Shahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Performance Evaluation of Zinc Tailing Waste Material for Embankment Construction: Experimental and Numerical Investigation11771191317810.22044/jme.2024.13368.2459ENPankajBhattDepartment of Civil Engineering, Chandigarh University, Mohali, IndiaAnil KumarSinhaCSIR-Central Road Research Institute, New Delhi, IndiaMariyaDayana P JCSIR-Central Road Research Institute, New Delhi, IndiaParvathiGeetha SreekantanCSIR-Central Road Research Institute, New Delhi, IndiaMurtazaHasanDepartment of Civil Engineering, Chandigarh University, Mohali, IndiaJournal Article20230714The rapid development of road networks needs huge construction materials. Mining and industrial wastes can be used as sustainable road construction materials and will be alternatives to fulfill the huge demand in road construction. Zinc tailing is one such mining waste and has the potential for road construction. This material was collected from Zawar mines (Rajasthan), and characterization was carried out for embankment/subgrade applications. A physical model test was conducted in the laboratory to examine the stress-settlement behaviour. To improve the modulus value of tailing, it was reinforced with geogrid in two different laying patterns, viz. layer/loop and stress-settlement behavior was studied. Different parameters were studied: reinforcement depth, layer of reinforcement, number of loops, and depth of loop of reinforcement. The experimental result was validated with the numerical finite element method (SoilWorks). Tailing comprises fine-grained silt-size particles (61%) with no swelling behavior and non-plastic nature. It has values of MDD and OMC as 1.86 g/cm<sup>3</sup> and 11%, respectively. It has a higher value of CBR (12%) and internal friction angle (34.6<sup>o</sup>) with cohesionless nature. The variation of settlement with stress is linear for reinforced and unreinforced tailing fill. As the depth of reinforcement increases, settlement increases in both layer and loop reinforcement. The settlement trajectory obtained from a numerical method closely resembles that of a laboratory physical model, particularly when the applied stress is up to 600 kPa. The modulus of elasticity of tailing was significantly improved with the introduction of geogrid reinforcement either in layer or loop.https://jme.shahroodut.ac.ir/article_3178_d5248f3eabe5653b2d41369101d4c3ad.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Revitalizing Mining Heritage Tourism: A Machine Learning Approach to Tourism Management11931225302910.22044/jme.2024.13770.2554ENAditiNagDepartment of Architecture and Planning, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India0000-0002-0604-6945SmritiMishraDepartment of Architecture and Planning, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, IndiaJournal Article20231030The convergence of Mining Heritage Tourism (MHT) and Artificial Intelligence (AI) presents a transformative paradigm, reshaping heritage preservation, visitor engagement, and sustainable growth. This paper investigates the dynamic synergy between these realms, probing how AI-driven technologies can augment the authenticity, accessibility, and educational significance of mining heritage sites. Focusing on the profound impact of AI on MHT, this study centers its examination on the Barr Conglomerate located in the culturally rich Pali District, India. Employing a mixed-methods approach involving survey data analysis and neural network modelling, the research work explores AI applications that enhance visitor experiences, interpret historical narratives, optimize resource allocation, and mitigate the adverse effects of over-tourism. The study meticulously navigates a vast landscape of AI technologies, spanning machine learning, natural language processing, and augmented reality, show-casing their potential to enrich encounters with mining heritage. While AI promises to revolutionize heritage management, the paper emphasizes the critical importance of ethical considerations and cultural sensitivities. Balancing innovation with preservation, the study advocates for an inclusive approach that honors diverse cultural values and encourages community engagement. Through this exploration, the paper delves into the practical implementation of AI, unveiling best practices lessons learned and illuminating challenges and opportunities. Ultimately, this research work envisions a future where AI empowers mining heritage to transcend temporal boundaries, cultivating immersive experiences resonating with authenticity, global understanding, and sustainable stewardship.https://jme.shahroodut.ac.ir/article_3029_c31325bf580c0f2d34a9f3412ca5149b.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Stability Analysis of Slope of a Pump House Building and Water Storage Tank at Narkanda, India: A case study12271240317610.22044/jme.2024.14159.2634ENSahilKumarDepartment of Civil Engineering, NIT Hamirpur (HP), IndiaRavi KumarSharmaDepartment of Civil Engineering, NIT Hamirpur (HP), IndiaJournal Article20240205Landslides affecting life and property losses has become a serious threat in various countries worldwide which highlights the importance of slope stability and mitigation. The methods and tools employed for slope stability analysis, ranging from traditional limit equilibrium methods to worldly-wise numerical modelling techniques. It focuses on the importance of accurate and reliable data collection, including geotechnical investigations, in developing precise slope stability assessments. Further, it also addresses challenges associated with predicting and mitigating slope failures, particularly in dynamic and complex environments. Mitigation strategies for unstable slopes were systematically reviewed of different researchers, encompassing both traditional and innovative measures. Traditional methods, such as retaining walls and drainage systems, the mitigation strategies were explored, emphasizing both preventive measures and remedial interventions. These include the implementation of engineering solutions such as slope structures, and Matrix Laboratory (MATLAB) techniques along with the comprehensive analysis of four prominent slope stability assessment tools: Rock Mass Rating (RMR), Slope Mass Rating (SMR), and the Limit Equilibrium Method (LEM). The comparative analysis of these tools highlights their respective strengths, limitations, and areas of application, providing researchers, authors, and practitioners with valuable insights to make informed choices based on project-specific requirements. To ensure the safety and sustainability of civil infrastructure, a thorough understanding of geological, geotechnical, and environmental factors in combination with cutting-edge technologies is required. Furthermore, it highlights the important role that slope stability assessment and mitigation play a major role in civil engineering for infrastructure development and mitigation strategies.https://jme.shahroodut.ac.ir/article_3176_9a4cfd2dc0ed01348edcd80a98fdd5d6.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Exploring Ground Behavior in Underground Excavations Under Squeezing Stress Conditions12411254313810.22044/jme.2024.14198.2644ENNaeemAbbasFaculty of Land Resources Engineering, Kunming University of Science and Technology, Yunnan, ChinaLiKegangDepartment of Mining Engineering Karakoram International University (KIU), Gilgit, PakistanJournal Article20240215The study examined the influence of cohesion, friction angle, and tunnel diameter on stability within engineering and geotechnical frameworks, while considering the consequences of nearby excavations on the overall stability assessment. The results show that a higher angle of internal friction leads to a decrease in soil stability number and weighting coefficient. Tunnel diameter significantly affects face support pressure, with larger diameters requiring stronger support due to increased stress. Higher friction angles help stabilize tunnel faces and mitigate diameter-related pressure effects. Stress redistribution around the tunnel is significant within 2 meters from the center, transitioning to elastic behavior elsewhere. A safety factor of 1.3 ensures tensile failure prevention in single and twin tunnels. Balanced stress distribution between tunnels with a slight difference is observed under isotropic in-situ stress. Numerical modeling enhances stress estimations and reveals changes during tunnel excavation, weakening the rock mass. Ground reaction curve analysis with support measures shows reduced tunnel convergence after implementation, suggesting support strategies like extended bolts using updated rock mass rating. The study improves tunnel design and stability assessment by comprehensively understanding stress redistribution and support strategies.https://jme.shahroodut.ac.ir/article_3138_8fb0d440123abd75ed92ced5f5c36e65.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001A Review on Analysis and Mitigation Strategies for Landslide Risk Management: Case studies of Nainital, Satluj Valley, Pipalkoti, Jhakri, Panjpiri in Himalayan Region, India12551270317510.22044/jme.2024.14218.2652ENTanyaThakurCivil Engineering Department, Chandigarh University, Mohali, Punjab, IndiaKanwarpreetSinghCivil Engineering Department, Chandigarh University, Mohali, Punjab, IndiaAbhishekSharmaCivil Engineering Department, Chandigarh University, Mohali, Punjab, IndiaJournal Article20240220Landslides affecting life and property losses has become a serious threat in various countries worldwide which highlights the importance of slope stability and mitigation. The methods and tools employed for slope stability analysis, ranging from traditional limit equilibrium methods to worldly-wise numerical modeling techniques. It focuses on the importance of accurate and reliable data collection, including geotechnical investigations, in developing precise slope stability assessments. Further, it also addresses challenges associated with predicting and mitigating slope failures, particularly in dynamic and complex environments. Mitigation strategies for unstable slopes were systematically reviewed of different researchers, encompassing both traditional and innovative measures. Traditional methods, such as retaining walls and drainage systems, the mitigation strategies were explored, emphasizing both preventive measures and remedial interventions. These include the implementation of engineering solutions such as slope structures, and Matrix Laboratory (MATLAB) techniques along with the comprehensive analysis of four prominent slope stability assessment tools: Rock Mass Rating (RMR), Slope Mass Rating (SMR), and the Limit Equilibrium Method (LEM). The comparative analysis of these tools highlights their respective strengths, limitations, and areas of application, providing researchers, authors, and practitioners with valuable insights to make informed choices based on project-specific requirements. To ensure the safety and sustainability of civil infrastructure, a thorough understanding of geological, geotechnical, and environmental factors in combination with cutting-edge technologies is required. Furthermore, it highlights the important role that slope stability assessment and mitigation play a major role in civil engineering for infrastructure development and mitigation strategies.https://jme.shahroodut.ac.ir/article_3175_bbbaa383727e180b7d816876f86b3920.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Phytotesting as a Tool in Assessing the Effectiveness of Salt Dump Reclamation12711289314910.22044/jme.2024.14331.2679ENAnnaPerevoshchikovaFaculty of Chemical Technologies, Industrial Ecology and Biotechnology, Perm National Research Polytechnic University, Perm, RussiaInstitute of Natural Science, Perm State University, Perm, RussiaLarisaRudakovaFaculty of Chemical Technologies, Industrial Ecology and Biotechnology, Perm National Research Polytechnic University, Perm, RussiaNataliaMitrakovaInstitute of Natural Science, Perm State University, Perm, RussiaElizavetaMalyshkinaFaculty of Biology, Perm State University, Perm, RussiaInstitute of Natural Science, Perm State University, Perm, RussiaNikitaKobelevFaculty of Biology, Perm State University, Perm, RussiaInstitute of Natural Science, Perm State University, Perm, RussiaJournal Article20240318The utilisation of potash reserves has various environmental consequences, such as the generation of substantial volumes of solid waste containing high levels of sodium chloride. The accumulation of environmental harm gives rise to an unfavourable environmental scenario in potash production areas, which requires the investigation of waste management solutions. The predominant approach to reducing surface waste involves backfilling mined areas. In other countries, salt dump reclamation is utilised alongside backfilling. The distinctive characteristic of salt dump reclamation lies in the water-solubility and phytotoxicity of the dump rock. This research aims to evaluate the morphometric and biochemical parameters (using phytotesting) of vegetation throughout the process of salt dump reclamation using different variants. A model reclamation was carried out in a laboratory setting, where three different variants were subjected to experimentation. A reduction in the thickness of the protective clay barrier resulted in a decline in morphometric aspects of the experimental crops as well as the woody vegetation. Reducing the thickness of the protective clay barrier leads to an elevation in the redox activity of the examined crops, thus pointing towards potential environmental toxicity. Superior morphometric and biochemical parameters were noted in vegetation possessing a substantial protective covering, hinting at the feasibility of utilising insulating layers for salt dump reclamation. Phytotesting serves as an indicative approach to assessing soil toxicity and as a parameter for determining soil resilience against pollution. The findings hold potential for application in further research within the field of biological reclamation in areas with dump sites.https://jme.shahroodut.ac.ir/article_3149_86030ec90815d9a0ee29a4d6e50627ad.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Stability Analysis of set-up Room of a Deep Longwall Panel of India using 3D Numerical Modelling Technique12911308315910.22044/jme.2024.14360.2689ENAvula RajashekarYadavMining Engineering Department, Indian Institute of Technology Kharagpur, West Bengal, IndiaSreenivasa RaoIslavathMining Engineering Department, Indian Institute of Technology Kharagpur, West Bengal, IndiaSrikanthKatkuriAdriyala Longwall Project, Singareni Collieries Company Limited, Telangana, IndiaJournal Article20240325The installation gallery/set-up room of a longwall panel is driven for installation of the longwall face machineries to start the extraction of coal from the longwall panel. The width of the installation gallery is 8 to 9 m. This gallery needs to be stabilized till the face machineries to be deployed from the driving of the room as it required to stand more than 8 to 10 months and develop the high stress concentration, roof-to-floor convergence and yield zone in the roof and sides. Hence, in this study, a deep longwall mine of India is considered to analyze the behavior of set-up room. For this, a total of twelve 3D numerical models are developed and analyzed considering Mohr’s-Coulomb failure criterion. Three panels located at 417, 462, 528 m having three different widths (8, 10 and 12 m) of set-up rooms are examined. The width of the set-up room is taken based on the length of the shield support. The results in terms of vertical stress distribution, vertical displacement, roof-to-floor convergence, plastic strain and yield zone distribution are presented.https://jme.shahroodut.ac.ir/article_3159_579a0bc17af939329ee75b24034b490b.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Design of wireless-based Based Sensor for real-time monitoring pH and TDS in Surface and Groundwater using IoT13091320319710.22044/jme.2024.14388.2693ENKushai CalebAluwongSchool of Materials and Mineral Resources Engineering, Universiti Sains Malaysia (USM), Penang, MalaysiaMohd Hazizan BinMohd HashimSchool of Materials and Mineral Resources Engineering, Universiti Sains Malaysia (USM), Penang, MalaysiaSuhainaIshmailSchool of Materials and Mineral Resources Engineering, Universiti Sains Malaysia (USM), Penang, MalaysiaJournal Article20240402In the past, assessing water quality has typically involved labor-intensive and costly processes such as laboratory analysis and manual sampling, which do not provide real-time data. In addition to tasting bad, drinking acidic water on a regular basis can result in acid reflux and recurrent heartburn while high total dissolved solids water can cause kidney stones, especially when the hard water content is more than 500ppm. With growing concerns about water quality, there is a need for continuous monitoring of pH and TDS levels in surface and groundwater sources. To address this, a cutting-edge wireless sensor system leveraging on Internet of Things (IoT) technology has been developed. This system incorporates top-notch pH and TDS sensors known for their accuracy, durability, and environmental compatibility. Integrated with microcontrollers featuring wireless communication capabilities, these sensors enable seamless data transmission to a central server through IoT protocols like cellular networks. The collected data is processed and calibrated to ensure reliability and precision. The IoT platform connected to the central server manages device connectivity, data storage, and analysis, making real-time data accessible via user-friendly web or mobile applications with interactive graphs and dashboards. Power-saving features are implemented to optimize battery life in remote and off-grid locations, and weather-resistant enclosures protect the sensor nodes from harsh environmental conditions. By deploying this wireless-based sensor system, users can gain valuable real-time insights into water quality in surface and groundwater monitoring locations.https://jme.shahroodut.ac.ir/article_3197_2ef2238f16641e42b3729f9566f36eba.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Numerical Analysis and Predictive Modeling Using Artificial Intelligence of the Relaxation Zone Around Hangingwall of Sublevel Open Stopes in Underground Mines13211342319610.22044/jme.2024.14413.2700ENSoufiAmineMohammed V University in Rabat, MorocooZerradiYoussefMohammed V University in Rabat, MorocooSoussiMohamedMohammed V University in Rabat, MorocooOuadifLatifaMohammed V University in Rabat, MorocooBahiAnasMohammed V University in Rabat, MorocooJournal Article20240413The aim of this study is to thoroughly analyze the relaxation zone developing around sublevel stopes in underground mines and identify the main parameters controlling its extent. A numerical approach based on the finite element method, combined with the Hoek-Brown failure criterion, was implemented to simulate various geometric configurations, geological conditions, and in-situ stress states. A total of 425 simulations were carried out by varying depth, horizontal-to-vertical stress ratio (k), rock mass quality (RMR), foliation orientation and spacing, as well as the height, width, and inclination of the sublevels. The results enabled the development of robust predictive models using regression analysis techniques and artificial neural networks (ANNs) to estimate the extent of the relaxation zone as a function of the different input parameters. It was demonstrated that depth and the k ratio significantly influence the extent of the relaxation zone. Additionally, a decrease in rock mass quality leads to a substantial increase in this zone. Structural characteristics, such as foliation orientation and spacing, also play a decisive role. Finally, the geometric parameters of the excavations, notably the height, width, and inclination of the sublevels, directly impact stress redistribution and the extent of the relaxation zone. The overall ANN model, taking into account all these key parameters, exhibited high accuracy with a correlation coefficient of 0.97. These predictive models offer valuable tools for optimizing the design of underground mining operations, improving operational safety, and increasing productivity.https://jme.shahroodut.ac.ir/article_3196_2c504ceba453950741f0a463d288d0c8.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Predicting Open Pit Mine Production using Machine Learning Techniques: A Case Study in Peru13451355315710.22044/jme.2024.14416.2703ENMarco AntonioCotrina TeatinoDepartment of Mining Engineering, Faculty of Engineering, National University of Trujillo, Trujillo, PeruJairo JhonatanMarquina AraujoDepartment of Mining Engineering, Faculty of Engineering, National University of Trujillo, Trujillo, PeruEduardo ManuelNoriega VidalDepartment of Mining Engineering, Faculty of Engineering, National University of Trujillo, Trujillo, PeruJose NestorMamani QuispeDepartment of Mining Engineering, University of Chile, Santiago, ChileJohnny HenrryCcatamayo BarriosDepartment of Mining Engineering, National University of San Cristóbal de Huamanga, Ayacucho, PeruJoe AlexisGonzalez VasquezDepartment of Industrial Engineering, National University of Trujillo, Trujillo, PeruSolio MarinoArango RetamozoDepartment of Industrial Engineering, National University of Trujillo, Trujillo, Peru0000-0003-3594-0329Journal Article20240413The primary objective of this research was to apply machine learning techniques to predict the production of an open pit mine in Peru. Four advanced techniques were employed: Random Forest (RF), Extreme Gradient Boosting (XGBoost), K-Nearest Neighbors (KNN), and Bayesian Regression (RB). The methodology included the collection of 90 datasets over a three-month period, encompassing variables such as operational delays, operating hours, equipment utilization, the number of dump trucks used, and daily production. The data were allocated 70% for training and 30% for testing. The models were evaluated using metrics such as Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Variance Accounted For (VAF), and the Coefficient of Determination (R<sup>2</sup>). The results indicated that the Bayesian Regression model was the most effective in predicting production in the open pit mine. The RMSE, MAPE, VAF, and R<sup>2</sup> for the models were 3686.60, 3581.82, 4576.61, and 3352.87; 12.65, 11.09, 15.31, and 11.90; 36.82, 40.72, 1.85, and 47.32; 0.37, 0.41, 0.41, and 0.47 for RF, XGBoost, KNN, and RB, respectively. This research highlights the efficacy of machine learning techniques in predicting mine production and recommends adjusting each model's parameters to further enhance outcomes, significantly contributing to strategic and operational management in the mining industry.https://jme.shahroodut.ac.ir/article_3157_23d8329aa120ef78d705535d3ff9692f.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Evaluation of Band Ratio Technique for Prediction of Iron-Titanium Mineralization Using Ensemble Machine Learning Model: A Case Study from Khamal area, Western Saudi Arabia13571371318610.22044/jme.2024.14451.2711ENAhmed AliMadaniDepartment of Geology, Faculty of Science, Cairo University, Giza, EgyptJournal Article20240424Innovation in mineral exploration occurs either in the construction of new ore deposit models or the development of new techniques used to locate the ore deposits. Band ratio is the image processing technique developed for mineral exploration. The present study presents a new approach used to evaluate the band ratio technique for discrimination and prediction of the Iron-Titanium mineralization exposed in the Khamal area, Western Saudi Arabia using the ensemble Random Forest model (RF) and SPOT-5 satellite data. SPOT-5 band ratio images are prepared and used as the explanatory variables. The target variable is prepared in which (70%) of the target locations are used for training and the rest are for validation. A confusion matrix and the precision-recall curves are constructed to evaluate the RF model performance and the Receiver Operating Characteristics curves (ROC) are used to rank the band ratio images. Results revealed that the 3/1, 2/1 & 3/2 band ratio images show excellent discrimination with AUC values of 0.986, 0.980 & 0.919 respectively. The present study successfully selects the 3/1 band ratio image as the best classifier and presents a new Fe-Ti mineralization image map. The present study proved the usefulness of the Random Forest classifier for the prediction of the Fe-Ti mineralization with an accuracy of 97%.https://jme.shahroodut.ac.ir/article_3186_edf290aecd36bb80dfd9a39e5a3f6f76.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Dynamic Pit Tracker: An Iterative Heuristic Algorithm Tracing Optimized Solution for Ultimate Pit Limit and Blocks Sequencing Problem13731394318210.22044/jme.2024.12944.2349ENMeisamSalekiSchool of Materials and Minerals Resources Engineering, Universiti Sains Malaysia (USM), MalaysiaRezaKhaloo KakaieFaculty of Mining, Petroleum & Geophysics Eng., Shahrood University of Technology, Shahrood, IranMohammadAtaeiFaculty of Mining, Petroleum & Geophysics Eng., Shahrood University of Technology, Shahrood, IranAliNouri QarahasanlouFaculty of Science and Technology, UiT, The Arctic University of Norway, Tromsø, NorwayJournal Article20230412One of the most critical designs in open-pit mining is the ultimate pit limit (UPL). The UPL is frequently computed initially through profit-maximizing algorithms like the Lerchs-Grossman (LG). Then, in order to optimize net present value (NPV), production planning is executed for the blocks that fall within the designated pit limit. This paper presents a mathematical model of the UPL with NPV maximization, enabling simultaneous determination of the UPL and long-term production planning. Model behavior is nonlinear. Thus, in order to achieve model linearization, the model has been partitioned into two linear sub-problems. The procedure facilitates the model solution and the strategy by decreasing the number of decision variables. Naturally, the model is NP-Hard. As a result, in order to address the issue, the Dynamic Pit Tracker (DPT) heuristic algorithm was devised, accepting economic block models as input. A comparison is made between the economic values and positional weights of blocks throughout the steps in order to identify the most appropriate block. The outcomes of the mathematical model, LG, and Latorre-Golosinski (LAGO) algorithms were assessed in relation to the DPT on a two-dimensional block model. Comparative analysis revealed that the UPLs generated by these algorithms are consistent in this instance. Utilizing the new algorithm to determine UPL for a 3D block model revealed that the final pit profit matched LG UPL by 97.95%.https://jme.shahroodut.ac.ir/article_3182_f58a43183a14d49a3713b3704fa0934d.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001A Generalized Mathematical Model for Integrated Production Planning in Drift-and-Fill Mining Operation13951408315810.22044/jme.2024.13578.2510ENMehdiRahmanpourSchool of Mining, College of Engineering University of Tehran, Tehran, IranGolpariNoroziSchool of Mining, College of Engineering University of Tehran, Tehran, IranHassanBakhshandeh AmniehSchool of Mining, College of Engineering University of Tehran, Tehran, IranJournal Article20230908Drift-and-fill mining is a variation of cut-and-fill mining method. Drift-and-fill mining method refers to the excavation of several parallel drifts in ore. Excavation of a new drift could start when its adjacent drifts are backfilled or not excavated. The amount of ore material and its grade depends on the excavation sequence of drifts. As the number of drifts increases, one will need a model to optimize the drift excavation and backfilling sequence. This paper introduces a mathematical model to determine the optimal drift-and-fill sequence while the safety constraints, excavation, and backfilling capacities and their dependencies are satisfied. The model seeks to minimize the deviations from some predefined goals, and it handles the long-term and short-term constraints in separate and integrated scenarios. An application of the model is presented based on the data available from a lead/zinc underground mining project. There are 91 drifts in the selected level. Based on the monthly planning horizon, the integrated model leads to the slightest deviations in both the mining rate and average grade, and the deviation from the predetermined annual goals is negligible. For the case where long-term and short-term plans are determined separately, the deviation is approximately 10%.https://jme.shahroodut.ac.ir/article_3158_d67a579a7f3660c09bb1d09eb0fdecf5.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Developing GEP tree-based, Neuro-Swarm, and whale Optimization Models for evaluating Groundwater Seepage into Tunnels: A Case Study14091436313910.22044/jme.2024.13601.2513ENShirinJahanmiriDepartment of Mining Engineering, University of Kashan, Kashan, IranAliAalianvariDepartment of Mining Engineering, University of Kashan, Kashan, Iran0000-0002-9487-1522MaliheheAbbaszadehDepartment of Mining Engineering, University of Kashan, Kashan, IranJournal Article20230913Groundwater inflow is a critical subject within the domains of hydrology, hydraulic engineering, hydrogeology, rock engineering, and related disciplines. Tunnels excavated below the groundwater table, in particular, face the inherent risk of groundwater seepage during both the excavation process and subsequent operational phases. Groundwater inflows, often perceived as rare geological hazards, can induce instability in the surrounding rock formations, leading to severe consequences such as injuries, fatalities, and substantial financial expenditures. The primary objective of this research is to explore the application of machine learning techniques to identify the most accurate method of forecasting tunnel water seepage. The prediction of water loss into the tunnel during the forecasting phase employed a tree equation based on gene expression programming (GEP). These results were compared with those obtained from a hybrid model comprising particle swarm optimization (PSO) and artificial neural networks (ANN). The Whale Optimization Algorithm (WOA) was selected and developed during the optimization phase. Upon contrasting the aforementioned methods, the Whale Optimization Algorithm demonstrated superior performance, precisely forecasting the volume of water lost into the tunnel with a correlation coefficient of 0.99. This underscores the effectiveness of advanced optimization techniques in enhancing the accuracy of groundwater inflow predictions and mitigating potential risks associated with tunneling activities.https://jme.shahroodut.ac.ir/article_3139_d9d72b91a7b915365631fbbbaf54da7a.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Flotation of Oxidized Antimony ore of Sefidabeh Mine14371459318310.22044/jme.2024.13694.2541ENAlirezaJavadiDepartment of Engineering, University of Kashan, Kashan, IranJournal Article20231015The main and economic mineral of antimony is stibnite or antimony sulfide, and the research and processes in the world are based on it, and oxide minerals are not considered among the economic and important reserves of antimony due to the difficulty of processing and the lack of optimal efficiency of the flotation method. On the other hand, taking into account that a large part of the antimony reserve of Sefidabeh is made up of low-grade oxidized ore; this research on the method of economic extraction and the possibility of recovering this type of reserve will be important due to the strategic nature of antimony metal. According to the experiments conducted in this research, the effective parameters for flotation include: pH, collector concentration, activator concentration, depressant concentration, activator type, and humic acid concentration. DX7 software was used for statistical modeling of experiments. Based on the above parameters, the design of the experiment was carried out using a partial factorial method and finally the number of 16 experiments was determined for the effect of the above factors on the grade and weight recovery of the sample. Antimony ore flotation with a grade of 4.32% was carried out in a two-stage method. In this method, in the first stage, flotation of antimony sulfur (stibnite, Sb<sub>2</sub>S<sub>3</sub>) was performed at a specific pH by adding the activator of copper sulfate or lead nitrate and the depressant together, potassium amyl xanthate collector and MIBC. In the second stage of flotation, the tailings of the first stage of flotation for antimony oxides were treated with a sodium oleate collector (with determined concentrations) at a specific pH by adding copper sulfate or lead nitrate activator, sodium oleate collector and humic acid and MIBC frother agent. The interaction between pH and activator concentration (BD) has a direct effect on the amount of concentrated antimony, with an increase in pH from 6 to 8 antimony when using an activator concentration of 300 g/t, and a decrease when using an activator concentration of 500 g/t. Flotation was done. In the best conditions, with two-stage flotation of antimony, 68.99% recovery and 13.32 grade were obtained.https://jme.shahroodut.ac.ir/article_3183_d51548e5b79c2b5eb0f03f2afe6c7964.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001A New Method for Stability Analysis of Chain Pillar in Longwall Mining by using Coulmann Graphical Method14611476313610.22044/jme.2024.13754.2548ENMohammad SinaAbdollahiDepartment of Mining and Metallurgical Engineering, Yazd University, Yazd, IranMehdiNajafiDepartment of Mining and Metallurgical Engineering, Yazd University, Yazd, IranAlirezaYarahamdi BafghiDepartment of Mining and Metallurgical Engineering, Yazd University, Yazd, IranRaminRafieeDepartment of Mining, Petroleum & Geophysics Engineering, Shahrood University of Technology, Shahrood, IranJournal Article20231026The stability analysis of chain pillars is crucial, especially as coal extraction rates increase, making it essential to reduce the size of these pillars. Therefore, a new method for estimating the load on chain pillars holds significant importance. This research introduces a novel solution for estimating side abutment load and analyzing the stability of chain pillars using the dynamic mode of the Coulmann Graphical (CG) method. The solution is implemented using Visual Studio software and is named Coulmann Chain Pillar Stability Analysis (CCPSA). The CG method is widely recognized in civil engineering as a highly efficient technique for determining soil side abutment pressure in both static and dynamic conditions. This method involves calculating the top-rupture wedge of chain pillars using the CG method. The CCPSA software functions share significant similarities with those of the Analysis Longwall Pillar Stability (ALPS) method. However, the main point of departure between the proposed method and the ALPS empirical method lies in their respective approaches to calculating side abutment load on chain pillars and evaluating subsidence conditions. The effectiveness of this method has been validated using a database of chain pillars from various mines worldwide and has been compared with the ALPS method. The results of the comparison demonstrate that the CCPSA is highly effective in evaluating chain pillar stability. This underscores the potential of the CG method and CCPSA software in providing valuable insights for assessing and ensuring the stability of chain pillars in mining operations.https://jme.shahroodut.ac.ir/article_3136_0b329e2385eaa08e4ac25f8fad58aca7.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Mineral Prospectivity Modeling with Airborne Geophysics and Geochemistry Data: a Case Study of Shahr-e-Babak Studied Area, Southern Iran14771489307110.22044/jme.2024.13857.2575ENMoslemJahantighDepartment of Mining Engineering, Faculty of Mine, AmirKabir University, Tehran, IranHamid RezaRamaziDepartment of Mining Engineering, Faculty of Mine, AmirKabir University, Tehran, IranJournal Article20231118The present paper gives out data-driven method with airborne magnetic data, airborne radiometric data, and geochemistry data. The purpose of this study is to create a mineral potential model of the Shahr-e-Babak studied area. The studied area is located in the south-eastern of Iran. The various evidential layers include airborne magnetic data, airborne radiometric data (potassium and thorium), lineament density map, cu geochemistry signature, and multi-variate geochemistry signature (PC1). High magnetic anomalies, lineament structures, and alteration zones (K/Th) were derived from airborne geophysics data. Geochemistry signatures (Cu and PC1) were derived from stream sediment data. The principal Component Analysis (PCA) as an unsupervised machine learning method and five evidential layers were used to produce a porphyry prospectivity model. As a result of this combination, mineral prospectivity model was produced. Then a plot of cumulative percent of the studied area versus pca prospectivity value was used to discrete high potential areas. Then to evaluate the ability of this MPM, the location of known cu indications was used. The results confirm an acceptable outcome for porphyry prospectivity modeling. Based on this model high-potential areas are located in south southwestern and eastern parts of the studied area.https://jme.shahroodut.ac.ir/article_3071_0b4a73fc8a39ec0d26b0a1d0f766a7f5.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Optimizing Long-Term Production Scheduling in Open Pit Mining under Commodity Price Uncertainty: A Two-Stage Stochastic Programming Approach14911508317710.22044/jme.2024.13814.2576ENElhamLotfiDepartment of Mining and Metallurgical Engineering, Yazd University, Yazd, IranJavadGholamnejadDepartment of Mining and Metallurgical Engineering, Yazd University, Yazd, Iran0000-0003-3480-9644MehdiNajafiDepartment of Mining and Metallurgical Engineering, Yazd University, Yazd, IranMohammad SadeghZamaniDepartment. of Mathematical Sciences, Yazd University, Yazd, IranJournal Article20231118In the context of open pit mining operations, long-term production scheduling faces significant challenges due to inherent uncertainties, particularly in commodity prices. Traditional mathematical models often adopt a single-point estimation strategy for commodity price, leading to suboptimal mine plans and missed production targets. The simultaneous effect of commodity price uncertainty on the cut-off grade and long-term production scheduling is less considered. This paper introduces a novel model for optimizing open pit mine long-term production scheduling under commodity price uncertainty considering a dynamic cut-off grade strategy, based on a two-stage Stochastic Production Programming (SPP) framework. The presented model seeks to identify optimal mining block sequences, maximizing total discounted cash flow while penalizing deviations from production targets. To illustrate the model's efficiency, it was implemented in a copper mine. First, the Geometric Brownian Motion (GBM) model is used to quantify the future commodity price. Then, both deterministic and SPP models were solved using GAMS software. The results showed that the practical NPV obtained from the SPP model is approximately 3% higher than the DPP model, while all constraints are satisfied.https://jme.shahroodut.ac.ir/article_3177_13d20aeaf6453f5f3bbe0f678abdf085.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Discrete Elements Analysis of Sand Production Mechanism in Oil Well Considering Effects of in-situ Stress and Fluid Pressure15091525303710.22044/jme.2024.13894.2585ENMasoudYazdaniDepartment of Mining and Metallurgical Engineering, Yazd University, Yazd, IranMohammadFatehi MarjiDepartment of Mining and Metallurgical Engineering, Yazd University, Yazd, IranHamidSoltanianDrilling & Well Completion Technologies & Research Group, Research Institution of Petroleum Industry, Tehran, IranMehdiNajafiDepartment of Mining and Metallurgical Engineering, Yazd University, Yazd, IranManouchehrSaneiDepartment of Mining and Metallurgical Engineering, Yazd University, Yazd, IranJournal Article20231127Approximately 70% of the world's hydrocarbon fields are located in reservoirs with low-strength rocks such as sandstone. During the production of hydrocarbons from sandstone reservoirs, sand-sized particles may become dislodged from the formation, and enter the hydrocarbon fluid flow. Sand production is a significant issue in the oil industry due to its potential to cause erosion of pipes and valves. Separating grains from oil is a costly process. Therefore, oil and gas-producing companies are motivated to reduce sand production during petroleum extraction. Various methods exist for predicting this phenomenon including continuous, discontinuous, experimental, physical, analytical, and numerical methods. Given the significance of the subject, this research work aims to achieve two primary objectives. Firstly, it proposes a two-dimensional numerical model based on the discrete element method to address the issues of high strain and deformation in granular materials. This method is highly reliable in simulating the mechanism of sand production in oil wells. Secondly, the production of sand is influenced by two factors: fluid pressure and stress; to evaluate changes in production from a particular reservoir, it is necessary to analyze each parameter. Two sandstone samples, similar to reservoir rock conditions, were prepared and tested in the laboratory to demonstrate sand production phenomenon. The numerical results have been verified and compared to their experimental counterparts.https://jme.shahroodut.ac.ir/article_3037_8479d095c3d202ff0467085ec2c40f51.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Performance Evaluation of a Haul Truck Allocation Model in Sungun Copper Mine15271537313710.22044/jme.2024.13932.2597ENHosseinMirzaei Nasir AbadFaculty of Mining Engineering., Sahand University of Technology, Tabriz, IranMehrnazMohtashamFaculty of Mining Engineering., Sahand University of Technology, Tabriz, IranFarshadRahimzadeh-NanekaranFaculty of Mining Engineering., Sahand University of Technology, Tabriz, IranJournal Article20231205Transportation of materials is the most cost-intensive component in open-pit mining operations. The aim of the allocation models is to manage and optimize transportation activities, leading to reduced wasted time, and ultimately, increasing profitability while reducing operational costs. Given that the implementation of allocation models is one of the essential requirements in Iranian mining operations, this research work focuses on the transportation system in the Sungun copper mine, one of the largest mines in Iran, and highlights the challenges faced by the fixed allocation approach. The aim is to develop and implement a mathematical model to evaluate its performance, and suggest improvements. The allocation model attempts to optimize truck capacity utilization and maximize mining production. Implementing the model in the mine results in a 13.42% increase in total production compared to the conventional method, with a cost increase of 14.7%. The model shows the potential to meet operational and technical constraints to achieve optimal production. Overall, the developed model, with optimized management and improved fleet efficiency, outperforms the traditional haulage method in the mine.https://jme.shahroodut.ac.ir/article_3137_70f8ca5c5a6cc255e2080c4a27203fce.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Determination of the Caving Zone Height using Numerical and Physical Modeling based on the Undercutting Method, Joint Dip, and Spacing15391562314010.22044/jme.2024.13984.2609ENBehnamAlipenhaniSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.MehranJalilianSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.AbbasMajdiSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.HassanBakhshandeh AmniehSchool of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran.Mohammad HosseinKhosraviDepartment of Mining Engineering, Faculty of Engineering, University of Birjand, Birjand, IranJournal Article20231221The paper presents the effect of the dip of joints, joint spacing, and the undercutting method on the height of the caving in block caving. The obtained results show that among the three investigated parameters, respectively, the dip of joints, undercutting method, and joint spacing have the greatest effect on increasing the height of the caving zone. Comparing the data obtained from physical and numerical modeling shows a 97% match. Also, by increasing the joint spacing from 4 to 6 cm, 14%, from 6 to 8 cm, about 35%, and from 8 to 10, about 50%, the height of the caving zone has decreased. Regarding the dip of the joint, with the dip increasing from 30 to 45 degrees, about 3% of the caving height decreases. By increasing the dip of the joint from 45 to 60 degrees, the caving height has decreased by 42%. By increasing this value from 60 to 75 degrees, the caving height has increased by 50%. Also, changing the undercutting method from symmetric to advanced undercutting has increased the caving height by 40%. Additionally, three mathematical models have been proposed based on the shape of the caving zone in physical modeling.https://jme.shahroodut.ac.ir/article_3140_8fecdc6b19844118013933b219a9ff6c.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Application of Fractal Modeling for Accurate Resources Estimation in the Qarah Tappeh Copper Deposit, NW Iran15631577315210.22044/jme.2024.14071.2622ENSepidehGhasemiDepartment of Mining Engineering, Faculty of Engineering, Urmia University, Urmia, IranAliImamalipurDepartment of Mining Engineering, Faculty of Engineering, Urmia University, Urmia, IranSamanehBarakDepartment of Mining Engineering, Faculty of Engineering, Urmia University, Urmia, IranJournal Article20240116This investigation centers on the Qarah Tappeh copper deposit, situated in the northern region of West Azerbaijan province, approximately 15 kilometers northeast of Maku city. The primary objective of the study is to comprehensively examine the study area through the analysis of 253 lithogeochemical samples, and assessing reserves utilizing ordinary kriging, guided by subsurface data obtained from 14 boreholes totaling 909.2 meters. The concentration–volume (C–V) multifractal modeling approach was employed to estimate the deposit's reserve. The findings of this research project indicate an estimated 988,604 tons of the deposit with an average grade of 0.14%. Through the analysis of log–log plots within the C–V relationship, threshold values signifying various copper (Cu) concentrations were identified. These plots revealed a pronounced power-law correlation between Cu concentrations and their corresponding volumes, with arrows denoting four specific threshold values. Utilizing this analytical methodology, mineralized zones were classified into five distinct categories: high (>0.42%), above-average (0.35-0.42%), average (0.27-0.35%), below-average (0.14-0.27%), and low (<0.14%) mineralized zones.https://jme.shahroodut.ac.ir/article_3152_7983abaa6fbde05e261645c0d428e4fd.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Application of Hybrid Wavelet-Fractal Approach for Denoising and Spatial Modeling of Environmental Pollution15791590317410.22044/jme.2024.14197.2643ENHosseinMahdiyanfarDepartment of Mining Engineering, University of Gonabad, Gonabad, IranMirmahdiSeyedrahimi-NiaraqDepartment of Mining Engineering, Faculty of Engineering, University of Mohaghegh Ardabili, Ardabil, IranJournal Article20240215In this investigation, the hybrid approach of wavelet transforms and fractal method named Wavelet-Fractal model has been utilized for geochemical contamination mapping as a novel application. For this purpose, the distribution maps of pollutant elements were transformed to the position-scale domain using two-dimensional discrete wavelet transformation (2DDWT). The Symlet2 and Haar mother wavelets were applied for two-dimensional signal analysis of elemental concentrations of As, Pb, and Zn based on soil samples taken from the Irankuh mining district, Central Iran. The Symlet2 and Haar wavelet coefficients of approximate and detail components were obtained at one level frequency decomposition using 2DDWT. The wavelet coefficients of approximate component (WCAC) were modeled using a fractal method for delineating the geochemical contamination populations of toxic elements. Based on the results of wavelet-fractal models, the As, pb, and Zn were classified into three and four populations. Two areas contaminated with metals have been found in the district. These areas are within the limit of mining operations and its surroundings. The wavelet-fractal proposed model has been able to separate environmental areas contaminated with toxic metals accurately. Anomalously intense pollution has spread to one kilometer outside the mining operation limit. This dispersion in the case of Pb and Zn elements is well seen in the geochemical map prepared with the Haar class.https://jme.shahroodut.ac.ir/article_3174_5b0ab7f735aa72be1029f60ea5107666.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001Environmental Friendly Approach: Atmospheric and High-Pressure Acid Leaching Studies, Low-Grade Laterites Nickel Processing15911606319810.22044/jme.2024.14230.2656ENAhmadAbbasi GharaeiDepartment of Mining Engineering, Science and Research Branch of Islamic Azad University, Tehran, IranBahramRezaiDepartment of Mining Engineering, Amirkabir University of Technology, Tehran, Iran.HadiHamidian ShormastiDepartment of Mining Engineering, Qaem Shahr Branch Islamic Azad University, Qaem Shahr, IranJournal Article20240223This paper examines the performance of Atmospheric Leaching (AL) and High-Pressure Acid Leaching (HPAL) on nickel laterite, classified as limonite. The study, conducted on a laboratory scale, involved temperatures of 35-95°C for AL and 220-250°C for HPAL. Nickel and cobalt contents were found to be 0.7% and 0.04%, respectively. AL achieved an 89% yield of Al with a pH of 0.2 and a 14-hour leaching time, while nickel and iron recoveries reached 92% and 87% after 20 hours, with an acid consumption of 1.2 kg H<sub>2</sub>SO<sub>4</sub> per 100 kg laterite (dry) at pH 0.2. Leaching experiments at 220-250°C for 2 hours showed similar nickel recovery rates, indicating no improvement beyond 240°C. Hematite, a stable compound associated with nickel, hindered its release during HPAL due to its resistance to leaching. Nickel yields remained around 90% in both AL and HPAL tests. Iron behavior differed significantly between the two methods, with HPAL dissolving iron initially but transforming it into hematite in situ, leading to lower net acid consumption compared to AL. The leaching mechanism for iron oxides followed empirical power law kinetics of order 1.5 with activation energies of 36.23 and 25.09 kJ/mol for Ni and Fe, respectively.https://jme.shahroodut.ac.ir/article_3198_fbbc30baa6d6d11412ca0fa3aef80f40.pdfShahrood University of TechnologyJournal of Mining and Environment2251-859215420241001The Effect of Soil and Grout Mixture on the Ground Surface Settlement in Mechanized Excavation16071626314110.22044/jme.2024.14136.2666ENFaezehBarriDepartment of Mining Engineering, Sahand University of Technology, Tabriz, IranHamidChakeriDepartment of Mining Engineering, Sahand University of Technology, Tabriz, IranMohammadDarborDepartment of Mining Engineering, Sahand University of Technology, Tabriz, Iran0000-0001-7854-9077HamedHaghkishDepartment of Construction Management, Islamic Azad University, Tabriz, IranJournal Article20240304Excavation with Tunnel Boring Machine (TBM) in urban environments can have risks, such as ground surface settlement. The empty space between the cutterhead and the segment should be filled with suitable grout during the excavation. Nowadays, using grout behind the segment and other fillers fill the empty space behind the segment and reduce the amount of ground surface settlement. Undoubtedly, using a grout with appropriate mechanical behavior can be a suitable substitute for excavated soil in mechanized tunneling. In this research, the mechanical behavior of the grout behind the segment during injection into the space between the soil and the segment and its mixture with the soil is studied. Also, the effect of mechanical properties of grout mixed with soil on the ground surface settlement is investigated using numerical modeling. The components of two-component grout of this study comprises Sufian type 2 cement with 28-day strength of 44 MPa and density of 3050 kg/m<sup>3</sup>, Salafchegan bentonite with density of 2132 kg/m<sup>3 </sup>and precipitator of liquid sodium silicate with density of the solution 1500 kg/m<sup>3</sup>. The results of the laboratory studies indicated that mixing the grout and soil increases the mechanical properties of grout significantly. Increasing the soil in the mixture of soil and grout up to 40% increases the uniaxial compressive strength up to 300%, the elasticity of modulus up to 156% and the cohesion of the mixture up to 100%. On the other hand, based on the results of numerical modeling, the proper injection pressure can significantly reduce the ground surface settlement. Increasing the injection pressure from 0 to 120 kPa has a 17% influence on the reduction of ground surface settlement.https://jme.shahroodut.ac.ir/article_3141_b2bba49ea577e30404ef4b2337dee2f8.pdf