Mining, Metallurgy & Exploration最新文献

{"title":"Development of Novel Hybrid Intelligent Predictive Models for Dilution Prediction in Underground Sub-level Mining","authors":"Prosper Chimunhu, Roohollah Shirani Faradonbeh, Erkan Topal, Mohammad Waqar Ali Asad, Ajak Duany Ajak","doi":"10.1007/s42461-024-01029-8","DOIUrl":"https://doi.org/10.1007/s42461-024-01029-8","url":null,"abstract":"<p>Tenuous dilution estimates in underground mine production scheduling continue to cause significant variations between schedule forecasts and actual production. This arises partly from the inference of dilution from predecessor stopes’ performance, disregarding that these stopes would have undergone multiple intermediate design changes between scheduling and actual mining. The resultant drill and blast-influenced dilution factors gradually lose its robustness over longer planning horizons or when applied to greenfield or brownfield expansions that do not have prior performance data. To overcome this problem, a new methodology is proposed to predict dilution in underground sub-level open stoping (SLOS) using basic geological, geotechnical and stope design attributes available in the early stage of mine planning. The method utilises principal component analysis (PCA), classification and regression tree (CART) algorithm and stepwise selection and elimination (SSE) analysis. First, SSE analysis was conducted to identify the most important independent variables to be used with the CART algorithm (i.e., the SSE-CART model) to provide a predictive model. PCA analysis was then performed, and the new principal components were used to propose a new comparative model (i.e., the PCA-CART model). Low <i>R</i>² values were observed for both models, necessitating the consolidation of dilution categories to increase the models’ prediction bandwidth. The hybrid PCA-CART model outperformed the SSE-CART model with overall F1 score prediction accuracy of 72% and target dilution category prediction accuracy of over 93% against SSE-CART’s 70% and 72%, respectively. Importantly, this study revealed a 13% minimum underestimation of dilution relative to the original design stopes.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"27 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572923","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":"Research Status and Prospects of Auto-height Adjustment Strategy for Shearer","authors":"Yuwei Zhu, Pengfei Wang","doi":"10.1007/s42461-024-01035-w","DOIUrl":"https://doi.org/10.1007/s42461-024-01035-w","url":null,"abstract":"<p>The development of autonomous shearer height adjustment technology, a crucial component of generalized mining automation, is covered in this study. This study examines the main technical development research in the two directions of coal-rock interface detection and memory cutting in order to investigate the development of shearer auto-height adjustment technology. The development of five methods, such as image recognition method, is introduced in detail in coal rock identification. It lists the shortcomings of each approach and provides an overview of the major variables influencing the advancement of shearer auto-height adjustment technology. Based on the current state of height adjustment technology development and the demand for coal mine intelligence, the following development outlook for auto-height adjustment of shearers is suggested: integrating a variety of cutting-edge technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), and Big Data (Big Data), along with the safety mechanism, to create a more complete and effective auto-height adjustment system for shearers. The article concludes by highlighting ongoing research in this area, which uses data expansion to address the issue of poor data quality while also allowing for the combination of machine learning algorithms, data expansion by the appropriate network model to train high-quality and high-precision models, and the development of memory cutting technology to create a comprehensive, continuous, and accurate independent height adjustment control system of the shearer.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"85 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141552146","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":"Application of Artificial Intelligence to the Alert of Explosions in Colombian Underground Mines","authors":"Luis Vallejo-Molina, Astrid Blandon-Montes, Sebastian Lopez, Jorge Molina-Escobar, Andres Ortiz, David Soto, Jose Torero, Alejandro Toro, Alejandro Molina","doi":"10.1007/s42461-024-01008-z","DOIUrl":"https://doi.org/10.1007/s42461-024-01008-z","url":null,"abstract":"<p>The use of Artificial Intelligence (AI), particularly of Artificial Neural Networks (ANN), in alerting possible scenarios of methane explosions in Colombian underground mines is illustrated by the analysis of an explosion that killed twelve miners. A combination of geological analysis, a detailed characterization of samples of coal dust and scene evidence, and an analysis with physical modeling tools supported the hypothesis of the existence of an initial methane explosion ignited by an unprotected tool that was followed by a coal dust explosion. The fact that one victim had a portable methane detector at the moment of the methane explosion suggested that the ubiquitous use of these systems in Colombian mines could be used to alert regulatory agencies of a possible methane explosion. This fact was illustrated with the generation of a database of possible readouts of methane concentration based on the recreation of the mine atmosphere before the explosion with Computational Fluid Dynamics (CFD). This database was used to train and test an ANN that included an input layer with two nodes, two hidden layers, each with eight nodes, and an output layer with one node. The inner layers applied a rectified linear unit activation function and the output layer a Sigmoid function. The performance of the ANN algorithm was considered acceptable as it correctly predicted the need for an explosion alert in 971.9 per thousand cases and illustrated how AI can process data that is currently discarded but that can be of importance to alert about methane explosions.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"13 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141552121","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":"Delineation of Potential Gold Mineralization Zones in the Kushaka Schist Belt, Northcentral Nigeria, Using Geochemical, Ground Magnetic, Induced Polarization, and Electrical Resistivity Methods","authors":"Sherif Olumide Sanusi, Deborah Ima-Abasi Josiah, Oladele Olaniyan, Gbenga Moses Olayanju","doi":"10.1007/s42461-024-01033-y","DOIUrl":"https://doi.org/10.1007/s42461-024-01033-y","url":null,"abstract":"<p>This study integrated geophysical methods (ground magnetics, electrical resistivity, and induced polarization measurements) in conjunction with fire assay and inductively coupled plasma-atomic emission spectrometry techniques to delineate orogenic gold mineralization potential zones in the Kushaka greenschist belt. Different edge detection filters and a 3D Euler deconvolution technique were applied to magnetic data to delineate geologic structures that control orogenic gold mineralization in the study area. VOXI Earth Modeling™ software was applied to induced polarization and electrical resistivity data to generate gold mineralized targets in the study area. Based on the geochemical findings in this study, orogenic gold mineralization in the belt is associated with galena, sphalerite, monazite, bastnaesite, and manganese oxide minerals and has a metamorphic origin. The total magnetic field results indicate that NE-SW and NW–SE trending structures are primarily associated with gold assay hotspots, indicating that orogenic gold mineralization in this belt is connected to Pan-African orogenic events. Fractured zones with disseminated gold-sulfide deposits and hydrothermal alteration halos exhibit low resistivity and high chargeability signatures. However, the occurrence of disseminated gold-sulfide deposits that infilled quartz veins and fractured zones in the intensely silicified metasedimentary rocks exhibit high chargeability and high resistivity signatures. The produced gold mineralized targeting model correlates well with geologic structures, metasedimentary rocks, and gold hotspots, indicating that lithologies and geologic structures preferentially control orogenic gold mineralization in the belt. Hence, the information gathered in this study would assist miners and academia in determining the drill-hole locations for future gold exploration programs in the area.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"24 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141521296","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":"Operation Parameters Optimization Method of Coal Flow Transportation Equipment Based on Convolutional Neural Network","authors":"Xueqi Yang, Xinqin Gao, Haiyang Zheng","doi":"10.1007/s42461-024-01031-0","DOIUrl":"https://doi.org/10.1007/s42461-024-01031-0","url":null,"abstract":"<p>Mine coal flow transportation has some typical features of long-distance and complex environments. The transportation equipment usually adopts the mode of constant speed, which makes a large amount of energy waste. To solve these problems, the characteristics of the coal flow transportation system are analyzed. Based on a principal component analysis-convolutional neural network (PCA-CNN), the operation parameters optimization method of coal flow transportation equipment is proposed. Taking the transport time, transport cost, and equipment utilization of belt conveyors and other equipment as the optimization objectives, the multi-objective functions are established, and the operation parameters such as transport speed, transport distance, and equipment start-up time are optimized. The PCA and the CNN are respectively used to determine the weight of each objective function and iteratively train the practical production data samples under multiple constraints. The fully connected layer of CNN is constructed by the Lagrange multiplier method. The optimal production mode and operation parameters of the coal flow transportation equipment are obtained, satisfying the multi-objective functions and constraints. Finally, the practical engineering case is simulated by Plant Simulation, and the operation parameters of the coal flow transportation equipment are compared before and after optimization. The research results show that the objective function of each experiment is optimized to some degree. Furthermore, comprising other common algorithms, the advantages and effectiveness of the based-CNN operation parameters optimization method are verified. These have an important guiding significance for energy-saving and efficient coal flow transportation equipment operation.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"29 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141521297","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 New Approach to the Calculation of Bond Work Index with Mixed Grinding Media","authors":"Jiaqi Tong, Caibin Wu, Jingkun Tian, Yihan Wang, Li Ling, Guisheng Zeng, Huiming Shen","doi":"10.1007/s42461-024-01034-x","DOIUrl":"https://doi.org/10.1007/s42461-024-01034-x","url":null,"abstract":"<p>Grinding media influence the energy consumption and efficiency of the grinding process during the calculation of the Bond Work index (BWi), a well-known method for selecting comminution equipment, evaluating milling efficiency, and calculating required milling power. Traditional grinding tests often choose steel balls as the grinding media, but ceramic balls are used widely currently with their high efficiency in grinding. This study aims to calculate the Bond Work index with steel and ceramic balls and explore the equation for the BWi of mixed grinding media (steel and ceramic balls). This paper also proposes a conversion equation of BWi between the mixed grinding media (steel and ceramic balls) and conventional media (steel balls). The results combined the advantages of ceramic and steel balls to improve the grinding capacity and reduce energy consumption.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"3 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141509329","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":"An Integrated Hydrometallurgical Treatment and Combustion Process for Sustainable Production of Sm2O3 Nanoparticles from Waste SmCo Magnets","authors":"Elif Emil-Kaya","doi":"10.1007/s42461-024-01032-z","DOIUrl":"https://doi.org/10.1007/s42461-024-01032-z","url":null,"abstract":"<p>Samarium (Sm), as one of the rare earth elements (REEs), has gained significant attention in the production of SmCo magnets due to their high corrosion and oxidation resistance, as well as their high-temperature stability. SmCo magnets find applications in various industries, including but not limited to national defense, aerospace, military, and medical equipment. Sm and Co have been classified as a critical metal due to its economic importance and supply risk. Recovering Sm from SmCo magnets is an effective method to ensure a stable supply. The present study investigates an integrated hydrometallurgical treatment and combustion process for the preparation of rare earth oxide (Sm₂O₃) powders from SmCo. Initially, SmCo powders is exposed to nitric acid, and the resulting slurry is selectively oxidized at 250 °C to obtain Sm(NO₃)₃, Co₂O₃, and Fe₂O₃. Subsequently, the selectively oxidized powders are leached with water to extract Sm. Sm₂O₃ powders are produced from the obtained leaching solution using an energy- and time-efficient solution combustion process. In this process, once the ignition point of the leaching solution-citric acid complex is reached, combustion occurs and concludes within a short time. The combusted powders are then calcined at different temperatures to produce crystalline Sm₂O₃ powders. Finally, the optimal conditions for the production of Sm₂O₃ are identified, and the produced powder is characterized through XRD and FESEM analysis.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"133 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141521298","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":"Study on the Influence of Grouting Treatment on the Movement and Deformation of Surface in Longwall Coal Mining Goaf Areas","authors":"Qian Hao, QiYin Zheng, ShaoWei Liu, WeiGuo Hao, Xiong Wu","doi":"10.1007/s42461-024-01026-x","DOIUrl":"https://doi.org/10.1007/s42461-024-01026-x","url":null,"abstract":"<p>The grouting treatment of the old goaf in a coal mine is an essential measure to ensure the safety of the road above it. A novel calculation model is proposed to more accurately determine the appropriate treatment range for the goaf on the road. Compared with traditional mining subsidence calculation models, this new model demonstrates improved fitting to the observed deformation in experimental studies. The deformation of the grouted area is caused by the residual deformation of the untreated goaf areas, and the deformation of the treated area is different from that of the area above the coal wall in the mining stage, which is made by the grouting reinforcement body after grouting treatment. The walking rule (walking probability) of the random medium theoretical walking model is enhanced in this paper to describe this distinction, and a calculation model suitable for quantitative analysis of surface residual deformation in road goaf after grouting reinforcement is established. The standard recommended method, the probability integral method, and a newly derived improved calculation formula are compared in this study. The treatment width predicted by the standard recommended method is the widest, reaching 182 m. The probability integral method predicts a narrower width of 139 m; while the improved calculation formula predicts the narrowest width of 124 m. Compared to the former two, the improved calculation formula not only considers factors such as the depth of the goaf, the overlying strata lithology but also the residual deformation and the grouting reinforcement body. An innovative and effective method for calculating the surface deformation of goaf areas after grouting treatment is developed, thereby offering a basis for designing more precise goaf treatment schemes.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"132 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141509354","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":"Stochastic Optimization for Long-Term Planning of a Mining Complex with In-Pit Crushing and Conveying Systems","authors":"Liam Findlay, Roussos Dimitrakopoulos","doi":"10.1007/s42461-024-01005-2","DOIUrl":"https://doi.org/10.1007/s42461-024-01005-2","url":null,"abstract":"<p>Semi-mobile in-pit crushing and conveying (IPCC) systems can help reduce truck haulage in open-pit mines by bringing the crusher closer to the excavation areas. Optimizing a production schedule with semi-mobile IPCC requires integrating extraction sequence, destination policy, crusher relocation, conveyor layout, and truck fleet investment decisions. A mining complex with multiple mines and IPCC systems should be optimized simultaneously to find an optimal schedule for the entire value chain. An integrated stochastic optimization framework is proposed to produce long-term production schedules for mining complexes using multiple semi-mobile IPCC systems. The optimization model has flexibility to select the crusher locations and conveyor routes from anywhere inside the pits. The framework uses simulated orebody realizations to consider multi-element grade uncertainty and manage associated risk. A hybrid metaheuristic solution approach based on simulated annealing and evolutionary algorithms is implemented. The method is demonstrated using an iron ore mining complex.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"34 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141531722","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":"An Information Entropy–based Risk (IER) Index of Mining Safety Using Clustering and Statistical Methods","authors":"Dharmasai Eshwar, Snehamoy Chatterjee, Rennie Kaunda, Hugh Miller, Aref Majdara","doi":"10.1007/s42461-024-01024-z","DOIUrl":"https://doi.org/10.1007/s42461-024-01024-z","url":null,"abstract":"<p>In recent decades, the mining industry in the United States has made significant strides in reducing accidents and injuries. While these improvements are commendable, interpreting these statistics can be challenging due to concurrent declines in workforce size, employee hours, productivity, and operating systems. The Mine Safety and Health Administration (MSHA) of the United States has instituted tools like the Pattern of Violation (POV) and Significant &amp; Substantial (S&amp;S) calculator to monitor safety in mines. However, both have their respective limitations. Various risk indices have been proposed to address these limitations, leveraging multiple matrices from MSHA databases. Yet, the primary challenge lies in effectively integrating these diverse matrices into a cohesive risk index. This research endeavors to develop an information entropy–based risk (IER) index through the optimization of weights assigned to these sometimes-conflicting matrices. The seven-dimensional risk indicators considered for IER index computation encompass (a) citations, (b) orders, (c) significant &amp; substantial citations, (d) penalties, (e) incidents with no lost time, (f) lost time injuries, and (g) proposed penalty for violation. The efficacy of the proposed IER index was assessed using data from MSHA’s underground mines spanning from 2011 to 2020. Validation of the IER index was conducted through application of the BIRCH clustering algorithm in tandem with rigorous statistical analysis. The clustering performance was evaluated using the multivariate analysis of variance (MANOVA) test, followed by post hoc analysis. Box plots and univariate analysis of variance (ANOVA) tests were then employed to substantiate the statistical significance of mean differences in IER index values across clusters. The MANOVA test and subsequent post hoc results underscore the successful clustering of the seven-dimensional risk indices across all time periods using the BIRCH algorithm. The ANOVA test unequivocally demonstrates that the mean risk index values of at least one cluster are statistically distinct from the others at a 95% confidence level for all periods. Post hoc analysis further confirms the statistical significance of differences in mean risk indices between clusters. These findings were further supported by the results obtained from the box plots. Finally, the proposed approach was applied to an underground coal mine to illustrate its practical effectiveness. This study demonstrates that the proposed approach can empower mining companies to comprehensively assess their safety performance and implement necessary measures for improvement.</p>","PeriodicalId":18588,"journal":{"name":"Mining, Metallurgy & Exploration","volume":"77 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141532435","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}