Search Documents

By Lynn Salvati, Colin LaVassar, Loic Galisson, Joel Theodore, Lynette Sla

"Sound Transit’s University Link and Northgate Link projects will add 6.75 miles (10.9 km) of twin-bored tunnel to Seattle’s light rail system, extending the route north from downtown Seattle. The tunnels are being constructed primarily in glacial soils using pressurized-face tunnel boring machines. Cover over the tunnel alignment varied from 13 feet to over 300 feet (4–91 m). Since the tunnels are located in densely populated urban areas, controlling ground movements and monitoring settlement were essential to success of these projects. Hundreds of geotechnical instruments, including extensometers, surface settlement points, and near-surface settlement points, were used in both projects to monitor settlement. The observed data were compared to settlement predictions made prior to tunneling, and analyses performed to update empirical factors to better estimate settlements. Recommendations for designing efficient and cost-effective settlement monitoring programs are provided based on the review of the monitoring data and analyses.INTRODUCTIONThe paper includes data from Sound Transit’s University Link and Northgate Link projects. These projects will add 6.75 miles of twin-bored tunnel to Seattle’s light rail system. The tunneling for University Link will extend the light rail system from downtown Seattle to the University of Washington. Tunneling from downtown Seattle to the Capitol Hill Station was completed under the U230 contract, and tunneling from the Capitol Hill Station to the University of Washington Station was completed under the U220 contract. The Northgate Link extension will extend the light rail line north of the University of Washington, including approximately 3.5 miles (5.6 km) of twin tunnels between the University of Washington Station and the Maple Leaf Portal and two stations, U District Station and Roosevelt Station. Tunneling for the Northgate Link project is still underway as part of the N125 project. At the time of writing, tunneling from the Maple Leaf Portal to Roosevelt Station has been completed. Therefore data labeled as N125 in this paper only include the portion of the alignment from the Maple Leaf Portal to Roosevelt Station."

Jan 1, 2016

By Laura Suarez, Jörgen Kajberg, Pär Jonsén

How does an investigation into the breakage characterization of electric arc furnace (EAF) manganese slags contribute to a more responsible usage of resources throughout the life cycle of steel products and reduction of carbon emissions? The main goal of this study is to increase the knowledge on the mechanical response of manganese slag to open the potential of pyrometallurgical residues to become secondary material in industrial applications such as infrastructure construction, fillers, binders and soil stabilization, among others.

Mar 1, 2024

By Min Chen, Qinghua Liang, Weishan Yan, Yuan Feng, Shigang Wang

Various coal mine robots (CMRs) and unmanned aerial vehicles (UAVs) are implemented to explore unknown mines for improving the safety and efficiency of mining. It is challenging for CMRs and UAVs to achieve accurate positioning due to the absence of the Global Positioning System (GPS), poor lighting conditions, and similar geometric features in complex mine scenes. LiDAR-based localization and mapping methods are more accurate than others, while long-time running in large-scale scenarios will introduce nonnegligible cumulative errors. This study presents a semantic-aided Li- DAR simultaneous localization and mapping (SLAM) with loop closure, which leverages the uniqueness of mine intersection structure to establish stable semantic loop closure. Specifically, we propose a semantic intersection descriptor of translation and rotation invariance, which encodes 3D point clouds of the same intersection from different positions and viewpoints into a unified image. By using the semantic descriptor, we can construct a constant loop constraint when the same intersection is revisited from different directions to reduce cumulative drift. We provide experimental validation using large data sets collected in two large underground mines, namely, a simulated Edgar mine deployed in ROS Gazebo and a public underground mine data set provided by ETH. Experimental results show that the proposed method has higher localization accuracy and outperforms the existing LiDAR-based SLAM strategies.

Feb 1, 2024

By Martin Langenderfer, Catherine Johnson, Alexander Douglas

Mine haul roads degrade rapidly due to extreme loads on suboptimal construction materials. Unmanned aerial vehicles (UAV) are suited to quantify large-area road-network conditions, such as surface roughness, defects and grade to optimize remediation of poor conditions and reduce overall costs. Mine haul roads present unique challenges, such as material type and edge characteristics, to automatic road detection that often fails, requiring manual road input. This research work proposes a new method using the road center determined by the principal curve of a haul truck’s path. Analysis grids were created from this center line. A dense point cloud from UAV photogrammetry was generated and multiple linear regression analysis was conducted on each individual grid. The root-mean-square error in each grid indicates the surface roughness, and the change of slope between grids indicates the road grade inconsistencies. This method was applied to 26 road sections, and the results were validated by images taken from the truck operator’s vantage point. Critical defects were identified including excessive pothole formation, corrugation, depressions retaining water, and narrowing of travel lane. The results demonstrate this is a valid method of road identification and quantification of road defects at a mine site.

Apr 1, 2024

By Philani Larrance Ngwenyama, Ronald CW Webber-Youngman

The survival chances of trapped miners in underground mines depend on how quickly they can be located and rescued post-accident. During entrapments, emergency rescue is highly desired but can be hindered by the lack of positioning information when a fit-for-purpose missing-person locator system is not available. Various types of missing-person locator systems are available to aid search-and-rescue operations. From the wide range of the available systems, selecting the most suitable one becomes the next challenge. The available systems have not been measured if they are fit-for-purpose or not, and to what situation. This study proposes user requirements that can be used as a guideline to facilitate the system selection process. These user requirements provide a framework for the design and development of a fit-for-purpose missing-person locator system. The user requirements can also be used for evaluating the performances of a particular system, predict its success, and also drive future research toward developing new technology to enhance the capabilities of the current systems.

Apr 1, 2024

By Kasimcan Koruk, Julian M. Ortiz

A geological model accounting for uncertainties possesses important advantages for resource estimation. Machine learning algorithms (MLAs) employed on multivariate geochemical datasets open up ways to new methodologies for such geological models with ease in comparison to traditional geostatistical methods. This article proposes a two-step MLA with an ensemble implementation to define geological domains and their uncertainties based on geochemical data. The proposed workflow is applied hierarchically on a dataset from a porphyry copper deposit to perform binary classification that can be attributed to alteration domains.

Mar 1, 2024

By Ewan Wingate, Ranjit Prasad, Yanjun Liu

The phosphorus journey begins with the extraction of primary phosphorus in the form of phosphate in apatite through openpit mining and, in some rare cases, underground mining methods. The ores are processed in beneficiation plants to remove impurities before the phosphate rock concentrate is either sold on the open market or converted into phosphoric acid in downstream chemical production facilities by the wet acid process or thermal phosphorus routes. These can in turn be converted into fertilizers, as well as used in the food and electronic industries. The advent of the EV battery has given rise to a new use for purified phosphoric acid in the production of lithium ferro phosphorus (LFP) cathode material for EV battery cathode assemblies. The production of LFP relies on raw materials such as lithium carbonate, lithium hydroxides, iron salts and purified phosphoric acid.

Feb 1, 2024

By Jaeheon Lee, Junmo Ahn, Jae-Yeon Kim, Yoo-Jin Kim, Jiajia Wu, Eun-Woo Kim, Jai-Won Byeon, Jun-Jae Lee

The surge in demand for battery materials, coupled with environmental challenges linked to battery disposal, underscores the need to recycle spent lithium-ion batteries (LIBs). Green recycling approaches, in particular, have garnered attention for battery recycling. In this study, a hydrometallurgical method using a synergetic organic lixiviant combining methanesulfonic acid (MSA) and citric acid (CA) as an alternative to inorganic mineral acids was introduced as a green approach to recycle cathode materials of LIBs. The conditions for leaching and recovery processes were optimized. Cathode materials were regenerated using the recovered materials. Moreover, the leaching performance and economic feasibility of this leaching system were compared with those of various other organic acids.

Feb 1, 2024

By S. J. Schatzel, K. M. Ajayi, E. N. Rubinstein, Z. Khademian

This study simulates the impact of a shale gas well casing breach near a longwall mine. Field studies are conducted to measure mining-induced permeability changes over the abutment pillar of a longwall mine, and a geomechanical model is developed in 3DEC, a three-dimensional numerical modeling code, to predict the aperture of fractures in the overburden at the study site. The predicted aperture values are used to determine mining-induced permeabilities, and the results are compared with the field measurements. These aperture values are provided as inputs into fracture flow code (FFC), which generates a stochastic discrete fracture network (DFN) model for the study site and predicts the potential shale gas flow to the mine. Results from 100 DFN realizations are statistically analyzed using the bootstrapping method to compensate for notable variation in fracture geometry. The results show a significant difference between the gas inflow for nearby panels due to increase in the induced permeability during mining of the second panel. The average gas flow to the mine was calculated as 4.72 × 10 m3/s (49 cfm) for a hypothetical breach at the Sewickley horizon during the first panel mining, 8.97 × 10 m3/s (19 cfm) for a hypothetical breach at the Uniontown horizon during the first panel mining, 2.16 × 10 m3/s (458 cfm) for a hypothetical breach at the Sewickley horizon during the second panel mining, and 8.07 × 10 m3/s (171 cfm) for a hypothetical breach at the Uniontown horizon during the second panel mining. Depending on the mine ventilation system, this could result in methane concentrations exceeding regulatory limits. Hence, these findings provide insights into the potential risk of an unconventional gas well casing breach near a longwall mine under shallow cover.

Feb 1, 2024

By AMIR EHSAN KIANFAR, Moritz Ziegler, TOBIAS HARTMANN, ELISABETH CLAUSEN

Accurate positioning information is a central step in the process of increasing automation and digitalization in the mining industry. Underground mine environments are prime examples for GNSS-denied environments that pose several additional challenges for the employed indoor positioning system (IPS). This work presents an ultra-wideband (UWB)- based system specifically tailored for underground mine environments. Initially, the UWB technology is reviewed and basic concepts of IPS are explained. Both software and hardware are described in detail, including positioning algorithms, electrical circuitry and the mining-compatible enclosure. Finally, the results from field tests in an underground mine are presented and positioning performance and the influence of dilution of precision (DOP) on positioning results are empirically evaluated. The results show that the localization errors are mostly below 1 m. Individual zones of high localization errors are suspected to be caused by noise interference. Significant DOP influence due to the mining drift geometry can be confirmed. The system shows promising localization results for different mining applications, while influences negatively impacting the accuracy are presented as items for future research.

Jan 1, 2024

By Mustafa Kumral, Yuksel Asli Sari

Economic evaluations of underground mining operations are made based on the estimated or simulated grades of the block model as the actual values are not known. Depending on how the planning decisions are made, the risk of the operation can be managed and decreased. This research introduces a mixed-integer linear programming (MILP) model for stope sequencing optimization that considers the uncertainty associated with net present value (NPV) using chance-constrained programming (CCP). The introduced method permits achieving a balance between maximizing NPV and reducing the associated operational risk through transforming the problem into a multiobjective problem, where the objectives are maximizing the NPV and minimizing the risk. This risk is expressed in terms of the standard deviation of project outcomes, taking into account multiple possible scenarios. In a case study, the efficiency of the method was demonstrated as a decision-making tool capable of translating a specified risk or reliability level into a stope sequencing plan.

Jan 1, 2024

By MAURICE SUNKPAL, Taghi Sherizadeh, Kutay E. Karadeniz, Dogukan Guner, Samuel Nowak

In this study, various rib bolting scenarios were investigated to better understand the effectiveness of the support systems. A coal mass constitutive model is implemented to a distinct element method (DEM) code, and rib factor-of-safety (RibFOS) analyses were performed by applying strength reduction for the coal matrix and explicitly modeled face cleats. Ribs with various overburden depths and mining heights composed of solid banded bright coal were considered. Different scenarios such as rib bolt length and number of bolts were studied to quantify the effect of primary rib support density on rib stability. As a result of the unsupported coal rib analyses, a decaying exponential relationship is proposed between the mining height-overburden depth and the RibFOS. The developed coal rib models clearly show the coal-rib bolt interaction and illustrate how the addition of rib bolts restricts the movement of the coal rib. The results reveal that the strength-reduction method in DEM code with the coal-mass model can aid in the development of practical primary sup- port charts, which can help in the rib support design process.

Feb 1, 2024

By Ankit Jha, Javad Sattarvand, Aaron Young

Blockchain technology is one of the prominent disruptive technologies that are being implemented in several disciplines. The application of blockchains in the mining and mineral industry can provide utility to several processes especially when the industry is undertaking digital transformation. The governing principles of blockchain technology are applicable in undertaking transformation in several processes within the mining industry. This study investigates the applications of blockchain technology within the realms of the mining industry and identifies key areas of implementation. A systematic review of publications on academic platforms relating to blockchain technology in the mining industry did not retrieve a considerable number of articles. Consequently, a thorough review of white papers and articles authored by individuals on use cases within the mining industry is compiled and presented in this review article. This review article identifies all the potential areas within the mining industry where blockchains could provide value and improve processes through their implementation. The broad area of implementation of blockchains includes supply chain, traceability in spares parts, contract management, regulatory compliance and cybersecurity.

Mar 1, 2024

By Shangyong Lin, Wei Sun, Weiping Liu, Muhammad Azam, Junfeng Cheng, Yujie Zhao, David Asubonteng, Michael Ngoie

Copper concentrates have wide application in global smelting operations, comprising primarily of chalcopyrite (CuFeS2) as the principal mineral, accompanied by chalcocite (Cu2S) and bornite (Cu5FeS4) as secondary copper-bearing minerals. However, these concentrates frequently harbor detrimental impurities, notably fluorine ions, which can cause various complications during the smelting process. Moreover, an elevated fluorine content in copper concentrates may entail financial penalties and sales constraints. This review conducts a comprehensive analysis of existing methods for the removal of fluorine, presenting a nuanced assessment of their merits and demerits. It also provides valuable insights into the current landscape of fluorine elimination from copper concentrates and pinpoints pivotal areas warranting future investigation. This review endeavors to serve as a pragmatic resource for researchers and industry professionals operating within this domain.

Jan 1, 2024

By S. Afrouz, C. Keles, W. R. Reed, E. Sarver, T. Akinseye, A. Greth, L. Pan, F. Animah

The resurgence of severe lung disease among U.S. coal miners has not only highlighted the need for improved dust controls, but also the need for an improved understanding of dust characteristics and monitoring strategies [1]. Following up on prior work by the National Institute of Occupational Safety and Health (NIOSH) to demonstrate a novel wet dust collection system on a roof bolter [2], the current study explores the effect of that system on dust characteristics and uses interlaboratory comparisons to comment on analytical methods. Results indicate the wet system did not appreciably affect the composition or size of respirable dust in the vicinity of the operating roof bolter. However, the system does appear to have substantial benefits for the operator. NIOSH has already shown it can reduce the respirable dust mass concentration to which the operator is exposed during dustbox cleanout [2,3], which is a frequent maintenance activity that can re-aerosolize dust, and new results here indicate the silica and silicates content in this dust may also be reduced, thereby reducing the overall hazard. Moreover, regarding analytical methods, excellent correlation was demonstrated between measurements of quartz mass, taken first by NIOSH and then by a university laboratory, using direct-on-filter Fourier transform infrared (FTIR) analysis. This method is the basis for envisioned “end of shift” silica monitoring (quartz is the predominant form of crystalline silica in coal mines) [4]. For particle-level analysis by scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), there was more variability in results generated by two independent university laboratories.

Mar 1, 2024

By Liming Yuan, Wei Tang, RICHARD THOMAS, JOHN SOLES

Lithium-ion (Li-ion) battery pack fires pose great hazards to the safety and health of miners. A detailed experimental study has been conducted at the National Institute for Occupational Safety and Health’s (NIOSH) Pittsburgh Mining Research Division (PMRD) to investigate the effectiveness of different fire suppression systems on Li-ion battery pack fire extinguishment. Tests were conducted in a well-ventilated container. Two sizes of battery packs (12 V and 24 V) were heated by heater strips to trigger thermal runaway and fire. Water mist with different flow rates, ABC powder, type D dry chemical, and water mist with F500 additives were used as the fire suppression agents. Multiple thermocouples were installed on the battery packs to measure the temperature evolution during the tests. The results indicate that the water mist with F500 additives is the most effective suppressant among the agents tested. Dry chemicals, however, do quench the fire for a moment, but cannot prevent re-ignition of the battery since they do not provide enough cooling. The findings of this paper can be used to develop safer battery fire suppression techniques in mining environments.

Jan 1, 2024

By JIAQI JIN, Chen-Luh Lin, Amanda N. Erskine, Jan D. Miller, Shijie Wang

The liberation and exposure of valuable mineral grains in ore particles are of significant importance in understanding the efficiency of flotation separations. A flotation feed sample from the Kensington concentrator was scanned by micro Xray computed tomography (micro-XCT), to determine the liberation and exposure of auriferous pyrite grains. The analysis results suggest a satisfying extent of liberation for particle sizes smaller than 212 μm. Theoretical flotation recovery of pyrite for selected particle size fractions was predicted from the three-dimensional liberation and exposure analysis. The plant flotation tail was also characterized by micro-XCT to identify liberated and partially liberated pyrite particles that might not be collected into the concentrate. However, liberation analysis of the tail sample revealed that the majority of liberated pyrite was recovered in the plant flotation circuit. Trainable Weka, a machine learning segmentation approach, was compared with the Watershed thresholding segmentation for the 106 × 45 μm particle size fraction scanned at a voxel size of 1.85 μm. Improved segmentation of small particles was found using the machine learning method.

Mar 1, 2024

By Xuebin Liu, Yi Shang, Can Zhou, Hongqiu Zhu, Junbo Du

In the neutral leaching process of zinc hydrometallurgy, the pH value directly affects the leaching rate of zinc calcine. However, due to the complex mechanism of the leaching process and frequent fluctuation of working conditions, it is difficult to control the pH value by manual control. Therefore, this study proposes a fuzzy control method based on rule extraction under multiple working conditions, and analyzes the pH control performance. Firstly, the different operating states are classified according to process mechanisms and the Pearson method. Secondly, under the framework of the active learning algorithm, the approximate linear dependence (ALD) method is introduced to iteratively select samples with rule information in the original sample set for manual annotation. Then, the support vector machine (SVM) method is used to extract fuzzy control rules in different working conditions. Finally, a fuzzy rule set is established according to the samples mapped by the support vector. The simulation results based on industrial data show that the proposed method has better control performance than conventional fuzzy control and proportional–integral–derivative (PID) control.

Apr 1, 2024

By Andrea Brickey, RICHARD AMOAKO, Akshay Chowdu

Production forecasts derived from the medium-term schedule represent the best path forward for underground mining operations to achieve corporate and operational goals. Unforeseen circumstances, such as equipment breakdown, can cause significant deviations from established production forecasts in the short term. Such situations require timely mitigation of the effects of the deviations in order to stay as close as possible to the medium-term plan. This paper presents a deterministic mathematical formulation for short-term scheduling that addresses this challenge. The formulation is able to make up for deficits resulting from operational disruptions by minimizing deviations from medium-term production goals and medium-term activity start dates. We demonstrate this in a case study by simulating disruptions involving reduction in ore extraction capacity and development advance rate. Aside from the rescheduling capability, this formulation can help mine planners conduct analysis on the impact of various disruptions on the schedule. The formulation can help identify those conditions or disruptions that are more detrimental to the achievement of forecast targets, or otherwise. The formulation also affords mine planners the flexibility to prioritize one production goal over the other, depending on operational conditions at the mine. In the future, we seek to incorporate in the formulation respirable dust, diesel particulate matter and ventilation constraints in order to create more realistic schedules, and enhance miners’ health and safety.

Jan 1, 2024

By Hakan Uyguçgil, Beril Bayraktar, Adnan Konuk

In mining, which is one of the industries with the highest risk of occupational accidents, a primary goal is to enhance safety through the thorough investigation of accidents using reliable methodologies. In this research, the data from 13,653 accidents reported in the Karadon Hard Coal Enterprise between 2000 and 2011 were analyzed and compared using the life-table and Kaplan-Meier methods. Accident records were classified and analyzed into four categories: environment-related, equipment-related, person-related and other accidents. Findings in terms of survival time indicate that environmentrelated and person-related accidents had the highest risk in Karadon, with equipment-related accidents having the lowest. This study established the reliability of using survival analysis methods to investigate occupational accidents in the mining sector. Given that environment-related and person-related accidents occur in a relatively short period, such as one year after starting work, it is recommended that research be done to improve workplace and occupational safety measures and broaden the training given to miners. Additionally, it is determined that increasing the use of automation and mechanization in underground coal mines, combined with developing a thorough equipment safety training program to raise awareness of the danger, can help prevent person-related occupational accidents caused by the interaction between equipment.

Feb 1, 2024