Furthermore, empirical relationships were developed between the RibFOS and the applied primary rib support density (PRSD) in U.S. coal mines. To ease the calculations, a stand-alone application, Design of Rib Support (DORS), was developed. This application can be used to assess rib stability and easily calculate CPRR, RibFOS, and PRSD.

Jul 1, 2023

By Peter Zhang, Daniel Su, Bo Kim, Zoheir Khademian

Building on the research results and knowledge obtained from the ongoing National Institute for Occupational Safety and Health (NIOSH) Gas Well Stability Research, researchers from the NIOSH provided detailed analyses on potential longwall mining and gas well casing interactions at an unconventional shale gas well pad in a West Virginia longwall mine. Following the recommendations from recent research findings, the 5-1/2-inch production casings in all five wells were left uncemented from 4,200 feet below the surface to the surface. Prior to the first longwall panel excavation, NIOSH researchers conducted sophisticated three-dimensional numerical modeling to predict longwall-induced deformations and gas well casing stresses, which were compared with post-first panel and post-second panel mining 40-arm caliper surveys. The pre-mining predictions and comparisons with post-mining 40-arm caliper surveys were presented to all parties involved, including the coal and gas operators, Mine Safety and Health Administration (MSHA), Pennsylvania Department of Environmental Protection (PADEP), and West Virginia Department of Mines (WVDOM), prior to the re-entry operation on December 13, 2022. To date, the re-entry operation is a resounding success.

Jul 1, 2023

By Timothy J. Matthews, Ted Klemetti, Timothy J. Batchler, Daniel J. McElhinney

Unplanned tailgate collapses and difficult mining conditions in U.S. longwalls have necessitated the use of innovative tailgate support systems. Severe ground movement induced by longwall loading has caused operators to utilize secondary support systems that can match yield and strength requirements with expected ground reactions. Standing support performance requirements depend on the nature of the ground deformation behavior, and therefore require a good understanding of the interaction between the support and ground to achieve an optimum roof support system. Mining operations often employ standing support strategies that are unique to their mine. A support system that functions successfully in one situation could fail in another situation. It is important that the design and installation of the standing support systems provide the highest probability of preventing roof falls. Pumpable roof supports are currently being used to provide a safe working environment for longwall mining. A full understanding of the impact of these performance characteristics is necessary to optimize the support application and to provide a foundation for making further improvements in the support performance. Optimization of roof support applications helps to ensure the protection of mine workers by preventing roof falls due to inadequate support design. The load capacity and stiffness characteristics of a 27-in.-diameter pumpable support system was evaluated using the National Institute of Occupational Safety and Health (NIOSH) Mine Roof Simulator (MRS). Previously, tests to evaluate the performance characteristics were performed on a single pumpable support. The goal of this new research is to evaluate the performance characteristic effects of the pumpable support system and compare it to an individual pumpable test examination. This research of a pumpable support system configuration simulates the current installation practices in U.S. coal mines.

Jul 1, 2023

By Jiachen Wang, Nan Wang, Yang Li

The close-multiple coal seam is an important component of China’s coal resources and plays a key role in total coal reserves. However, the overburden movement in the mining process of close-multiple coal seams is usually extensive, which is seriously affected by overmining. It is therefore essential to study the mechanism of roof breakage, the relationship between the shield and the surrounding rock, and the mechanism of overburden movement to ensure the safe operation and the efficient exploitation of close-multiple coal seams. This work first proposes a technical route for intelligent ground control. Second, the principle of cooperative control between the shield and overburden roof is revealed, and the shield support capacity calculation method is summarized. Third, the quantitative criterion for disturbance degree of key stratum (KSDD) is proposed based on the key strata theory. Finally, several intelligent evaluation and analysis systems have been developed in terms of overburden breakage and shield support capacity, multi-information analysis of ground control, and disturbance degree of overburden. The research results may provide an essential reference for the development of intelligent ground control in the mining process of close-multiple coal seams

Jul 1, 2023

By Wenbing Guo, Mingjie Guo, Hebing Zhang

As resources are depleted in coal mines, isolated support pillars are often mined. Cemented paste backfill has been used to provide support during the mining of these pillars due to its safe and green mining characteristics. However, traditional cemented paste backfill mining has some shortcomings, such as poor adaptability to geological structure, leakage of paste during filling, imperfect roof-contact in partially backfilled areas, and insufficient roof strata support before the backfill reaches its design strength. This paper presents the results of a case study where L-shaped interval cemented paste backfill technology has been safely used to mine an isolated coal panel beneath existing surface structures. This backfilling method has the advantages of preventing paste leakage, improving the backfilled ratio, reducing surface subsidence, and strongly adapting to geological structure. During this field application, the setting pressure of the backfill shield reached 20 MPa, the compressive strength of the backfilling body reached 2.0 MPa, and the backfilled ratio reached 93.7%. Observational ground monitoring showed that roof-to-floor convergence in adjacent roadways ranged from 132 to 167 mm. No obvious fractures or separations in the overlying strata were observed by a borescope. The maximum surface subsidence was 342 mm, the subsidence factor was 0.136, and the damage to surface buildings was within Grade I (slight damage). This case study clearly demonstrates that the L-shaped interval cemented paste backfill method can be safely used to mine the isolated coal panel beneath surface buildings.

Jul 1, 2023

By Mario E. Rossi

Often geometallurgical models are prepared at various project stages from very few data and are assumed to be representative of very large tonnages. These may include recovery models; crushing and grinding parameters and models; models of concentrate grades; models of acid consumption; etc. These models commonly do not carry a measure of uncertainty or variability, and are taken at face value at the time of design and planning. This paper proposes a proactive approach to modelling variability, providing uncertainty estimates and thus allowing for risk analysis and mitigation of geometallurgical models. The variability model is built up by understanding the limitations of the pillars of a geometallurgical model: data uncertainty; geologic model uncertainty; domain definition uncertainty; and parameter estimation uncertainty. Of these factors, typically domain definition is the most significant contributor to geometallurgical model variability. First, the fundamental supports for these models are briefly discussed, with domain definition emphasized. Second, two methods for uncertainty modelling are proposed. The first, more applicable to conceptual or early-stage projects, is a simpler and more expedient alternative that provides initial assessments of variability. This is intended to aid management in decision-making related to budgeting, including further sampling and testing. The second, a block-by-block approach that allows a detailed assessment of risk for specific designs and mine plans, thus providing further opportunities for mitigation. In the example provided, emphasis is placed in communicating this variability to both management and technical personnel in the form of “measured-indicated-inferred” indicators and also block-by-block confidence intervals.

Jun 25, 2023

By M Aboagye, K Appau, W. Assibey-Bonsu, C. Muller

A case study based on two recoverable resource modelling techniques (indirect and direct or localised methods) have been derived using typical feasibility study or new mine drilling data configurations from the extensions of an existing mine’s massive production database. The database is from the Gold Fields Tarkwa Gold mine (~6Moz Mineral Reserves and 13-year Life-of mine). The corresponding recoverable resources from the various techniques are then analysed using the open pit Whittle optimisation process. The results were then compared based on the Whittle optimisation results to determine the efficiencies of the approaches and the validity of the recoverable mineral resource estimates for mine planning and financial forecasts (including Cash Flows etc). Based on historical production metal recovery, the paper also assesses the corresponding orebody and mine planning as well as financial risks with regards to the modelling techniques. The study shows that the localized direct and somewhat more straight forward approach if applied efficiently can provide an equally useful tool for computing recoverable resources for mine planning and financial forecasts, as compared to the indirect approach as presently in use.

Jun 25, 2023

By M. Shahsavar, J. Sattarvand, J. Gomez

Mining can be categorized as a hazardous activity, considering some factors such as environmental conditions with a considerable presence of humidity, suspended particles, or falling rocks have affected the severity and number of accidents compared with other economic sectors. The industry analyzes incident reports to narrow the rate of severe injuries and fatalities, conducting root cause analysis and identifying leading indicators. As the International Council on Mining and Metals noted, the vast trove of incident data is not analyzed as much as possible due to a lack of analytics expertise at mine sites. However, machine learning could solve the problem of analyzing all the incident data in a no-timeconsuming way, considering the abundant data, and without using expert personnel in data science. Thus, a Convolutional Neural Network and a Naïve Bayes model were introduced to perform classification in the MSHA database. The database from 2020 consists of 60 fields to describe safety incidents; these fields include mine I.D., accident date, subunit (mill, surface), material extracted, and other metadata.

Jun 25, 2023

By Silvia Misk, Cristina Araújo, João Felipe Costa, Roberto Rolo

Linear estimation methods are widely used for resource evaluation. Among the existing linear estimation methods, ordinary Kriging (OK) was accepted as the best estimator to determine the average ore grade of each block. However, OK is inadequate for modeling small blocks in relation to data spacing, resulting in over-smoothed models. In this study, the results of the recoverable resource from the short-term model are compared to estimated models generated by the traditional method, i.e., OK, and non-linear methods. The conclusion is that non-linear methods improve the accuracy and precision of the long-term model when compared to the model generated by OK.

Jun 25, 2023

By Sebastian Avalos, Julian M. Ortiz

The long-term mine scheduling is the optimal decision on how to extract and process the mining reserves. The resulting plan is mainly driven by economic, metallurgical, and geological factors. Accounting for their uncertainties leads to a robust solution and the feasibility for economic-risk quantification. In this work, we model the spatial uncertainty of grade distributions of multiple correlated elements, by using a multivariate morphing transformation. The result is a set of multivariate geostatistical realizations of the grades, which honor the conditioning data, the direct and cross variograms, and the multivariate statistical distribution, inferred from a set of samples. These models are the input in a reinforcement learning framework, adopted to train a deep neural network that considers the grade uncertainty and leads to an optimum mine plan after training using deep Q-Learning. Mining and processing capacities, as well as economic parameters and metallurgical constraints, are incorporated as the reinforcement learning environment rules. The method is validated on a real deposit, providing insights for future applications.

Jun 25, 2023

By J. P. De Carvalho, R. Dimitrakopoulos

An actor-critic reinforcement learning approach is presented to improve the production of an industrial mining complex by defining shovel allocation and adapting the short-term plan given grade-control decisions. Blasthole data updates the simulated orebody models, which are input into a stochastic grade-control method based on a spatially constrained clustering approach that minimizes the profit-loss function. These aspects are embedded in a discrete-event simulator that defines the material flow from faces to processors. A case study at a copper mining complex shows the methods’ ability to adapt to new information, improving the quality of the material feed and increasing cash flow by 23% compared to a baseline case.

Jun 25, 2023

By Ernesto Maldonado, Zach Agioutantis, Jesus Romero

Reliable prediction of dynamic deformations is important when planning to undermine important structures that cannot tolerate large relative deformations and or large horizontal strains. This paper presents examples of dynamic deformation profiles that include subsidence, horizontal displacements, and horizontal strain for a number of points over a retreating longwall panel in the eastern United States. The prediction points are located at different distances from the excavation rib and therefore present a different response in terms of dynamic movements. The formulation is based on the influence function method as implemented in the Surface Deformation Prediction System (SDPS). Results show that the subsidence development curve may be reliably predicted for surface points in the middle of the panel. However, in cases where points may be affected by the magnitude of the edge effect offset, subsidence predictions may be very conservative, that is, higher than actual movements.

Jul 1, 2023

By Kevin Andrews, SETAREH GHAYCHI AFROUZ

Ground control analysis and groundwater inflow assessments for underground coal mines require in-depth field investigations including, but not limited to, geological and geotechnical core logging, downhole geophysical logging, laboratory rock strength testing, and packer (Lugeon) testing. Field and laboratory data collection are time consuming and expensive, and an initial understanding of the expected trends among various geotechnical and hydrogeological parameters can assist with the planning and optimization of geotechnical characterization studies and grouting plans. In this study, a comprehensive database is analyzed, comprised of important rock mass characteristics (hydraulic conductivity, rock quality designation (RQD), and lithology) for coal-bearing rocks in the Central Appalachian Basin. Statistical analysis of the data is completed to establish an enhanced understanding of geotechnical and hydrogeological conditions expected to be encountered as underground coal mining passes near and beneath streams and rivers. The results of the study provide valuable reference material for the coal mining industry for completion of shaft installations, mine stream crossings, environmental assessments, and grouting and mine dewatering designs.

Jul 1, 2023

By Milka Madahana, John Ekoru

Particulate matter is one of the leading pollutants in the mines and in the communities in the areas near or surrounding the mines. The availability of large Clinical and environmental data sets obtained from the mines has brought about the need to use better approaches to analyze the collected data. Prediction and control of particulate matter concentration in the mining environment is essential in minimizing air pollution and protecting the respiratory health of mine workers. The main objective of this research work is to analyze datasets obtained from a mining area using machine learning techniques which will then be followed by the real-time estimation of dust particulate in the mines. Datasets collected over 8 years in an hourly sampling rate from an open cast mine is cleaned and analyzed for trends and patterns. Artificial Neural Networks (ANNs), Support Vector Machines and decision trees techniques are applied to analyze and predict the particulate concentrate. The estimation of particulate concentration using Artificial Intelligence will significantly contribute toward the development of quantitative tools to be used in correlating of cause and effect of dust concentration in mines. The results obtained in this work will form a sub-unit of a respiratory health monitoring system for mine workers. The system is essential in the collection, analysis, and tracking of mine workers’ respiratory health, thus it forms part of an early intervention system for mine workers. From the existing theory, we expect the Artificial Neural Network will perform much better than previously used classical models.

Jun 25, 2023

By Richard Minnitt, Philippe Renard, Christina Dohm, Winfred Assibey-Bonsu, Matthew Aboagye, Julien Straubhaar, Mahlomola I. Mabala

The application of multiple point statistics (MPS) in oil studies has gained traction over the years; however, the use of MPS in mineral resource estimation and classification is still limited. This is despite MPS’ ability to deal with complex and heterogeneous geology better than the commonly applied two-point based methods. The availability and choice of a representative training image (TI) are often cited as the main challenge holding back MPS’ application in mining geostatistical studies. On the other hand, the general approach used in mining whereby early focus is on higher grade areas and lower grades are planned to be mined later presents a massive opportunity for the development of representative TIs. Mined-out areas provide large amounts of historical data that can be used to develop training images or training datasets that can be used to estimate in mining extension areas (often lower in grade), provided low grade areas are underpinned by similar geology analogue. This approach will enable more robust estimates in mine/pit extension areas for both high- and low-grade extensions than with traditional two-point geostatistical methods.

Jun 25, 2023

By Brendan Demich, Linda L. Chasko, Brendan Macdonald, Timothy J. Orr, Jessie J. Mechling, Cassandra Hoebbel, Jason Navoyski, William Helfrich, Jessica Cohen, Paul E. Schmidt, Jennica L. Bellanca

The National Institute for Occupational Safety and Health (NIOSH) in partnership with the Mine Safety and Health Administration (MSHA) developed VR Mine Rescue Training (VR-MRT). It is a training platform that allows mine rescue team members to explore virtual emergency scenarios collaboratively. Team members use a head-mounted display to visualize and interact together with equipment, hazards, and dynamic ventilation. All player actions are recorded and displayed for debriefing. Researchers at NIOSH demonstrated the training platform at various mine rescue competitions, including the International Mine Rescue Competition, and collected feedback. Participants’ responses were overwhelmingly positive. This paper describes the development of the software platform and the results of the usability surveys and interviews.

Jun 25, 2023