Pub Date : 2017-06-01DOI: 10.22059/IJMGE.2016.218204.594633
M. Khosravi, Hassan Sarfaraz, Mahmoud Esmailvandi, T. Pipatpongsa
One of the important parameters in undercut slopes design is the determination of the maximum stable undercut span. The maximum stable undercut span is a function of slope geometry, the strength parameters of the slope material, condition of discontinuities, underground water condition, etc. However, the desired production capacity and therefore the size of excavating equipment will sometimes ask for a wider undercut span. The influence of arching phenomenon in geo-material on the stability of undercut slopes is investigated earlier. It is believed that due to arching effect, some load transfer from the undercut area into stationary remaining side toes leads to a more stable slope. However, the transferred load may result in ploughing failure of side toes. One technique for preventing the ploughing failure is the use of counterweight balance on side toes. In this study, the influence of counterweight size on the stability of the undercut slopes was investigated through a series of numerical model tests using FLAC3D software. It was concluded that there is a meaningful relationship between the counterweight balance size and the maximum stable undercut span where increasing a counterweight size results in a wider stable span. Finally, the numerical results were compared with pre-conducted physical modeling test and a nonlinear relationship was proposed between the counterweight size and the maximum stable undercut span.
{"title":"A Numerical Analysis on the Performance of Counterweight Balance on the Stability of Undercut Slopes","authors":"M. Khosravi, Hassan Sarfaraz, Mahmoud Esmailvandi, T. Pipatpongsa","doi":"10.22059/IJMGE.2016.218204.594633","DOIUrl":"https://doi.org/10.22059/IJMGE.2016.218204.594633","url":null,"abstract":"One of the important parameters in undercut slopes design is the determination of the maximum stable undercut span. The maximum stable undercut span is a function of slope geometry, the strength parameters of the slope material, condition of discontinuities, underground water condition, etc. However, the desired production capacity and therefore the size of excavating equipment will sometimes ask for a wider undercut span. The influence of arching phenomenon in geo-material on the stability of undercut slopes is investigated earlier. It is believed that due to arching effect, some load transfer from the undercut area into stationary remaining side toes leads to a more stable slope. However, the transferred load may result in ploughing failure of side toes. One technique for preventing the ploughing failure is the use of counterweight balance on side toes. In this study, the influence of counterweight size on the stability of the undercut slopes was investigated through a series of numerical model tests using FLAC3D software. It was concluded that there is a meaningful relationship between the counterweight balance size and the maximum stable undercut span where increasing a counterweight size results in a wider stable span. Finally, the numerical results were compared with pre-conducted physical modeling test and a nonlinear relationship was proposed between the counterweight size and the maximum stable undercut span.","PeriodicalId":36564,"journal":{"name":"International Journal of Mining and Geo-Engineering","volume":"37 1","pages":"63-69"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82027258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.22059/IJMGE.2017.62147
M. Rezaei, M. Hossaini, A. Majdi, Iraj Najmoddini
The paper describes an artificial neural network (ANN) model to predict the height of destressed zone (HDZ) which is taken as equivalent to the combined height of caved and fractured zones above the mined panel in longwall mining. For this, the suitable datasets have been collected from the literatures and prepared for modeling. The data were used to construct a multilayer perceptron (MLP) network to approximate the unknown nonlinear relationship between the input parameters and HDZ. The MLP proposed model predicted values in enough agreements with the measured ones in a satisfactory correlation, in which, a high conformity (R2=0.989) was observed. To approve the capability of proposed ANN model, the obtained results are compared to the results of the conventional regression analysis (CRA) method. The calculated performance evaluation indices show the higher level of accuracy of the proposed ANN model compared to CRA. For further evaluation, the ANN model results are compared with the results of available models and in-situ measurements reported in literatures. Comparative results present a logical agreement between ANN model and available methods. Obtained results remark that the proposed ANN model is a suitable tool in HDZ estimation. At the end of modeling, the parametric study shows that the most effective parameter is unit weight whereas elastic modulus is the least effective parameter on the HDZ in this study.
{"title":"Determination of the height of destressed zone above the mined panel: An ANN model","authors":"M. Rezaei, M. Hossaini, A. Majdi, Iraj Najmoddini","doi":"10.22059/IJMGE.2017.62147","DOIUrl":"https://doi.org/10.22059/IJMGE.2017.62147","url":null,"abstract":"The paper describes an artificial neural network (ANN) model to predict the height of destressed zone (HDZ) which is taken as equivalent to the combined height of caved and fractured zones above the mined panel in longwall mining. For this, the suitable datasets have been collected from the literatures and prepared for modeling. The data were used to construct a multilayer perceptron (MLP) network to approximate the unknown nonlinear relationship between the input parameters and HDZ. The MLP proposed model predicted values in enough agreements with the measured ones in a satisfactory correlation, in which, a high conformity (R2=0.989) was observed. To approve the capability of proposed ANN model, the obtained results are compared to the results of the conventional regression analysis (CRA) method. The calculated performance evaluation indices show the higher level of accuracy of the proposed ANN model compared to CRA. For further evaluation, the ANN model results are compared with the results of available models and in-situ measurements reported in literatures. Comparative results present a logical agreement between ANN model and available methods. Obtained results remark that the proposed ANN model is a suitable tool in HDZ estimation. At the end of modeling, the parametric study shows that the most effective parameter is unit weight whereas elastic modulus is the least effective parameter on the HDZ in this study.","PeriodicalId":36564,"journal":{"name":"International Journal of Mining and Geo-Engineering","volume":"191 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88473718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.22059/IJMGE.2017.218671.594635
S. Salehi, M. Noaparast, S. Z. Shafaie
In this work, we present as investigation of chalcopyrite leaching under different leach conditions for how liquidation and surface of chalcopyrite study using Scanning Electron Microscopy (SEM) to determine the composition of the passivation layer in the surface of chalcopyrite. The study of chalcopyrite dissolution were in H2SO4 solution systems at pH of 1.2, with 5% chalcopyrite concentrate in redox potential of 460 mV at 90°C. The tests were directed to study on the leaching of chalcopyrite in ferric sulfate solution to extract copper with adding pyrite, silver and silver coated pyrite. In these approaches, achieved recoveries were different. The results showed that, in the present of pyrite, the presence of the elemental sulfur layer formed around the chalcopyrite particles which hindered the complete dissolution of copper in chalcopyrite. Also, in the presence of silver, no commercial process has been developed which successfully as a catalyst to recover copper from chalcopyrite. Because, the precipitation of argentojarosite, which forms during the leaching process, limits the availability of silver ion in solution which may act as a catalyst. But syndicate of silver and pyrite to form of silver coated pyrite, causes dissolution increase. However, in the presence of the pyrite coated by silver, leaching was very rapid for the duration of the test, and complete copper extraction was achieved within 10 hours.
{"title":"The role of catalyst in the passivation of chalcopyrite during leaching","authors":"S. Salehi, M. Noaparast, S. Z. Shafaie","doi":"10.22059/IJMGE.2017.218671.594635","DOIUrl":"https://doi.org/10.22059/IJMGE.2017.218671.594635","url":null,"abstract":"In this work, we present as investigation of chalcopyrite leaching under different leach conditions for how liquidation and surface of chalcopyrite study using Scanning Electron Microscopy (SEM) to determine the composition of the passivation layer in the surface of chalcopyrite. The study of chalcopyrite dissolution were in H2SO4 solution systems at pH of 1.2, with 5% chalcopyrite concentrate in redox potential of 460 mV at 90°C. The tests were directed to study on the leaching of chalcopyrite in ferric sulfate solution to extract copper with adding pyrite, silver and silver coated pyrite. In these approaches, achieved recoveries were different. The results showed that, in the present of pyrite, the presence of the elemental sulfur layer formed around the chalcopyrite particles which hindered the complete dissolution of copper in chalcopyrite. Also, in the presence of silver, no commercial process has been developed which successfully as a catalyst to recover copper from chalcopyrite. Because, the precipitation of argentojarosite, which forms during the leaching process, limits the availability of silver ion in solution which may act as a catalyst. But syndicate of silver and pyrite to form of silver coated pyrite, causes dissolution increase. However, in the presence of the pyrite coated by silver, leaching was very rapid for the duration of the test, and complete copper extraction was achieved within 10 hours.","PeriodicalId":36564,"journal":{"name":"International Journal of Mining and Geo-Engineering","volume":"61 1","pages":"91-96"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90609804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.22059/IJMGE.2017.223801.594650
A. Rastbood, A. Majdi, Y. Gholipour
To judge about the performance of designed support system for tunnels, structural forces i.e. peak values of axial and shear forces and moments are critical parameters. So in this study, at first a complete database using finite element method was prepared. Then, a model of artificial neural network (ANN) using multi-layer perceptron was developed to estimate lining structural forces. Sensitivity analysis showed that among input variables, the cover of the tunnel is most influencing variable. To prove the efficiency of developed ANN model, coefficient of efficiency (CE), coefficient of correlation (R2), variance account for (VAF), and root mean square error (RMSE) calculated. Obtained results demonstrated a promising precision and high efficiency of the presented ANN method to estimate the structural forces of tunnel lining composed from concrete segments instead of alternative costly and tedious solutions.
{"title":"Prediction of structural forces of segmental tunnel lining using FEM based artificial neural network","authors":"A. Rastbood, A. Majdi, Y. Gholipour","doi":"10.22059/IJMGE.2017.223801.594650","DOIUrl":"https://doi.org/10.22059/IJMGE.2017.223801.594650","url":null,"abstract":"To judge about the performance of designed support system for tunnels, structural forces i.e. peak values of axial and shear forces and moments are critical parameters. So in this study, at first a complete database using finite element method was prepared. Then, a model of artificial neural network (ANN) using multi-layer perceptron was developed to estimate lining structural forces. Sensitivity analysis showed that among input variables, the cover of the tunnel is most influencing variable. To prove the efficiency of developed ANN model, coefficient of efficiency (CE), coefficient of correlation (R2), variance account for (VAF), and root mean square error (RMSE) calculated. Obtained results demonstrated a promising precision and high efficiency of the presented ANN method to estimate the structural forces of tunnel lining composed from concrete segments instead of alternative costly and tedious solutions.","PeriodicalId":36564,"journal":{"name":"International Journal of Mining and Geo-Engineering","volume":"39 1","pages":"71-78"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78957915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.22059/IJMGE.2017.62150
Ali Behnamfard, R. Alaei
The proximate analysis is the most common form of coal evaluation and it reveals the quality of a coal sample. It examines four factors including the moisture, ash, volatile matter (VM), and fixed carbon (FC) within the coal sample. Every factor is determined through a distinct experimental procedure under ASTM specified conditions. These determinations are time consuming and require a significant amount of laboratory equipment. The calorific value is one of the most important properties of a solid fuel and its experimental determination requires special instrumentation and highly trained analyst to operate it. This paper develops mathematical and ANFIS models for estimation of two factors of proximate analysis based on the other two factors. Furthermore, the estimation of calorific value of coal samples based on proximate analysis factors is performed using multivariable regression, the Minitab 16 software package, and the ANFIS, Matlab software package. The results indicate that ANFIS is a more powerful tool for estimation of proximate analysis factors and calorific value than multivariable regression method. The following equation estimates the calorific value of coal samples with high precision: Calorific value (btu/lb)= 12204 - 170 Moisture + 46.8 FC - 127 Ash
{"title":"Estimation of coal proximate analysis factors and calorific value by multivariable regression method and adaptive neuro-fuzzy inference system (ANFIS)","authors":"Ali Behnamfard, R. Alaei","doi":"10.22059/IJMGE.2017.62150","DOIUrl":"https://doi.org/10.22059/IJMGE.2017.62150","url":null,"abstract":"The proximate analysis is the most common form of coal evaluation and it reveals the quality of a coal sample. It examines four factors including the moisture, ash, volatile matter (VM), and fixed carbon (FC) within the coal sample. Every factor is determined through a distinct experimental procedure under ASTM specified conditions. These determinations are time consuming and require a significant amount of laboratory equipment. The calorific value is one of the most important properties of a solid fuel and its experimental determination requires special instrumentation and highly trained analyst to operate it. This paper develops mathematical and ANFIS models for estimation of two factors of proximate analysis based on the other two factors. Furthermore, the estimation of calorific value of coal samples based on proximate analysis factors is performed using multivariable regression, the Minitab 16 software package, and the ANFIS, Matlab software package. The results indicate that ANFIS is a more powerful tool for estimation of proximate analysis factors and calorific value than multivariable regression method. The following equation estimates the calorific value of coal samples with high precision: Calorific value (btu/lb)= 12204 - 170 Moisture + 46.8 FC - 127 Ash","PeriodicalId":36564,"journal":{"name":"International Journal of Mining and Geo-Engineering","volume":"130 1","pages":"29-35"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73508892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-06-01DOI: 10.22059/IJMGE.2017.62152
A. Alipour, A. Khodaiari, A. Jafari, R. Tavakkoli-Moghaddam
In an Open-Pit Production Scheduling (OPPS) problem, the goal is to determine the mining sequence of an orebody as a block model. In this article, linear programing formulation is used to aim this goal. OPPS problem is known as an NP-hard problem, so an exact mathematical model cannot be applied to solve in the real state. Genetic Algorithm (GA) is a well-known member of evolutionary algorithms that widely are utilized to solve NP-hard problems. Herein, GA is implemented in a hypothetical Two-Dimensional (2D) copper orebody model. The orebody is featured as two-dimensional (2D) array of blocks. Likewise, counterpart 2D GA array was used to represent the OPPS problem’s solution space. Thereupon, the fitness function is defined according to the OPPS problem’s objective function to assess the solution domain. Also, new normalization method was used for the handling of block sequencing constraint. A numerical study is performed to compare the solutions of the exact and GA-based methods. It is shown that the gap between GA and the optimal solution by the exact method is less than % 5; hereupon GA is found to be efficiently in solving OPPS problem.
{"title":"A genetic algorithm approach for open-pit mine production scheduling","authors":"A. Alipour, A. Khodaiari, A. Jafari, R. Tavakkoli-Moghaddam","doi":"10.22059/IJMGE.2017.62152","DOIUrl":"https://doi.org/10.22059/IJMGE.2017.62152","url":null,"abstract":"In an Open-Pit Production Scheduling (OPPS) problem, the goal is to determine the mining sequence of an orebody as a block model. In this article, linear programing formulation is used to aim this goal. OPPS problem is known as an NP-hard problem, so an exact mathematical model cannot be applied to solve in the real state. Genetic Algorithm (GA) is a well-known member of evolutionary algorithms that widely are utilized to solve NP-hard problems. Herein, GA is implemented in a hypothetical Two-Dimensional (2D) copper orebody model. The orebody is featured as two-dimensional (2D) array of blocks. Likewise, counterpart 2D GA array was used to represent the OPPS problem’s solution space. Thereupon, the fitness function is defined according to the OPPS problem’s objective function to assess the solution domain. Also, new normalization method was used for the handling of block sequencing constraint. A numerical study is performed to compare the solutions of the exact and GA-based methods. It is shown that the gap between GA and the optimal solution by the exact method is less than % 5; hereupon GA is found to be efficiently in solving OPPS problem.","PeriodicalId":36564,"journal":{"name":"International Journal of Mining and Geo-Engineering","volume":"9 1","pages":"47-52"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85146242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-12-01DOI: 10.22059/IJMGE.2016.59826
Fatemeh Amirpoursaeid, O. Asghari
Truncated Gaussian Simulation (TGS) is a well-known method to generate realizations of the ore domains located in a spatial sequence. In geostatistical framework geological domains are normally utilized for stationary assumption. The ability to measure the uncertainty in the exact locations of the boundaries among different geological units is a common challenge for practitioners. As a simple and informative example of such a boundary, one can consider the boundary between ore and waste materials in an ore deposit. This boundary addresses the percentages of the ore and the waste, and also affect the future economy of mine and all precedent mine designs and mine plans. Deterministic approaches, based on interpretation of geological phenomenon, provide just one scenario of ore-waste variation, and do not offer a model for uncertainty of boundaries. On the other hand, geostatistical simulations, based on stochastic models, can measure the uncertainty of such a boundary. Through different techniques for spatial simulation of the categorical data (geological domains) truncated gaussian simulation has been proved to be versatile when geological units have sequential geometries and/or there are few number of indicators (ore and waste). This study addresses the application of TGS for conditional simulation of ore and waste domains in Golgohar iron ore deposit. Separation of the ore and waste domains has affected the ore tonnage estimation and resource evaluation. Various simulations can be considered as the spatial realizations of ore and waste. TGS can generate realizations of the domains and measure the uncertainty of ore-waste boundary. The accuracy of result has been checked through performance evaluation section and different scenarios (e.g. best, average and worst). The best scenario is the one with the most accuracy that is calculated from confusion matrix. The scenario No. 44 with 96 million cubic meters tonnage has an accuracy over 86 percent that is proposed as the best scenario for future mine design and planning.
{"title":"Application of truncated gaussian simulation to ore-waste boundary modeling of Golgohar iron deposit","authors":"Fatemeh Amirpoursaeid, O. Asghari","doi":"10.22059/IJMGE.2016.59826","DOIUrl":"https://doi.org/10.22059/IJMGE.2016.59826","url":null,"abstract":"Truncated Gaussian Simulation (TGS) is a well-known method to generate realizations of the ore domains located in a spatial sequence. In geostatistical framework geological domains are normally utilized for stationary assumption. The ability to measure the uncertainty in the exact locations of the boundaries among different geological units is a common challenge for practitioners. As a simple and informative example of such a boundary, one can consider the boundary between ore and waste materials in an ore deposit. This boundary addresses the percentages of the ore and the waste, and also affect the future economy of mine and all precedent mine designs and mine plans. Deterministic approaches, based on interpretation of geological phenomenon, provide just one scenario of ore-waste variation, and do not offer a model for uncertainty of boundaries. On the other hand, geostatistical simulations, based on stochastic models, can measure the uncertainty of such a boundary. Through different techniques for spatial simulation of the categorical data (geological domains) truncated gaussian simulation has been proved to be versatile when geological units have sequential geometries and/or there are few number of indicators (ore and waste). This study addresses the application of TGS for conditional simulation of ore and waste domains in Golgohar iron ore deposit. Separation of the ore and waste domains has affected the ore tonnage estimation and resource evaluation. Various simulations can be considered as the spatial realizations of ore and waste. TGS can generate realizations of the domains and measure the uncertainty of ore-waste boundary. The accuracy of result has been checked through performance evaluation section and different scenarios (e.g. best, average and worst). The best scenario is the one with the most accuracy that is calculated from confusion matrix. The scenario No. 44 with 96 million cubic meters tonnage has an accuracy over 86 percent that is proposed as the best scenario for future mine design and planning.","PeriodicalId":36564,"journal":{"name":"International Journal of Mining and Geo-Engineering","volume":"31 7 1","pages":"175-181"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76698715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-12-01DOI: 10.22059/IJMGE.2016.59875
A. N. Qarahasanlou, M. Ataei, R. KhaloKakaie, B. Ghodrati, Rasoul Jafarei
Tires represent a critical spare part in mines. There is a shortage of medium and large tires. In addition, with increased mining activities and the creation of new mines, the demand for tires has increased significantly. Thus, it is particularly important for mining engineers to identify tire characteristics and correctly manage the spare part inventory. Spare parts management is critical from an operational perspective, especially in asset intensive industries, such as mining, as well as in organizations owning and operating costly assets. A knowledge of the tires’ behavior (historical data) must be considered together with the operating environment conditions (covariates). This study uses multiple regression analysis based on Cox’s regression model to incorporate machine operating environment information into systems reliability analysis to estimate spare parts. It considers a proportional hazard model and a stratified Cox regression model for time independent and dependent covariates. Based on the results, the study develops a mathematical model for spare parts estimation at the component level for non-repairable parts (tires). It validates the outcomes using a case study of loader tires in Sungun mine in Iran. There is a significant difference in the results of spare parts forecasting and inventory management when considering and not considering covariates.
{"title":"Tire demand planning based on reliability and operating environment","authors":"A. N. Qarahasanlou, M. Ataei, R. KhaloKakaie, B. Ghodrati, Rasoul Jafarei","doi":"10.22059/IJMGE.2016.59875","DOIUrl":"https://doi.org/10.22059/IJMGE.2016.59875","url":null,"abstract":"Tires represent a critical spare part in mines. There is a shortage of medium and large tires. In addition, with increased mining activities and the creation of new mines, the demand for tires has increased significantly. Thus, it is particularly important for mining engineers to identify tire characteristics and correctly manage the spare part inventory. Spare parts management is critical from an operational perspective, especially in asset intensive industries, such as mining, as well as in organizations owning and operating costly assets. A knowledge of the tires’ behavior (historical data) must be considered together with the operating environment conditions (covariates). This study uses multiple regression analysis based on Cox’s regression model to incorporate machine operating environment information into systems reliability analysis to estimate spare parts. It considers a proportional hazard model and a stratified Cox regression model for time independent and dependent covariates. Based on the results, the study develops a mathematical model for spare parts estimation at the component level for non-repairable parts (tires). It validates the outcomes using a case study of loader tires in Sungun mine in Iran. There is a significant difference in the results of spare parts forecasting and inventory management when considering and not considering covariates.","PeriodicalId":36564,"journal":{"name":"International Journal of Mining and Geo-Engineering","volume":"37 1","pages":"239-248"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75899108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-12-01DOI: 10.22059/IJMGE.2016.59823
S. Salehi, M. Noaparast, S. Z. Shafaie
In this research work, the dissolution of chalcopyrite was investigated under atmospheric pressure, with sulfate media at low temperatures, in 30°C to 50°C. In the galvanic interaction between chalcopyrite and pyrite, pyrite is used as a leaching catalyst. Effects of different parameters such as temperature, stirring speed, pyrite to chalcopyrite ratio, particle size, and solution potential were examined. Results showed that maximum copper recovery in low temperature was achieved after 24 hours, under the following condition: stirring speed of 800 rpm, pyrite to chalcopyrite ratio 4, solution potential 440 mV, temperature 50°C, and particle size of -38 microns. In addition, kinetic studies indicated that chalcopyrite dissolution with pyrite followed the shrinking core model, and the reaction was controlled by the surface reaction. Activation energy (Ea) was calculated as 88 kJ/mol.
{"title":"Kinetics of chalcopyrite galvanic leaching using sulfate media at the low temperature in the GalvanoxTM process","authors":"S. Salehi, M. Noaparast, S. Z. Shafaie","doi":"10.22059/IJMGE.2016.59823","DOIUrl":"https://doi.org/10.22059/IJMGE.2016.59823","url":null,"abstract":"In this research work, the dissolution of chalcopyrite was investigated under atmospheric pressure, with sulfate media at low temperatures, in 30°C to 50°C. In the galvanic interaction between chalcopyrite and pyrite, pyrite is used as a leaching catalyst. Effects of different parameters such as temperature, stirring speed, pyrite to chalcopyrite ratio, particle size, and solution potential were examined. Results showed that maximum copper recovery in low temperature was achieved after 24 hours, under the following condition: stirring speed of 800 rpm, pyrite to chalcopyrite ratio 4, solution potential 440 mV, temperature 50°C, and particle size of -38 microns. In addition, kinetic studies indicated that chalcopyrite dissolution with pyrite followed the shrinking core model, and the reaction was controlled by the surface reaction. Activation energy (Ea) was calculated as 88 kJ/mol.","PeriodicalId":36564,"journal":{"name":"International Journal of Mining and Geo-Engineering","volume":"78 1","pages":"157-161"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85852643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-12-01DOI: 10.22059/IJMGE.2016.59825
J. Mehrabani, S. Z. Shafaei, M. Noaparast, M. Mousavi
In this research work, the zinc extraction was investigated, using bioleaching process from a low grade zinc concentrate which was produced from the accumulated flotation tailings. Zinc content was initially upgraded to 11.97% by flotation process. Bioleaching experiments were designed and carried out by a mixed culture of Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirilium ferrooxidans, as well as a mixed moderate thermophile bacteria in the shake flasks. Effect of two types bacteria, indigenous bacteria accompany by concentrate sample, and added mixture of bacteria were evaluated. The term of indigenous bacteria refers to the bacteria which initially exist in the natural concentrate sample. The results showed that more than 87% and 94% of Zn was dissolved in the bioleaching condition of mesophile and moderate thermophile bacteria, respectively. Comparing bioleaching and leaching tests indicated that mesophile bacteria improved Zn extraction 36%, in which contribution of concentrate indigenous bacteria (test condition of non-inoculation) and added mesophile mixed bacteria were equal to 34% and 66% of that improvement, respectively. In addition, moderate thermophile bacteria improved sphalerite leaching up to 38% in which contribution of concentrate indigenous bacteria and added moderate bacteria were about 50% separately.
{"title":"Bioleaching of a low grade sphalerite concentrate produced from flotation tailings","authors":"J. Mehrabani, S. Z. Shafaei, M. Noaparast, M. Mousavi","doi":"10.22059/IJMGE.2016.59825","DOIUrl":"https://doi.org/10.22059/IJMGE.2016.59825","url":null,"abstract":"In this research work, the zinc extraction was investigated, using bioleaching process from a low grade zinc concentrate which was produced from the accumulated flotation tailings. Zinc content was initially upgraded to 11.97% by flotation process. Bioleaching experiments were designed and carried out by a mixed culture of Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirilium ferrooxidans, as well as a mixed moderate thermophile bacteria in the shake flasks. Effect of two types bacteria, indigenous bacteria accompany by concentrate sample, and added mixture of bacteria were evaluated. The term of indigenous bacteria refers to the bacteria which initially exist in the natural concentrate sample. The results showed that more than 87% and 94% of Zn was dissolved in the bioleaching condition of mesophile and moderate thermophile bacteria, respectively. Comparing bioleaching and leaching tests indicated that mesophile bacteria improved Zn extraction 36%, in which contribution of concentrate indigenous bacteria (test condition of non-inoculation) and added mesophile mixed bacteria were equal to 34% and 66% of that improvement, respectively. In addition, moderate thermophile bacteria improved sphalerite leaching up to 38% in which contribution of concentrate indigenous bacteria and added moderate bacteria were about 50% separately.","PeriodicalId":36564,"journal":{"name":"International Journal of Mining and Geo-Engineering","volume":"10 1","pages":"169-173"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90866139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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