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By Arash Nikvar-Hassani, Lianyang Zhang

To address the drawbacks of the conventional portland cement/fly ash (PC/FA)–based cementitious material currently used in practice to construct pumpable roof supports (PRSs), a novel cementitious material has been developed based on geopolymerization technology. The novel cementitious material is comprised of two pumpable grout streams: Stream 1 is a slurry composed of pozzolanic material and high-calcium additive and stream 2 is an alkaline solution comprised of a gelling agent. Biopolymer has been added to the second stream to provide ductility to the geopolymer cementitious material. In the laboratory scale, systematic experiments have been carried out to investigate the viscosity, setting time, and uniaxial compressive strength (UCS) of the new cementitious material and develop the right recipe for field applications. By collaborating with industry and the National Institute for Occupational Safety and Health (NIOSH), full-scale PRSs have been constructed and tested. The results show that (1) the novel cementitious material based PRSs has much higher peak UCS and similar or higher residual strength than the conventional PC/FA-based PRSs; and (2) unlike the PC/FAbased cementitious material, the novel cementitious material shows good long-term durability with nocracking/disintegration when exposed to air.

Jul 1, 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 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 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 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 Bo Hyun Kim, Mark K. Larson

Researchers at the National Institute for Occupational Safety and Health have tested the finite element code, UT3PC, with LaModel to evaluate their results using know case studies. The purpose of the testing was to demonstrate the usefulness and limitations of these programs in evaluating mine layout design. Both of these software packages are simple to use and free for public download. Their use by mine engineers, along with other tools, such as empirical methods, can enhance the assessment of a mine layout design. LaModel can model mining layout on a mine scale or, at least, on a multiple-panel scale. However, this software has limitations in calibrating to conditions at many coal mines in the western United States. The UT3PC software models smaller parts of a mine and is used to evaluate the design of pillars, shafts, or drifts; but the software calculates all components of the stress tensor and provides stresses, displacements, and safety factors throughout the model volume. The two codes are used to evaluate design of one known case, and UT3PC is used to evaluate another case. The results and approaches demonstrated in the testing are intended to aid mine engineers in evaluating site-specific problems and to show that these tools can provide useful information to the mine engineer in evaluating mine layout design.

Jul 1, 2023

By Hamid Maleki

Mine seismicity is influenced by the mechanical properties of both near-seam strata and overburden/underburden and the prudent selection of mining methods and mine layout designs, utilizing sitespecific structural setting of the mines. The importance of adequate data collection, monitoring, and prudent structural designs has long been recognized and utilized in many U.S. operations with adequate engineering resources. In this paper, two case studies of historic seismic events and contributing factors, in deep coal and trona mines with overburden thickness exceeding 1,500 ft, are reviewed using observations and analysis. By back analyzing the overburden response in a historic room-and-pillar coal mine, the overburden collapse mechanism associated with a 3.3 magnitude seismic event is reviewed as well as the need for improvements in designs including panel and barrier pillar widths. Similar high-order seismic events were also experienced in trona mines of the Green River Basin during 1990s, interrupting room-and-pillar mining and creating ground control concerns. Efforts to improve structural mine designs are described in this paper leading to stable and productive operations for decades following the high-order seismic events in both coal and trona case studies. These efforts included improving room-and-pillar extraction layouts and utilizing properly designed longwall mining techniques that were verified using long-term geotechnical instrumentation. The study mines are located on the Wasatch Plateau (WP), Utah and in the Green River Basin (GRB), Wyoming. More recently, in Utah’s East Mountain alone, Energy West Mining Company (EWMC) has extracted some 165 million tons of coal without any significant incidents. Overall, favorable geologic conditions and prudent mine layout designs are key elements to this successful experience in both single- and two-seam layouts. Utilization of conservatively designed longwall mining technique in the GRB has been geotechnically stable, using reported experience in 15 panels and monitoring results in the Northwest (NW) District with measurable longwallinduced seismicity being rare. These studies demonstrate a considerable amount of progress that has been made within the last four decades in the application of longwall mining technique, integrated monitoring, and analyses for the verification of structural designs in mines in the United States.

Jul 1, 2023

By Mark Van Dyke, Mark Mazzella, Gamal Rashed, Nicole Evanek, Brent Slaker

In the past decade, there have been several incidents of massive ground collapses in underground stone mines in the eastern United States. Fortunately, these events have not resulted in any fatalities. However, three mine workers were injured and many others were at risk due to the hazard from the fall of ground and/or the airblast associated with these massive collapses. The National Institute for Occupational Safety and Health (NIOSH) initiated a project to better understand the causes of these massive ground collapses to help prevent their future occurrence. The main objective of this study is to investigate the main factor(s)that initiated one of these massive ground collapses. The authors relied on several tools including three-dimensional (3-D) LiDAR scans for the surface subsidence feature and the underground mine workings around the collapsed area, borescope data at multiple locations around the collapse, S-Pillar analysis for average and unfavorable conditions, and numerical models. The emphasis has been placed on the impact of the following limestone pillar stability parameters: pillar width-to-height (W/H) ratio, benching, the existence of karst features, weak roof, and geological discontinuities. 3-D LiDAR scans were utilized to show the shape and the extent of karst cavities observed within stable pillars around the perimeter of the collapsed area. Together, this coupling of field measurements and observations and modeled systems suggests the potential causes of the collapse.

Jul 1, 2023

By Xiaoting Li, Richard Adasiak, Benjamin Mirabile

Pumpable J-Crib stopping walls and Jennmar high-strength (HS) stopping panel walls are widely used for resisting high-ventilation air pressures and roof support in underground mines due to their installation efficiency, convergence allowance, and better performance than traditional concrete block stopping walls. Based on the different entry dimensions and required maximum ventilation air pressures of up to 36-in. water gauge, 24-, 27-, 30-, and 36-in.-diameter pumpable J-Crib stopping walls, or 18- to 30-in. thick Jennmar HS stopping panel walls can be designed, and their support capacities and convergence allowances are evaluated for better roof control. Pumpable J-Crib stopping walls consist of 0.187-in.-diameter steel wire reinforced, JCrib material-filled bags, and non-wire-reinforced filler bags in between. Jennmar HS stopping panel walls consist of two, 20-gauge (0.04-in.-thick), galvanized, cold-formed steel panels with J-Seal materials pumped in between. Based on the fundamental structural design principles and specifications of ACI 318-19(22), the compression and flexural strength, and shear resistance of the walls can be checked to be compliant with the codes and specifications following the load and resistance factor design (LRFD) method. Specifically, the 0.187- in.-diameter steel wires in the pumpable J-Crib walls and 20-gauge steel panels in the HS stopping walls are integral parts of the walls and are considered to effectively confine the J-Crib or J-Seal materials. These steel elements play a significant role in reinforcing and improving the strength or support capacity of the stopping walls from a structural design perspective. Because of the high ductility of low-density J-Crib/J-Seal materials and steel elements, these walls are good at accommodating or absorbing the roof convergence (≥5% entry height), which cannot be matched by a traditional concrete block stopping wall (Figure 1). Based on the successful design and application of these stopping walls in different mines for improving roof stability and avoiding the air leakage, the authors have formulated the design methodology and verified independently by the finite element analysis (FEA) simulation technique. This design methodology combines the fundamental structural design principles with specific wall dimensions and material properties, facilitating mine engineers and government agencies to understand the in-depth working mechanism of these stopping walls.

Jul 1, 2023

By Steven Keim, Steven Stansfield, Kevin Andrews

Geotechnical, geological, and hydrogeological fieldwork and data collection for the mining industry is often conducted by younger, less-experienced staff members. In many cases, fieldwork personnel are recent college graduates or are otherwise relatively new to the mining industry. Due to busy schedules, staffing shortages, project budgets, and in some cases, poor management, new fieldwork hires often do not receive thorough training. In the past and the present, many workers in the mining industry learn(ed) by “doing.” While this is still considered to be the most practical approach and the easiest way for a company to determine the skill set of an employee, there is always some risk involved in the “feet to the fire” method. The reality is that field personnel are often collecting data on which major operational decisions will be made or on which regulators will base enforcement decisions. Inadequately trained or inexperienced field personnel may collect inaccurate data or fail to recognize key conditions that may influence decisions made by regulators, design engineers, mine managers, and corporate leaders. Even the best engineers may come to incorrect conclusions if they are starting with poor input data. Decisions based on inaccurate data often result in delays, budget issues, unsafe conditions, or even worse consequences. This paper provides numerous mining industry examples of incidences where inaccurately collected field information did, or could have, resulted in major adverse consequences. The paper also offers some simple approaches to minimizing the potential for such problems.

Jul 1, 2023

By Chris Roos

The mining industry has made strides in planning for operations to be safe for the workforce and public, to protect the natural environment, and to maximize value for shareholders. However, many of the techniques used to accomplish these goals are based on estimated models of mineral content, production efficiency, and economic performance. The industry has begun to recognize the need for understanding the uncertainty in these models, how it affects their decisions, and what the potential impacts are for each project. The challenge has become how technical professionals can effectively communicate the impact of this uncertainty and its importance to both technical and non-technical audiences. This paper presents mining engineers (and other technical professionals) with traditional and modern principles of data visualization and technical communication that can assist with communicating the effects of uncertainty in the mine planning process.

Jun 25, 2023

By Javad Sattarvand, Amin Moniri-Morad

Predicting equipment failure behavior plays a critical role in providing a safe operation. Although various reliability evaluation methods are available for estimating failure behavior profiles, these approaches are based on mathematical formulation, leading to actual operation simplification and improper estimation of failure trends. This study proposes a discrete-event simulation (DES) approach to model fleet failure behavior. This approach can model the maintenance strategies in multi-component systems with minimum simplifications. In this regard, the first step was to collect a historical failure time dataset (e.g., the time between failures). Then, the DES model is established to predict the severity of failure events and design maintenance strategy considering actual operation circumstances. Afterward, the maintainability analysis was performed to estimate equipment downtime and availability. The achieved results showed that the system availability was about 85%. Also, the findings demonstrated that the DES could efficiently predict the equipment failure behavior using various stochastic events.

Jun 25, 2023

By Robert Bissonette, Samir Sbai

A critical component of implementing autonomous systems is the ability to use information from a robust sensory and information system to make sound, predictable, and repeatable decisions to assure safety. This means that any such system would need to evaluate what objects (people, equipment, boulders, etc.) of interest exist in that environment (with relevant data about identity, trajectory, characteristics, etc.), project a future continuum of those objects (including considerations for variabilities), and make control intervention choices to minimize risk due to exposures in the present operational area. The components of an overall system would include: a) sensor and data fusion, b) probability projection of future states, c) generation and evaluation of alternate futures, and d) implementation of best course of action to reduce risk. The National Institute for Occupational Safety and Health (NIOSH) Spokane Mining Research Division (SMRD) is studying this framework for applications for autonomous mining equipment. This paper focuses on using information from the sensor fusion engine to generate a continuous projection of future and alternate states (b and c above) incorporating the factors of confidence, accuracy, tolerance, and other variabilities. We refer to this as Machine Situational Awareness (MSA).

Jun 25, 2023

By Javad Sattarvand, Frimpong Kwaku Asare

The safe evacuation of miners during an emergency in the shortest amount of time is one of the most essential features of a mining operation. Despite advancements in mine evacuation research, the usage of mine vehicles during evacuation has not been considered. The majority of recent studies have been done on miners’ evacuation on foot. Mathematical formulations including Minimum Cost Network Flow (MCNF) models, Dijkstra's algorithm, Floyd-Warshall algorithm, and Ant Colony Optimization models have been used to solve mine evacuation problems. These models, which concentrate on determining the shortest escape routes during the evacuation, have been found to be computationally expensive and may not offer the best solutions in some cases. The goal of this paper is to incorporate light vehicles in the evacuation process using a mixed-integer programming approach. The methodology aims to minimize the total time required to evacuate the mine, ensuring minimal exposure of the miners to the adverse conditions that triggered the evacuation.

Jun 25, 2023

By Amy McBrayer, Andrea Brickey

Limited research has been conducted related to the development of mathematical optimization models for production scheduling at large surface coal mines using the area, i.e., strip, mining method. Increased economic and technical challenges have led to a new interest in production schedule optimization models for these type of mining operations like those currently applied to model underground and open pit mines. While area mines share similar characteristics to both open pit and underground metal operations, neither an open pit nor underground production scheduling model adequately depicts an area mine mathematically. We present an integer programming model with blending constraints and discuss the challenges and opportunities related to the implementation for area mines as well as future research in area mine production scheduling.

Jun 25, 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 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. 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 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