Mining, Metallurgy & Exploration最新文献

{"title":"Lessons Learned From Haul Truck Operator Near-Miss Events: Use of the Critical Decision Method to Identify Strategies to Improve Operator Safety in Mining","authors":"Cassandra L. Hoebbel, Jennica L. Bellanca, Jonathan K. Hrica","doi":"10.1007/s42461-024-01066-3","DOIUrl":"https://doi.org/10.1007/s42461-024-01066-3","url":null,"abstract":"<p>Accidents involving powered haulage and mobile equipment such as haul trucks often account for the greatest number of fatalities in the mining industry each year. Despite previous analyses that have identified root causes and other contributing factors, there is still a need to better understand the events leading up to these types of accidents, what lessons may be learned, and what strategies can be employed to prevent fatal accidents from occurring. This study examines naturalistic decision-making (NDM) using the critical decision method (CDM). The CDM is a retrospective interview approach used to explore time-limited, high-stakes decision-making that has not been often used in the mining industry. In this study, the CDM is used to obtain more information about what happens prior to, during, and after a potentially fatal situation such as a near-miss event, loss of control, or minor accident involving equipment damage. Researchers captured first-hand accounts from 21 haul truck operators involved in near-miss events from mine sites of various sizes and commodities throughout the USA. These accounts provide rich and detailed narratives from the perspective of haul truck operators themselves and reveal insights into what decisions haul truck operators make, what sensory cues they perceive, and what strategies they employ during challenging and non-routine situations so that haul truck operators can be better prepared in the future. Themes critical to operator decision- making emerged from the data with the top three including, <i>know your truck</i>, <i>situational awareness</i>, and <i>safety first</i>. These themes suggest that haul truck operators need to have a mastery level understanding of how their truck works in order to effectively react, that haul truck operators need to maintain an understanding of conditions and their environment, and that haul truck operators should prioritize safety when making decisions. To support haul truck knowledge acquisition and retention, mine operators may consider providing more detailed and hands on training including practice time in a variety of conditions. To support situational awareness, mine operators may consider investing in collision warning technologies and emphasizing good communication practices. Lastly, mine operators may consider continually emphasizing safety and their commitment to safe practices to help all mine workers internalize safety as a value, thereby reducing or eliminating related conflicts in decision- making. These results, along with potential solutions offered by study participants, can help to inform future research, raise awareness about hidden hazards, and build more creative interventions and realistic training scenarios for use by the industry to address haul truck safety issues.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"124 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Dynamic Recognition Method of Rock Burst Precursor Information Based on Adaptive Denoising and Object Detection","authors":"Shenglei Zhao, Jinxin Wang, Enyuan Wang, Qiming Zhang, Huihan Yang, Zhonghui Li","doi":"10.1007/s42461-024-01055-6","DOIUrl":"https://doi.org/10.1007/s42461-024-01055-6","url":null,"abstract":"<p>Acoustic emission (AE) and electromagnetic radiation (EMR) can reflect the precursor information of rock burst and play important roles in rock burst monitoring, early warning, and prevention. However, the existing denoising methods of AE and EMR monitoring signals are poor, and the recognition of precursor information lacks comprehensiveness, accuracy, and real-time. This paper presents a novel method combining adaptive denoising and object detection to realize dynamic recognition of rock burst precursor information. Successive Variational Mode Decomposition (SVMD) adaptively decomposed the AE and EMR monitoring signals such as pulse and intensity into different mode components and Kalman Filter (KF) performed on each mode component to eliminate redundant noise. Furthermore, the YOLOX object detection algorithm recognizes the precursor information in the time–frequency domain after noise removal, including the time interval, frequency band, and energy. The case study illustrates that the precursor response of the AE and EMR monitoring signal in time–frequency domain is highlighted by denoising, and the average accuracy of different types of precursor recognition reaches 96%. Finally, the consistency of the identified precursor information and field records shows the feasibility and effectiveness of the method, which has practical guiding significance for improving the level of rock burst prevention.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"35 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparative Experimental Analysis of the Effect of Spiral Geometry on the Separation of Fine Chromite Particles. Part 1: Potential Downstream Impacts","authors":"Damla Izerdem","doi":"10.1007/s42461-024-01063-6","DOIUrl":"https://doi.org/10.1007/s42461-024-01063-6","url":null,"abstract":"<p>This study focuses on examining the separation performance of spirals employed in a classified fine-sized (− 200 + 2 5 µm) chromite ore. Dwindling global reserves of high-grade chromium ores and dispersing minerals in the form of fine particles make it attractive to find alternative and efficient methods for enriching these minerals in an economically as well as environmentally sustainable manner. Experimental tests were conducted on three spiral concentrators with distinct geometries. The effects of pulp density, flowrate, and splitter blade positions on the separation efficiency and enrichment ratios were thoroughly examined. The separation variables were comparatively assessed, and response surface method (RSM) was employed for optimization. The results indicated that optimal separation performance was achieved using a small diameter spiral (<i>Ø</i>: 60 cm), whereas the least effective separation occurred in a large diameter spiral (<i>Ø</i>: 100 cm) with a lower pitch angle. The findings revealed that high flowrates and pulp densities adversely affected the separation efficiencies, and the positions of the splitters significantly impacted the quality of the obtained products.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"389 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization and Reprocessing of Artisanal and Small-Scale Gold Mine Tailings","authors":"Abdou Azizi Youpoungam, Sadiye Kantarcı, İbrahim Alp","doi":"10.1007/s42461-024-01059-2","DOIUrl":"https://doi.org/10.1007/s42461-024-01059-2","url":null,"abstract":"<p>Millions of tons of solid waste are generated by artisanal and small-scale gold mining in several regions of the world. This study focused on the tailings from the Abu Hamad artisanal gold mine located in northeastern Sudan. The results of the analyses carried out showed that this amalgam waste contained on average 5.5 g/ton of gold, 50 g/ton of mercury, 3.3 g/ton of silver, and 191 g/ton of copper. The particle size distribution was between − 10 and + 300 µm, and the average grain size was about 65 µm. Metal distributions showed that gold and mercury grades increased in fine-grained size fractions. X-ray diffraction analyses showed that quartz is the main constituent mineral phase of these residues. The presence of gold, mercury, and other accessory minerals such as sulfide and oxide minerals was revealed by the SEM–EDS. Microscopic analysis showed that majority of gold particles in these tailings are free while few others were occluded in quartz. The gravity tests carried out showed that the best gold recovery result was 47.18%. Bench scale stirred cyanide leaching tests showed that gold, mercury, copper, and silver can be recovered at 90%, 71%, 32%, and 22%, respectively, in 24 h. These high gold recoveries show that these tailings offer a possible commercial secondary resource for gold mining. These wastes contain high mercury grades, which can cause various environmental and public health problems, that is why new environmentally friendly treatment techniques should be developed to recover gold and mercury from these tailings.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"26 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review of the Applications of Through-the-Earth (TTE) Communication Systems for Underground Mines","authors":"Philani Larrance Ngwenyama, Ronald C. W. Webber-Youngman","doi":"10.1007/s42461-024-01056-5","DOIUrl":"https://doi.org/10.1007/s42461-024-01056-5","url":null,"abstract":"<p>Underground mining accidents have the potential of leaving miners trapped in unknown and life-threatening locations for an extended period of time. The lives of the trapped and unaccounted-for miners are at risk and require emergency rescue. But, the primary tracking systems are highly susceptible to damage during accidents and are most likely to be defunct and inoperable post-accident. This prompted the need for a robust and reliable post-accident communication and locator system. Subsequently, the through-the-earth (TTE) communication systems were developed and tested in underground mines. Under ideal conditions, these systems are capable of post-accident full-duplex two-way voice, text, and data communication and fingerprint detection of the geolocations of the trapped miners. This is achieved through a wireless link established by the transmission of electromagnetic and seismic waves between surface and underground, even in challenged underground environments. Unlike the primary tracking systems, the TTE communication systems do not require extensive shaft-to-workplace backbone infrastructure. This has made the TTE systems to be less susceptible to damage and therefore suitable for post-accident communication. Instead, the Earth’s crust acts as the signal transmission medium which forms an uplink and downlink communication path. This is achieved by injecting an electric current into the ground using electrodes, by transmitting magnetic fields from a radiating loop antenna, or by inducing fingerprint geolocations using seismic waves. Range and data rates are the critical requirements for the effectiveness of these systems and are dependent on factors such as the antenna design, frequency, and rock properties. This study provides a review of the applications of the different types of TTE communication systems, their evolution, factors that affect them, and techniques for improving their efficiencies and capabilities. These systems present the mining industry with an opportunity to improve safety by providing post-accident communication and locating trapped miners as quickly as possible. This will improve their survival chances and ultimately reduce fatality rates in the mining industry.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"2019 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution and Disaster-Causing Characteristics of Air-Leakage Fractures in Shallow Thick Coal Seams: A Case Study","authors":"Wei Zhang, Deming Wang, Zhenhai Hou, Chenguang Wang","doi":"10.1007/s42461-024-01068-1","DOIUrl":"https://doi.org/10.1007/s42461-024-01068-1","url":null,"abstract":"<p>Composite air leakage from mining-induced fractures is a critical cause of coal spontaneous combustion and gas explosions in a shallow-buried goaf. Physics simulations and numerical calculations were performed to elucidate the dynamic evolution law of air-leakage fractures during mining. The results showed that overburden and surface fractures were the main channels for airflow in the goaf. Additionally, the generation of all fractures was primarily controlled by the key stratum. The dynamic development of overburden fractures was evident during mining, and the fractures underwent opening, closing, and stabilization. The spatial distribution of the overburden fractures was shaped like a double trapezoid. In the low trapezoid, the overall fracture density was high, but the middle fractures were poor because of compaction. In the high trapezoid, horizontal fractures were widely distributed and relatively large, and vertical fractures were mainly distributed on the sides and middle, which were interconnected with the horizontal fractures and penetrated the surface to form composite air-leakage channels. The abundance of fractures from the surface and goaf was the primary cause of multi-source air leakages deep behind the 2421–1 working face in the Baijigou coal mine.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"11 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geofingerprinting of Coltan Using Handheld Spectroscopic Devices","authors":"Samuel Kessinger, Jon Kellar, Prasoon Diwakar","doi":"10.1007/s42461-024-01030-1","DOIUrl":"https://doi.org/10.1007/s42461-024-01030-1","url":null,"abstract":"<p>Following the enactment of the Dodd-Frank Act in 2010, specifically Sect. 1502, US companies have been required to report utilizing conflict minerals from the Democratic Republic of Congo (DRC). The conflict mineral coltan, an ore consisting of elements tantalum and niobium, is central to this issue and engenders the need to track and trace the mineral’s supply chain. X-ray fluorescence (XRF) and laser-induced breakdown spectroscopy (LIBS) have been used, in combination with both unsupervised and supervised machine learning, to accurately classify coltan samples with known provenances. Sample spectra were first used as input data into unsupervised machine learning clustering algorithms, upon which dendrogram and constellation plots were generated. The classification achieved via unsupervised machine learning provided the proof of concept necessary to further investigate classification using supervised machine learning algorithms. The sample’s raw spectra were then used to train a supervised machine learning algorithm, consisting of a voting classifier relying on the results from random forest classifier (RFC), linear regression classifier (LRC), support vector classifier (SVC), and multi-layer perceptron classifier (MLPC). The classification achieved using raw spectra was able to achieve accuracies up to ~ 97%. The samples’ raw spectra were pre-processed using principal component analysis (PCA), and the pre-processed data was fed into the same supervised machine learning classifier described above. Accuracies of ~ 98% and ~ 96%, respectively, were achieved. When reviewing the predicted classifications arising from the use of these two different types of spectra, specifically reviewing the confidence score associated with each predicted provenance classification, it was possible to account for the incorrect provenance classifications returned by the voting classifier. If the predicted provenance and associated confidence score obtained via each spectra type was compared to the resulting provenance prediction and confidence score obtained by the other spectra type, and only the prediction with the higher associated confidence score was used, classification accuracies of 100% could be achieved.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"19 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Value of Drilling—A Chance-Constrained Optimization Approach","authors":"Rick Jeuken, Michael Forbes","doi":"10.1007/s42461-024-01061-8","DOIUrl":"https://doi.org/10.1007/s42461-024-01061-8","url":null,"abstract":"<p>Managing uncertainty is a core challenge in mine planning. Mine planners often represent various planning variables, such as equipment performance and geological parameters, as random variables due to inherent uncertainties. This paper looks at geological uncertainty and its impact on mine planning. Some traditional approaches to manage this uncertainty include using conditional simulations or mathematical programming in the planning process. Drilling additional holes, despite its cost, is a common method to reduce uncertainty using additional samples to reduce deposit variance. In this paper, we first outline an ore blending optimization model which uses chance-constrained programming to manage property limit risk when selecting the order of ore feed into a processing facility. In coal mining, in tactical planning horizons, the order of coal seam removal is usually predetermined, allowing a blending model to ensure optimal feed properties. Using chance-constrained programming allows us to blend the uncertainties from geological models to maximize plant output while adhering to property constraints. We use the chance-constrained blending model to determine the value of additional information from infill drilling. The model prioritizes drilling locations that reduce uncertainty and improve blending outcomes. A case study on a coking coal mine in Queensland, Australia, demonstrates the model’s application, highlighting significant improvements in blending by reducing the variance of high-quality blocks. The study concludes that targeting high-quality blocks for variance reduction can better accommodate lower-quality material, offering a more valuable approach than the traditional focus of reducing uncertainty in low-quality blocks. This approach provides insights for improving mine planning strategies and showcases the potential of chance constraints in optimizing ore blending under uncertainty.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"1 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting the Stability of Rock Slopes in the Presence of Diverse Joint Networks and External Factors Using Machine Learning Algorithms","authors":"Sudhir Kumar Singh, Subodh Kumar, Debashish Chakravarty","doi":"10.1007/s42461-024-01060-9","DOIUrl":"https://doi.org/10.1007/s42461-024-01060-9","url":null,"abstract":"<p>The presence of joints in rocks significantly impacts the mechanical behavior and stability of a slope. A better comprehension of the relationship between jointed rock masses and slope stability has been made possible by recent advances in machine learning algorithms and numerical modelling. The purpose of this research is to predict the stability of slopes in the presence of different types of joints (parallel deterministic, cross jointed, Baecher, Veneziano, and Voronoi) with the help of classification-based machine learning algorithms. In order to achieve this goal, 40,290 different cases have been utilized, following numerical simulation using shear strength reduction (SSR) technique in RS2. Geomechanical properties, parameters defining slope geometry, structural properties of joints including properties of filling materials, and the influence of certain external factors have been considered. For these datasets, classification algorithms such as random forest, k-nearest neighbor, support vector machine, logistic regression, decision tree, and Naive Bayes have been utilized. Additionally, the synthetic minority oversampling technique (SMOTE) has been implemented in order to address imbalanced class problems. The results exhibit an encouraging level of accuracy, with random forest and decision tree both achieving 0.98 as an overall accuracy.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"285 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of Crown Pillar Thickness in the Stress Relaxation Zone Surrounding Sub-Level Open Stopes","authors":"Vishal Babu Guggari, Gnananandh Budi","doi":"10.1007/s42461-024-01058-3","DOIUrl":"https://doi.org/10.1007/s42461-024-01058-3","url":null,"abstract":"<p>The excavation of steeply dipping ore deposits using sub-level mining techniques with delayed backfill can cause stress relaxation and concentration in the stope hanging wall and footwall at deeper depths. Designing adequate crown pillars that can withstand significant horizontal stress and prevent the collapse of the hanging wall and footwall is crucial for ensuring safe mining operations. This study developed a methodology for predicting the appropriate crown pillar thickness for depths between 510 and 1000 m based on 240 non-linear numerical models with Mohr–coulomb elastoplastic failure criteria under plane strain conditions with five parameters affecting crown pillar stability. A precise and reliable empirical equation has been devised to compute the safety factor (<i>SF</i>) of the crown pillar. The equation has a high predictive capability with an <i>R</i>² value of 0.85. Design charts were developed for various geo-mining conditions and working depths to estimate the optimal crown pillar thickness.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"65 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}