Strategies based on the repowering existing and powering new mobile equipment with contemporary diesel engines with substantially lower tailpipe and crankcase emissions are expected to play an important role in the efforts to curtail exposures of underground miners to criteria diesel pollutants. Laboratory characterization of tailpipe emissions for three "clean" engines that meet U.S. Environmental Protection Agency (EPA) Tier 4 final emissions standards were used to assess the viability and effectiveness of those strategies. The evaluated engines were representative of those that achieve the emission standards through implementation of various in-cylinder emissions control strategies, use of crankcase filtration, and use of three types of exhaust aftertreatment systems: (1) diesel oxidation catalytic converter (DOC), (2) combination of DOC and the full-flow wall flow monolith diesel particulate filter (DPF), or (3) combination of DOC, diesel exhaust fluid (DEF)-based selective catalytic reduction (SCR) system, and ammonia slip catalyst (ASC). The study showed that the highest reductions in concentrations of diesel aerosols in underground workings, in terms of both mass and number, could be achieved if the engines, preferably in all power classes, are fitted with viable DPF systems. The use of U.S. EPA Tier 4 final engines equipped with DOC and DOC/SCR/ASC systems could help operators to considerably reduce mass, but not number concentrations of aerosols. The emissions of two of the evaluated engines, one equipped with DOC and the other equipped with DOC/DPF systems, were characterized by substantial secondary NO emissions that would limit the viability of those engines for underground mining applications. The catalyst formulations used in the exhaust aftertreatment systems of the diesel engines marketed to the underground mining industry need to be formulated to minimize the potential for generation of secondary NO emissions. Engines fitted with viable SCR/ASC systems present a low-NO alternative. All three of the evaluated advanced engines were found to have low CO output. Due to nuances associated with the use of diesel-powered mobile equipment in underground mines, the selection and potentially optimization of advanced engines for underground mining applications deserves special consideration.

Maintaining the particulate emissions from contemporary diesel engines equipped with diesel particulate filter (DPF) systems at targeted levels and assuring the effectiveness of DPF systems retrofitted to traditional diesel engines are critical to the efforts of underground mining operations to reduce exposures of miners to diesel particulate matter. The methodologies and instrumentation currently used to support the emission-assisted maintenance (EAM) programs for previous generations of diesel engines are in need of improvement to allow for monitoring low concentrations of complex aerosols emitted by the advanced diesel engines. The results showed that of the test conditions currently used in EAM programs, the torque converter stall and hydraulic stall are the most suitable for assessing the effectiveness of the DPF-based advanced aftertreatment systems. The low idle and high idle test conditions, frequently used in EAM programs for traditional engines, did not produce reliable and reproducible data. The solid particle number (SPN) concentrations proved to be more suitable than total particulate number concentrations as a metric for EAM monitoring of diesel aerosols emitted by advanced diesel engines. Both of the evaluated direct reading instruments, TSI 3795-HC and Pegasor Mi3, provided comparably accurate results of assessments of the SPN concentrations in the targeted range of concentrations between 2 × 10 and 3 × 10 #/cm. Those proved to be viable EAM tools for determination of the efficiencies and performance degradation of the DPF system. The findings of this study should provide the underground mining industry with valuable information needed to enhance their EAM programs.

Occupational exposures to respirable dusts and respirable crystalline silica (RCS) is well established as a health hazard in many industries including mining, construction, and oil and gas extraction. The U.S. National Institute for Occupational Safety and Health (NIOSH) is researching methods of controlling fugitive dust emissions at outdoor mining operations. In this study, a prototype engineering control system to control fugitive dust emissions was developed combining passive subsystems for dust settling with active dust filtration and spray-surfactant dust suppression comprising a hybrid system. The hybrid system was installed at an aggregate production facility to evaluate the effectiveness of controlling fugitive dust emissions generated from two cone crushers and belt conveyors that transport crushed materials. To evaluate effectiveness of the system, area air measurements ( = 14 on each day for a total of 42 samples) for respirable dust were collected by NIOSH before, during, and after the installation of the dust control system in the immediate vicinity of the crushers and the nearby conveyor transfer point. Compared to pre-intervention samples, over short periods of time, geometric mean concentrations of airborne respirable dust were reduced by 37% using passive controls ( = 0.34) but significantly reduced by 93% ( < 0.0001) when the full hybrid system was installed. This proof-of-concept project demonstrated that the combined use of active and passive dust controls along with a spray surfactant can be highly effective in controlling fugitive dust emissions even with minimal use of water, which is desirable for many remote mining applications.

Lithium-ion battery applications are increasing for battery-powered vehicles because of their high energy density and expected long cycle life. With the development of battery-powered vehicles, fire and explosion hazards associated with lithium-ion batteries are a safety issue that needs to be addressed. Lithium-ion batteries can go through a thermal runaway under different abuse conditions including thermal abuse, mechanical abuse, and electrical abuse, leading to a fire or explosion. The NIOSH Mining program is conducting research to prevent and respond to lithium-ion battery fires for battery electric vehicles in the mining industry. In this study, experiments were conducted to investigate the effectiveness of different suppression systems including dry chemical, class D powder, and water mist for lithium iron phosphate battery pack fires. The effects of activation time and release time of the water mist system on the suppression of lithium-ion battery fires were studied. The results of this study may be helpful for developing strategic firefighting and response plans for battery-powered vehicles used in mining.

Fatigue-related risk is a persistent safety concern for the mining industry. However, fatigue and sleepiness are often treated interchangeably, which can lead to confusion and potentially less effective reduction of safety risk. To provide clarity, we present an overview of similarities and differences between work-related fatigue risk and sleepiness including definitions, theories, measurements, and mitigation strategies. As a supplement, a summative visual model which highlights these similarities and differences is presented. Expanding industry knowledge in this area will assist safety professionals in crafting more targeted risk management practices appropriate for work-related fatigue risk, sleepiness, or both.

Pillar stability continues to be a significant concern in multiple-level mining conditions, particularly for deep mines when pillars are not stacked or the thickness of interburden between mining levels is thin. The National Institute for Occupational Safety and Health (NIOSH) is currently conducting research to investigate the stability of pillars in multiple-level limestone mines. In this study, FLAC3D models were created to investigate the effect of interburden thickness, the degree of pillar offset between mining levels, and in situ stress conditions on pillar stability at various depths of cover. The FLAC3D models were validated through in situ monitoring that was conducted at a multiple-level stone mine. The critical interburden thickness required to minimize the interaction between the mining levels on top-level pillar stability was explored, where the top level mine was developed first followed by the bottom level mine. The model results showed that there is an interaction between numerous factors that control the stability of pillars in multiple-level conditions. A combination of these factors may lead to various degrees of pillar instabilities. The highest degree of local pillar instability occurred when pillar overlap ranges between 10 and 70%. On the contrary, the highest degree of stability occurs when the pillars are stacked, the underlying assumption is that the interburden between mining levels is elastic (never fails). Generally, for depths of cover investigated in this study, the stability of top-level pillars shallower than 100 m (328 ft) or with interburden thicknesses greater than 1.33 times the roof span-16 m (52.4 ft) in this study-does not appear significantly impacted by pillar offset. The results of this study improve understanding of multiple-level interactions and advances the ultimate goal of reducing the risk of pillar instability in underground stone mines.

Given the recent focus on powered haulage incidents within the US mining sector, an appraisal of collision avoidance/warning systems (CXSs) through the lens of the available research literature is timely. This paper describes a rapid review that identifies, characterizes, and classifies the research literature to evaluate the maturity of CXS technology through the application of a Technology Readiness Assessment. Systematic search methods were applied to three electronic databases, and relevant articles were identified through the application of inclusion and exclusion criteria. Sixty-four articles from 2000 to 2020 met these criteria and were categorized into seven CXS technology categories. Review and assessment of the articles indicates that much of the literature-based evidence for CXS technology lies within lower levels of maturity (i.e., components and prototypes tested under laboratory conditions and in relevant environments). However, less evidence exists for CXS technology at higher levels of maturity (i.e., complete systems evaluated within operational environments) despite the existence of commercial products in the marketplace. This lack of evidence at higher maturity levels within the scientific literature highlights the need for systematic peer-reviewed research to evaluate the performance of CXS technologies and demonstrate the efficacy of prototypes or commercial products, which could be fostered by more collaboration between academia, research institutions, manufacturers, and mining companies. Additionally, results of the review reveal that most of the literature relevant to CXS technologies is focused on vehicle-to-vehicle interactions. However, this contrasts with haul truck fatal accident statistics that indicate that most haul truck fatal accidents are due to vehicle-to-environment interactions (e.g., traveling through a berm). Lastly, the relatively small amount of literature and segmented nature of the included studies suggests that there is a need for incremental progress or more stepwise research that would facilitate the improvement of CXS technologies over time. This progression over time could be achieved through continued long-term interest and support for CXS technology research.

Mine equipment fires remain as one of the most concerning safety issues in the mining industry, and most equipment fires were caused by hot surface ignitions. Detailed experimental investigations were conducted at the NIOSH Pittsburgh Mining Research Division on hot surface ignition of liquid fuels under ventilation in a mining environment. Three types of metal surface materials (stainless steel, cast iron, carbon steel), three types of liquids (diesel fuel, hydraulic fluid, engine oil), four air ventilation speeds (0, 0.5, 1.5, 3 m/s) were used to study the hot surface ignition probability under these conditions. Visual observation and thermocouples attached on the metal surface were used to indicate the hot surface ignition from the measured temperatures. Results show that the type of metal has a noticeable effect on the hot surface ignition, while ventilation speed has a mixed influence on ignition. Different types of liquid fuels also show different ranges of ignition temperatures. Results from this work can be used to help understand equipment mine fires and develop mitigation strategies.

In recent years, there has been increasing interest in the role that individual factors play in health and safety (H&S) outcomes in the mining industry. Two surveys, one measuring self-reported routine safety performance and one measuring individual perceived competence in the non-routine knowledge, skills, and abilities (KSAs) critical to emergency response, were administered to two samples of mineworkers in separate research studies over a 2-year period ( = 2,020 and 696, respectively). Eight demographic items were common to both surveys and their associations with each performance outcome were tested in response to a series of exploratory research questions. Significant relationships were found between both safety outcome variables and individual factors, including the length of experience in current job, current mine, and mining industry, as well as participant workgroup and work schedule. Notably, the length of experience in the mining industry was the only variable significantly associated with both routine and non-routine safety performance. This analysis suggests that individual factors such as length of job, industry, and mine experience are predictive of routine and/or non-routine safety performance outcomes in significant and sometimes unexpected ways.

Underground mining operations use several remedial measures to alleviate the miners' exposure to respirable dust. This includes maintaining the ventilation airflow, deploying scrubbers on equipment, and using water sprays to move air and dust away from the miners and to capture them. Despite these engineering controls, recent research shows an increased occurrence of exposure-related issues in the impacted miners. Masks and other PPE devices are considered the least preferred in the hierarchy of controls. However, they show a high protection factor if designed properly and according to recommendations. A Powered Air Purifying Respirator (PAPR) is a battery-operated personal scrubber that has found widespread application in industries. This respirator uses a blower to move air through a high-efficiency particulate air (HEPA) filter, delivering the purified air to the user. Its popularity is attributed to its high protection efficiency. This paper summarizes the current applications and evaluation methods of PAPRs. It strongly recommends their usage in underground mines to reduce the risk of mine dust lung diseases such as pneumoconiosis, asbestosis, silicosis, and others that do not have any conclusive treatment. While the high efficiency of the respirators has been demonstrated, we recommend further studies to investigate the unique challenges associated with their use in underground mines. Therefore, this paper also presents computational fluid dynamics (CFD) simulations as a tool to understand the performance of PAPRs in underground tunnels, which could help to understand not only the efficiency, but also the challenges associated with their implementation.

This laboratory-scale study presents the development and validation of a hydraulic fracturing technique to directly measure the tensile strength of cemented paste backfill (CPB), providing an alternative to traditional strength testing methods. Fracture initiation pressure (FIP) was used as the primary measure of CPB strength. Experimental results were compared with traditional benchmark measures such as uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and critical Mode-I fracture toughness (K). Regression analysis of experimental results revealed a strong linear relationship between FIP and these benchmark strength measures, indicating that FIP can be used as a reliable predictor of CPB strength. However, traditional linear elastic failure models did not adequately explain the observed FIP values, as they significantly over-predicted the CPB tensile strength. To address this, the Point Stress (PS) model was applied, which provided a more accurate prediction of tensile strength, especially in cases involving small boreholes. The PS model explained observed effects of borehole size on the material's response to hydraulic pressurization. This study confirms that hydraulic fracturing, interpreted through the PS model, is an effective method for determining CPB strength and provides a practical alternative measure to conventional testing methods.

Underground mine fires are a threat to the safety and health of mine workers. The timely determination of the location and size of an underground fire is of great importance in developing firefighting strategies and reducing the risk of any injuries. Machine learning was used in this paper to develop a predictive model for fire location and fire size in an underground mine. The ventilation data were obtained by simulating different mine fire scenarios with MFire. The ventilation data of all airways were used as features to predict the fire location. Based on the feature importance, five airways were selected to monitor, and the airflow data of the selected airways were used to predict the fire location and fire size. An accuracy score of 0.920 was obtained for the prediction of fire location. In addition, in-depth analyses were conducted to characterize the wrong predictions with the purpose of improving the performance of the random forest model. The results show that the occurrence of fire at closely connected airways at some locations can generate misleading ventilation data for each other and the model performance can be further improved to 0.962 by grouping them. Fire size is another factor affecting the model performance and the model accuracy increases with increasing fire size. The result from this study can help mine safety personnel make informed decisions during a mine fire emergency.

Occupational exoskeletons (EXOs) have received growing attention as a new ergonomic intervention to reduce physical demands in various industries (e.g., manufacturing, logistics, construction, and agriculture). However, their potential use in mining has not yet been reported. Survey data ( = 135) were obtained from mining workers in the United States (US) and Indonesia (ID). Qualitative and frequency analyses were used to summarize and compare respondents' perceived barriers, benefits, and promoters to EXO use and adoption. Beta regression analyses were also used to examine whether the perceived likelihood to use arm-support EXOs or back-support EXOs differed between the countries and was affected by demographic or job characteristics, or by perceptions regarding EXOs. Both US and ID respondents reported potential benefits of EXOs for physically demanding tasks such as lifting and overhead work, and they shared concerns about adaptation, uncertainty or lack of knowledge, confined spaces, device weight, potential failure or damage, and costs. However, some key differences also emerged: US respondents were more likely to consider using arm-support EXOs and back-support EXOs, despite expressing concerns about their use; ID respondents, although they reported more existing health and safety hazards, appeared more hesitant about adopting EXOs, possibly due to these additional hazards. These results demonstrate that miners appear to have an interest in EXOs but also emphasize the need to ensure task compatibility, comfort, and affordability to ensure the safe and effective adoption of EXO technology in mining in both developed and developing countries.

The application of statistical analysis software programs has proven useful for the investigation of rockfall runout distance along a designed slope. Rockfall modeling programs are continually being upgraded with more sophisticated analysis tools, such as the use of the rigid body versus lump mass models. Engineers at mine sites utilizing the software may have varied experience related to these models, their associated input parameters, and how to interpret the generated results. To address this concern, researchers at the Spokane Mining Research Division (SMRD) of the U.S. National Institute for Occupational Safety and Health (NIOSH) investigated the influence of slope height, slope angle, slope material, and rock size for both rigid body and lump mass models in a 2-D statistical analysis program. Based on a literature search and industry input, specific ranges common to that of an open pit mining environment were chosen for each of the input parameters to determine 90% rock runout distance as well as their sensitivity to change. Data collected from this numerical analysis and simulation will be compared to empirical rockfall data gathered through the duration of the Highwall Safety project conducted by NIOSH from 2022-2026.

According to the 2010-2019 Mine Safety and Health Administration (MSHA) accident report database, 91% of reported ground control accidents in US longwall mines were caused by roof instability. Gateroads are subjected to significant changes in loading conditions from the development to the longwall abutment loading phases. When combined with thinly bedded shale roof, found in many US longwall coal mines, the design of efficient roof support becomes challenging. In previous work, the bonded block modeling (BBM) of roof by UDEC was validated against field extensometer measurements in a longwall entry roof at a 180-m depth of cover. The BBM was shown capable of capturing delamination and buckling of shale roof, one of the main roof instability mechanisms in longwall mines. This paper presents the recent findings on the roof-support interaction using BBM models of the same longwall entry. The effects of cable bolts, roof bolt density, and strap support on potential roof instability are studied. Results demonstrate the potential for BBM numerical models to help understand the complex roof and support system interactions and to assist with optimizing gateroad support systems.

Banded Iron Formations (BIF) are sedimentary rock formations ranging in age from 0.8 to 3.8 billion years and consist of alternating layers of silica and iron. The thickness of the alternating layers varies between and within deposits, with this lithology forming approximately two-thirds of South Africa's future low-grade hematite resources. The production costs for South African iron ore producers are approximately double that of the largest iron ore producers, namely, Brazil and Australia. This in conjunction with volatile commodity prices, necessitated a cost-sensitive beneficiation strategy for low-grade hematite to sustain the industry and extend life of mine. A BIF sample grading at 44% Fe and comprising predominantly of hematite and quartz with minor amounts of magnetite and goethite was subjected to three fines gravity processing routes to establish the amenability of this sample to beneficiation. To provide flexibility for iron ore producers who still have high-grade resources available, two product grades were considered, namely a 60% Fe product for further blending or a 63% Fe product for direct sales.

The gravity flow behavior of blasted ore and caved waste in sublevel caving (SLC) mines is complex. The shape of fragmented ore and caved waste is identified as one of the principal factors influencing the gravity flow of ore. To investigate the effect of the particle shapes on the gravity flow, a code was developed to generate polyhedral fragments in different shapes and divide them into internal elements. Then these fragments were imported in the LS-DYNA code to generate SLC models containing blasted ore and caved waste and model the extraction process. To model the non-continuous loading process, the gravity flow was considered to be an intermittent process by setting a switcher at the extraction point. The flow behavior of ore from the numerical modeling is in agreement with the experimental results. The cumulative dilution of ore by waste is up to around 30%, which agrees with the results of the field survey.

The collapse of a mine pillar is a catastrophic event with great consequences for a mining operation. In spite of the low probability of occurrence for a pillar collapse in comparison to other ground control instability issues, these consequences make these events high risk. Therefore, the design of these structures should be considered from a risk perspective rather than from a factor-of-safety deterministic approach, as it has been traditionally done. This work presents a risk-based pillar design framework that enables to characterize discontinuities' effect in pillar strength, as well as accounting for the possible range of stresses that will be acting on pillars. The proposed methodology is based on the integration of stochastic discrete element modeling for pillar strength estimation, and stochastic continuous modeling for pillar stress determination. This approach was evaluated in an underground dipping stone mine. Using the reliability analysis method, results from the stress estimation model were integrated with those obtained from the stochastic DEM approach, thereby enabling the probability of failure estimation for the pillars throughout the mine. Finally, the methodology was validated by comparing numerical modeling results with LiDAR and photogrammetric surveys from the mine. Results from this design framework provide additional decision-making tools to prevent pillar failure from the design stages by reducing uncertainty. The proposed method enables the integration of pillar design into the risk analysis framework of the mining operation, ultimately improving safety by preventing future pillar collapses.

Accurately predicting haul truck (HT) travel times (TT) in underground mines is essential for enhancing operational planning, as it allows planners to forecast extraction rates at each work face, minimize queue-related downtime, and ultimately increase productivity. However, in underground environments where GPS signals are unavailable, beacon-based locating systems have not yet been utilized for this predictive purpose. This study addresses that gap by introducing a machine learning approach for HT TT prediction that relies exclusively on beacon detection data, thus eliminating the need for traditional telemetry. The proposed method combines three route-segmentation strategies-full-route, short-segment, and major-segment predictions-with Gaussian mixture models, long short-term memory networks, and a stacking ensemble. Validated on two underground mines, it outperformed industry benchmarks, reducing prediction error by up to 34% on ascending routes and 18% on descending routes while achieving even greater precision for autonomous HTs. It showcases the untapped potential of beacon-based location systems for predictive applications, supporting mine planners.

This assessment was designed to explore and characterize the airborne particles, especially for the sub-micrometer sizes, in an underground coal mine. Airborne particles present in the breathing zone were evaluated by using both (1) direct reading real-time instruments (RTIs) to measure real-time particle number concentrations in the workplaces and (2) gravimetric samplers to collect airborne particles to obtain mass concentrations and conduct further characterizations. Airborne coal mine particles were collected via three samplers: inhalable particle sampler (37 mm cassette with polyvinyl chloride (PVC) filter), respirable dust cyclone (10 mm nylon cyclone with 37 mm Zefon cassette and PVC filter), and a Tsai diffusion sampler (TDS). The TDS, a newly designed sampler, is for collecting particles in the nanometer and respirable size range with a polycarbonate filter and grid. The morphology and compositions of collected particles on the filters were characterized using electron microscopy (EM). RTIs reading showed that the belt entry had a greatly nine-times higher total particle number concentration in average (~ 34,700 particles/cm) than those measured at both the underground entry and office building (~ 4630 particles/cm). The belt entry exhibited not only the highest total particle number concentration, but it also had different particle size fractions, particularly in the submicron and smaller sizes. A high level of submicron and nanoparticles was found in the belt conveyor drift area (with concentrations ranging from 0.54 to 1.55 mg/m among three samplers). The data support that small particles less than 300 nm are present in the underground coal mine associated with dust generated from practical mining activities. The chemical composition of the air particles has been detected in the presence of Ca, Cu, Si, Al, Fe, and Co which were all found to be harmful to miners when inhaled.

Stockpiling and storage of topsoil for use in reclamation and revegetation are common practices for many mining operations. However, stockpiling can lead to significant changes in topsoil physical and biogeochemical properties that may be detrimental to reclamation. The objective of this research was to assess the effect of long-term stockpiling on soil biogeochemical properties in a semiarid region. We hypothesized that soil properties would change systematically with depth reflecting a shift to anaerobic conditions and resulting in a general decrease in soil health. To address this hypothesis, boreholes > 20-m deep were drilled into a 14-year-old topsoil stockpile at a copper mine in Arizona and samples collected every ~ 75 cm. Samples were analyzed for soil DNA biomass, texture, general agronomic properties, mineral composition, oxalate and dithionite extraction of active mineral phases, and total elemental composition. Depth profiles revealed non-systematic changes in biogeochemical variables with depth, including variation in soil DNA biomass, organic matter (OM), extractable nitrate (NO-N) and ammonium (NH-N) nitrogen, plant-available manganese (Mn) and iron (Fe), and oxalate-extractable Mn and Fe. Differences in biogeochemical properties were associated with zones of variable redox state mediated by OM content and layer depth. Anaerobic zones were observed at depths greater than 4 m where OM > 1%, and aerobic zones were observed at depths up to 15 m where OM < 1%. This study demonstrates the importance of stockpile composition on biogeochemical processes during storage and contributes to improved understanding of topsoil management as a resource for reclamation of degraded mine lands in semiarid environments.