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1 - Application of gravity separators for enrichment of South Chah-Palang tungsten ore https://ijmge.ut.ac.ir/article_57304.html 10.22059/ijmge.2016.57304 1 In the present study, the possibility of concentrating tungsten-copper vein ore in South Chah-Palang was examined using gravity separators including Jig Machine (-2360+600 μm), shaking table (-600+120 μm), and multi-gravity separator (MGS) (-120 μm). The representative sample contains 1.5% WO3 and 5.95% CuO. The main tungsten minerals were ferberite and wolframite and their appropriate liberation degree was approximately in the range of 250 μm. Box-Behenken and CCD response surface methods were applied to model and optimize jig machine and MGS results, respectively. Shaking table performance was modeled by full factorial design method. In Jig machine tests, the effects of water flow rate, frequency and feed particle size were investigated. Deck inclination, wash water, and feed water flow rate were operational parameters in shaking table. In the MGS testes, the effects of two parameters of tilt angle and wash water flow rate were inspected. In this set of experiments, WO3 recovery and grade were considered as responses of each model. The maximum recovery of WO3 in jig machine was obtained in water flow rate of 3.71 lit/min, frequency of 153rpm, and the particle size range of -2360+1700 μm. In this case, the grade and recovery of WO3 were 2.85% and 94.33%, respectively. The maximum WO3 recovery was 93.9% with grade of 8.20 % using shaking table in the deck inclination of 11 degree, feed water flow rate of 7 lit/min, and wash water flow rate of 8 lit/min. The maximum WO3 recovery in MGS attained with 3.45 degrees tilt angle and wash water rate of 3.16 lit/min. The grade and recovery of WO3 in the MGS method were 4.2% and 90.61%, respectively. 0 - 1 12 - - Hamid Hedayati Sarab-shahrak M.Sc., Mineral Processing, School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran Iran h.hedayati2012@gmail.com - - Mohammad Noaparast Professor, Mineral Processing, School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran Iran noparast@ut.ac.ir - - Sied Ziaedin Shafaei Tonkaboni Professor, Mineral Processing, School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran Iran zshafaie@ut.ac.ir - - Sied Mehdi Hosseini M.Sc., Mineral Processing, Mining & Metallurgical Engineering, Yazd University, Yazd, Iran Iran ng_kg2000@yahoo.com gravity separation Jig Machine MGS shaking table tungsten ore [1]. Lassner, E., Schubert, W.D. (1998). Tungsten: properties, chemistry, technology of the element,##alloys, and chemical compounds. Chapter 5, Kluwer Academic/Plenum Pub. Co., New York.##[2]. Srinivas, K., Sreenivas, T., Natarajan, R., Padamanabhan, N.P.H. (2000). Studies on the recovery of tungsten from a composite wolframite– scheelite concentrate. Hydrometallurgy., No. 58, PP. 43-50.##[3]. Zhao, Z., Li, J., Wang, S., Li, H., Liu, M., Sun, P., Li, Y. (2011). Extracting tungsten from scheelite concentrate with caustic soda by autoclaving process. Hydrometallurgy., No. 108, PP. 152-162.##[4]. Ghosh, C., Pai, D.R., Narasimham, J.B., Majumdar, K.K. Beneficiation of low grade wolframite ore from Degana, Rajasthan.##[5]. Davies, P.O.J., Goodman, R.H., Deschamps, J.A. (1991). Recent developments in spiral design, construction and application. Minerals Engineering., Vol. 4, No. 3/4, PP. 437-456.##[6]. Sutaone, A.T., Raju, k.s. (2000). Physical Separation Processing of Bulk Tin-Tungsten Pre-concentration into Individual Constituents for Commercial Applications. International mineral processing congress, C9.7-12.##[7]. Clemente, D., Newling, p., Botelho de Sousa, A., Lejeune, G., Barber, S.P., and Tucker, P. (1993). Reprocessing Slime Tailing from a Tungsten mine. Minerals Engineering., VoL. 6, Issues 8–10, PP. 831-839.##[8]. Greaves, J.n. (1989). Tungsten and Gold Recovery from Alaskan Scheelite-Bearing Ores. Report of Investigations 9251, Bureau of Mines and United States Department of the Interior.##[9]. Will Mitchell, Jr., Sollenberger, C.L., Kirkland, T.G. (1952). Flotation Test on Korean Scheelite Ore. J. of Mining Eng., Vol. 190, PP. 60-64.##[10]. Rao, G.M., Subrahmanyan, N.N. (1936). Beneficiation of Tungsten ores in India- problems, processes, applications, and demands in general on a global scene. Fizykochemiczne Problemy Mineralurgii., No 18, PP. 23-37.##[11]. Srivastava, J.P., Pathak, P.N. (2000). Pre-concentration: a necessary step for upgrading tungsten ore. Int. J. Miner. Process., No 60, PP. 1–8.##[12]. Mohammadnejad, S., Noaparast, M., Shafaei Tonkaboni, S.Z., Olyaei, Y., Haghi, H., Hosseini, S.M. (2015). Application of Shaking Table in Scheelite Enrichment from Nezam Abad Mine Using Box-Behenken Design. XVI Balkan Mineral Processing Congress (BMPC2015), Vol. 1, Section 4. PP. 299-303.##[13]. Aslan, N. (2007). Modeling and optimization of Multi-Gravity Separator to produce celestite concentrate. Powder Technology., No 174, PP. 127–133.##[14]. Aslan, N. (2008). Multi-objective optimization of some process parameters of a multi-gravity separator for chromite concentration. Separation and Purification Technology., No 64, PP. 237–241.##[15]. Aslan, N. (2007). Application of response surface methodology and central composite rotatable design for modeling the influence of some operating variables of a Multi-Gravity Separator for coal cleaning. Fuel., No 86, PP. 769–776.##[16]. Selim, A.Q., El-Midany, A.A., Abdel-Fattah, A.S., Ibrahim, S.S. (2010). Rationalization of the up-grading circuit of celestite for advanced applications. Powder Technology., No 198, PP. 233–239.##[17]. Aslan, N., Cifci, F., Yanb, A.D. (2008). Optimization of process parameters for producing graphite concentrate using response surface methodology. Separ. Purif .Technol., No 59, PP. 9–16.##[18]. Mehrabania, J.V., Noaparasta, M., Mousavi, S.M., Dehghand, R., Ghorbani, A. (2010). Process optimization and modelling of sphalerite flotation from a low-grade Zn-Pb ore using response surface methodology. Separation and Purification Technology., No 72, PP. 242–249.##[19]. Aslan, N. (2008). Application of response surface methodology and central composite rotatable design for modeling and optimization of a multi-gravity separator for chromite concentration. Powder Technology., No 185, PP. 80–86.##[20]. Frank, F.A. (2003). Gravity separation in. SME principles of mineral processing. 2nd. Ed. Chapter 2, New York.##[21]. Montgomery, D.C. (2001). Design and Analysis of Experiments. New York: John Wiley & Sons.##

1 - A real-time approach toward the chemical quality control of rock material (Case study: Gravel mines in Semnan, Iran https://ijmge.ut.ac.ir/article_57305.html 10.22059/ijmge.2016.57305 1 The quality of concrete is highly dependent on the characteristics of its aggregate, such as the size, minerals, and their chemical properties. Even a small amount of impurities, such as hydrated sulfates, chlorine (salt), and acidic pH of the rock material, can adversely affect the quality of the concrete. Thus, many national codes and standards are developed for testing, selecting, and employing the rock materials in concrete. For instance, Iranian standards 446, 449, 1702, 4978, 4984, 7174, and 86721 are currently serving this purpose. In the present research, a new real-time system was developed in order to replace the customary chemical analysis and size distribution tests. 20 samples were taken from two mines, selected by the Building Material Committee of Semnan Province, in order to determine the dissolved chlorine and sulfate, pH, density as well as size distribution. The new system is constituted of hydraulic jacks and a reservoir, designed to take samples from the conveyer in given time intervals. The samples were washed with distilled water and real-time analyses of dissolved chlorine and pH were performed. The results showed 85% agreement with the results from laboratory analyses. The correct classification rate (CCR) was 92% for 13 samples. 0 - 13 22 - - Behzad Tokhmechi Associate Professor, Faculty of Mining, Petroleum and Geophysics Engineering, University of Shahrood, Iran Iran tokhmechi@shahroodut.ac.ir - - Seyed Fazlolah Saghravani Assistant Professor, Faculty of Civil Engineering, University of Shahrood, Iran Iran saghravani@shahroodut.ac.ir - - Parham Janfeshan Araghi Ph.D. Candidate, Faculty of Civil Engineering, Isfahan University of Technology, Iran Iran parham.janfeshan@gmail.com - - Hosein Marvi Assistant Professor, Faculty of Electrical and Robotic Engineering, University of Shahrood, Iran Iran h.marvi@shahroodut.ac.ir - - Mohamad Esmaeel Borhani Mining Engineer, Zaminnegar Pasargad Co., Iran Iran me_borhani@yahoo.com - - Abolfazl Darbani Civil Engineer, Semnan Provincial Government Iran abolfazl.darbani@gmail.com concrete mixture, dissolved chloride, pH real-time analysis, rock material [1]. ISO, (1994), ISO 8402, Quality Management and Quality Assurance – Vocabulary. International Organization for Standardization, Geneva, Switzerland.##[2]. Lomas, S. (2004), QAQC Program. General Discussion. AMEC Internal document.##[3]. Sketchley, D. (1999), Case history guidelines for establishing sampling protocols and monitoring quality control. Proceedings of CIMM Annual General Meeting Symposium on Quality Control of Resource Estimations: an ISO Perspective.##[4]. Chatterjee, S. (2006). Geostatistical and image based quality control models for Indian mineral industry. Unpublished Ph.D. Thesis dissertation, IIT Kharagour, India, 272 pp.##[5]. Jimenez, A.R., Jain, A.K., Ceres, R., Pons, J.L. (2001). Automatic fruit recognition: a survey and new results using range/attenuation images. Pattern Recognition 32. 10: 1719–1736.##[6]. Miller, W., Jaskot, J., McCoy, B., and Schiller, E. (1996). A distributed system for 100% inspection of aluminum sheet products. 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A classification algorithm and optimal feature selection methodology for automated solder joint inspection. Journal of Manufacturing Systems 17: 251–262.##[11]. Oestreich, J. Tolley, W. and Rice, D. (1995). The development of a color sensor system to measure mineral compositions. Minerals Engineering 1.2:31-39.##[12]. Perez, C., Casali, A., Gonzalez, G., Vallebuona, G., and Vargas, R. (2000). Lithological composition sensor based on digital image feature extraction, genetic selection of features and neural classification. In Proc. of the Int. Con. on Information Intelligence & Systems, IEEE, Bethesda, pp. 236-241.##[13]. Casali, A., Gonzalez, G., Vallebuona, G., Perezq C. and Vargas, R. (2001). Grind ability Soft-Sensors Based on Lithological Composition and On-Line Measurements. Minerals Engineering 14.7:689-700.##[14]. Aydemir, S., Keskin, S., Drees, L.R. (2004). Quantification soil features using digital image processing (DIP) techniques. Geoderma 119.1:1-8.##[15]. Marmo, R., Amodio, S. (2005). Textural identification of carbonate rocks by image processing and neural network: Methodology proposal and examples. Computers & Geosciences 31:649–659.##[16]. Donskoi, E., Clout, J.M.F. (2005). Recognition – a specialized software package for iron ore characterization. In Iron Ore 2005. Aus. IMM, Fremantle pp. 203–211.##[17]. Singh, V., Singh T.N., Singh V. (2010). Image processing applications for customized mining and ore classification. Int. J. Arab Geosci. DOI: 10.1007/s12517-010-0125-2.[19] Management and Planning Organization of Iran (MPOI). (1990). Iranian Concrete Code (ABA): Technical note # 120.##[18]. Khorram F. Memarian H. Tokhmechi B. Soltanian Zadeh H. (2012) Lithological Classification Using Image Processing Technique, SME Annual Meeting and Exhibition, Washington, USA, 4 pages.##[19]. Khorram F. Memarian H. Tokhmechi B. Soltanian Zadeh H. (2012) Limestone Chemical Component Estimation using Image Processing & Pattern Recognition Techniques, Journal of Mining and Environment, Vol. 2, No. 2, pp. 49-58.##

1 - Geological Hazards analysis in Urban Tunneling by EPB Machine (Case study: Tehran subway line 7 tunnel) https://ijmge.ut.ac.ir/article_57306.html 10.22059/ijmge.2016.57306 1 Technological progress in tunneling has led to modern and efficient tunneling methods in vast underground spaces even under inappropriate geological conditions. Identification and access to appropriate and sufficient geological hazard data are key elements to successful construction of underground structures. Choice of the method, excavation machine, and prediction of suitable solutions to overcome undesirable conditions depend on geological studies and hazard analysis. Identifying and investigating the ground hazards in excavating urban tunnels by an EPB machine could augment the strategy for improving soil conditions during excavation operations. In this paper, challenges such as geological hazards, abrasion of the machine cutting tools, clogging around these tools and inside the chamber, diverse work front, severe water level fluctuations, existence of water, and fine-grained particles in the route were recognized in a study of Tehran subway line 7, for which solutions such as low speed boring, regular cutter head checks, application of soil improving agents, and appropriate grouting were presented and discussed. Due to the presence of fine particles in the route, foam employment was suggested as the optimum strategy where no filler is needed. 0 - 23 36 - - Hassan Bakhshandeh Amnieh School of Mining, College of Engineering, University of Tehran, Iran Iran hbakhshandeh@ut.ac.ir - - Mohammad Saber Zamzam Department of Mining Engineering, University of Kashan, Iran Iran mohammad_saber_zamzam@yahoo.com - - M.R. Mozdianfard Department of Chemical Engineering. University of Kashan, Iran Iran mousavi.miningeng@yahoo.com EPB geological hazards Mechanized tunneling Tehran subway line 7 [1]. Iranian Tunnelling Association (http://www.irta.ir)##[2]. International Tunnelling And Underground Space Association (http://www.ita-aites.org)##[3]. USA - UCA of SME - Underground Construction Association of SME (uca.smenet.org)##[4]. Guglielmetti , V., Grasso, P., Mahtab, , M., & Shulin, X. (2007). "Mechanized tunnellling in urban areas"., Turin, Italy: Taylor & Francis Group.##[5]. Langmaack, L. (2006). "EPB tunnelling – chances and limits. symposium on :Utilisation of underground space in urban areas"., Darmstadt, Germany: Sharm el-sheikh, Egypt.##[6]. Lambert, J.H., and Haimes, Y.Y., and Li, D., and Schooff, R.M., Tulsiani, V., (2001). "Identification, ranking, and management of risks in a major system acquisition", Reliability Engineering and system Safety, No. 72, pp. 315-325.##[7]. Ghosh, S and Jintanapakanont, J., (2004). ''Identifying and assessing the critical risk factors in an underground rail project in Thailand: a factor analysis approach"; International Journal of Project Management, Vol. 22, pp. 633–643.##[8]. Wagner, H., (2006). "Risk Evaluation and Control in Underground Construction"; International Symposium on Underground Excavation and Tunneling. 2-4 February, Bangkok: Thailand.##[9]. Herrenknecht, M. Bappler, K., (2006). "Mastering risks during mechanized excavation in urban centers with highly complex ground conditions".##[10]. Degn Eskesen, S., Tengborg, P., Kampmann, J., Holst Veicherts, T, (2004). "Guidelines for tunnelling risk management: International Tunnelling Association", Working Group No.2,##[11]. Beard, A. N., (2010). "Tunnel safety, risk assessment and decision-making", Tunnelling and Underground Space Technology, Vol. 25, pp. 91–94.##[12]. Isaksson, T., Stille, H., (2005). "Model for Estimation of Time and Cost for Tunnel Projects Based on Risk Evaluation", Rock Mechanic and Rock Engineering, Vol. 38, No. 5, pp. 373–398.##[13]. Pipattanapiwong, J., (2004). "Development of multiparty risk and uncertainty management process for an infrastructure project", Doctoral dissertation, Kochi University of Technology.##[14]. PMI (Project Management Institute); (2004). "a Guide to the Project Management Body of Knowledge (PMBOK Guide)"., Pennsylvania, Newtown Square.##[15]. BTS/ABI, (2003). "The Joint Code of Practice for Risk Management of Tunnel Works in the UK", London: BTS. (www.britishtunnelling.org).##[16]. Sepasad Engineering Company. (2008). "Execution Method, Machine Choice and TBM Technical Specifications of Tehran Subway Line 7". Tehran,Iran: Sepasad Engineering Company.##[17]. Sahel Consulting Engineers . (2008). "Engineering Geology Report of the Eastern-Western Part of Tehran Subway Line 7 Tunnel". Tehran: Sepasad Engineering Company.##[18]. 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1 - Application of fractal modeling and PCA method for hydrothermal alteration mapping in the Saveh area (Central Iran) based on ASTER multispectral data https://ijmge.ut.ac.ir/article_57307.html 10.22059/ijmge.2016.57307 1 The aim of this study is determination and separation of alteration zones using Concentration-Area (C-A) fractal model based on remote sensing data which has been extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. The studied area is on the SW part of Saveh, 1:250,000 geological map, which is located in Urumieh-Dokhtar magmatic belt, Central Iran. The pixel values were computed by Principal Component Analysis (PCA) method used to determine phyllic, argillic, and propylitic alteration zones. The C-A fractal model is utilized for separation of different parts of alteration zones due to their intensity. The log-log C-A plots reveal multifractal nature for phyllic, argillic, and propylitic alteration zones. The obtained results based on fractal model show that the main trend of the alteration zones is in NW-SE direction. Compared to the geological map of the study area and copper mineralizations, the alteration zones have been detected properly and correlate with the mineral occurrences, intrusive rock, and faults. 0 - 37 48 - - Mirko Ahmadfaraj School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran Iran mirko.ahmadfaraj@gmail.com - - Mirsaleh Mirmohammadi School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran. Iran m.mirmohammadi@ut.ac.ir - - Peyman Afzal 1- Department of Mining Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran. 2- Camborne School of Mines, University of Exeter, Penryn, UK. Iran p_afzal@azad.ac.ir ASTER Concentration–Area (C-A) fractal model hydrothermal alteration mapping Principal Component Analysis (PCA) Saveh [1] Beiranvndpour, A., & Hashim, M. (2011). Identification of hydrothermal alteration minerals for exploring of porphyry copper deposit using ASTER data, SE Iran. Journal of Asian Earth Sciences, 42(6), 1309–1323. http://doi.org/10.1016/j.jseaes.2011.07.017##[2] Beiranvandpour, A., & Hashim, M. (2012a). Identifying areas of high economic-potential copper mineralization using ASTER data in the Urumieh-Dokhtar Volcanic Belt, Iran. Advances in Space Research, 49(4), 753–769. http://doi.org/10.1016/j.asr.2011.11.028##[3] Beiranvandpour, A., & Hashim, M. (2012b). The application of ASTER remote sensing data to porphyry copper and epithermal gold deposits. Ore Geology Reviews, 44, 1–9. http://doi.org/10.1016/j.oregeorev.2011.09.009##[4] Zoheir, B., & Emam, A. (2012). Integrating geologic and satellite imagery data for high-resolution mapping and gold exploration targets in the South Eastern Desert, Egypt. 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Journal of Geochemical Exploration, 112, 131–138. http://doi.org/10.1016/j.gexplo.2011.08.002##[14] Afzal, P., Khakzad, A., Moarefvand, P., Omran, N. R., Esfandiari, B., & Alghalandis, Y. F. (2010). Geochemical anomaly separation by multifractal modeling in Kahang (Gor Gor) porphyry system, Central Iran. Journal of Geochemical Exploration, 104(1-2), 34–46. http://doi.org/10.1016/j.gexplo.2009.11.003##[15] Agterberg, F. P., Cheng, Q., Brown, a., & Good, D. (1996). Multifractal modeling of fractures in the Lac du Bonnet Batholith, Manitoba. Computers and Geosciences, 22(5), 497–507. http://doi.org/10.1016/0098-3004(95)00117-4##[16] Sim, B. L., Agterberg, F. P., & Beaudry, C. (1999). Determining the cutoff between background and relative base metal smelter contamination levels using multifractal methods. Computers and Geosciences, 25, 1023–1041. http://doi.org/10.1016/S0098-3004(99)00064-3##[17] Hassanpour, S., & Afzal, P. (2013). Application of concentration–number (C–N) multifractal modeling for geochemical anomaly separation in Haftcheshmeh porphyry system, NW Iran. Arabian Journal of Geosciences, 6(3), 957–970. http://doi.org/10.1007/s12517-011-0396-2.##[18] Shahriari, H., Ranjbar, H., & Honarmand, M. (2013). Image Segmentation for Hydrothermal Alteration Mapping Using PCA and Concentration–Area Fractal Model. Natural Resources Research, 22(3), 191–206. http://doi.org/10.1007/s11053-013-9211-y##[19] Aramesh Asl, R., Afzal, P., Adib, A., & Yasrebi, A. B. (2014). Application of multifractal modeling for the identification of alteration zones and major faults based on ETM+ multispectral data. Arabian Journal of Geosciences, 8(5), 2997–3006. http://doi.org/10.1007/s12517-014-1366-2##[20] Berberian, F., Muir, I. D., Pankhurst, R. J., & Berberian, M. (1982). Late Cretaceous and early Miocene Andean-type plutonic activity in northern Makran and Central Iran. 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Lithos, 115(1-4), 190–204. http://doi.org/10.1016/j.lithos.2009.12.002##[25] Arvin, M., Pan, Y., Dargahi, S., Malekizadeh, A., & Babaei, A. (2007). Petrochemistry of the Siah-Kuh granitoid stock southwest of Kerman, Iran: Implications for initiation of Neotethys subduction. Journal of Asian Earth Sciences, 30(3-4), 474–489. http://doi.org/10.1016/j.jseaes.2007.01.001##[26] Omrani, J., Agard, P., Whitechurch, H., Benoit, M., Prouteau, G., & Jolivet, L. (2008). Arc-magmatism and subduction history beneath the Zagros Mountains, Iran: A new report of adakites and geodynamic consequences. Lithos, 106(3-4), 380–398. http://doi.org/10.1016/j.lithos.2008.09.008##[27] Caillat, C., Dehlavi, P., Jantin, B.-M., Nogol Sadat, A., Hushmandzadeh, A., Behruzi, A., Lotfi, M., Nazer, N. K., and Mahdavi, M. (1984). Geological map of Saveh 1:250,000 sheet. Geological Survey of Iran, Tehran.##[28] Abrams, M., & Hook, S. (2002). ASTER User Handbook Version 2. Jet Propulsion Laboratory, 135. Retrieved from Abrams2002NASA.pdf##[29] Rowan, L. C., & Mars, J. C. (2003). Lithologic mapping in the Mountain Pass, California area using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Remote Sensing of Environment, 84, 350–366. http://doi.org/10.1016/S0034-4257(02)00127-X##[30] Rowan, L. C., Schmidt, R. G., & Mars, J. C. (2006). Distribution of hydrothermally altered rocks in the Reko Diq, Pakistan mineralized area based on spectral analysis of ASTER data. Remote Sensing of Environment, 104(1), 74–87. http://doi.org/10.1016/j.rse.2006.05.014##[31] Moore, F., Rastmanesh, F., Asadi, H., & Modabberi, S. (2008). Mapping mineralogical alteration using principal-component analysis and matched filter processing in the Takab area, north-west Iran, from ASTER data. International Journal of Remote Sensing, 29(10), 2851–2867. http://doi.org/10.1080/01431160701418989##[32] Tangestani, M. H., Mazhari, N., Agar, B., & Moore, F. (2008). 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1 - Accuracy evaluation of different statistical and geostatistical censored data imputation approaches (Case study: Sari Gunay gold deposit) https://ijmge.ut.ac.ir/article_57308.html 10.22059/ijmge.2016.57308 1 Most of the geochemical datasets include missing data with different portions and this may cause a significant problem in geostatistical modeling or multivariate analysis of the data. Therefore, it is common to impute the missing data in most of geochemical studies. In this study, three approaches called half detection (HD), multiple imputation (MI), and the cosimulation based on Markov model 2 (MM2) are used to impute the censored data. According to the fact that the new datasets have to satisfy the original data underlying structure, the Multidimensional Scaling (MDS) approach has been used to explore the validity of different imputation methods. Log-ratio transformation (alr transformation) was performed to open the closed compositional data prior to applying the MDS method. Experiments showed that, based on the MDS approach, the MI and the MM2 could not satisfy the original underlying structure of the dataset as well as the HD approach. This is because these two mentioned approaches have produced values higher than the detection limit of the variables. 0 - 49 60 - - Babak Ghane Simulation and Data Processing Laboratory, University College of Engineering, School of Mining Engineering, University of Tehran, Tehran, Iran Iran babakghane@ut.ac.ir - - Omid Asghari Simulation and Data Processing Laboratory, University College of Engineering, School of Mining Engineering, University of Tehran, Tehran, Iran Iran o.asghari@ut.ac.ir Censored data collocated cosimulation Markov model 2 half detection imputation Multidimensional Scaling multiple imputation [1]. Croghan, C., & Egeghy, P. P. (2003). 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W., & Aitchison, J. (2006). Log-ratios and geochemical discrimination of Scottish Dalradian limestones: a case study. Geological Society, London, Special Publications, 264(1), 25-41.##[37]. Wang, W., Zhao, J., & Cheng, Q. (2014). Mapping of Fe mineralization-associated geochemical signatures using logratio transformed stream sediment geochemical data in eastern Tianshan, China. Journal of Geochemical Exploration, 141, 6-14.##[38]. Aitchison, J. (1982). The statistical analysis of compositional data. Journal of the Royal Statistical Society. Series B (Methodological), 139-177.##[39]. Job, M. R. (2012). Application of Logratios for Geostatistical Modelling of Compositional Data (Doctoral dissertation, University of Alberta).##[40]. Wickelmaier, F. (2003). An introduction to MDS. Sound Quality Research Unit, Aalborg University, Denmark.##

1 - The reclamation of mica flakes from tailing disposal using gravity separators and flotation https://ijmge.ut.ac.ir/article_57309.html 10.22059/ijmge.2016.57309 1 A sample from the small-sized tailing pile of an Iranian mica processing plant was subjected to a series of mica recovery experiments. Mineralogical and microscopic investigations indicated that the dominant mica mineral was phlogopite which was accompanied by plagioclase feldspars. Before beneficiation studies, the particle size distribution of the representative sample was obtained, and the specifications of each size fraction were investigated in detail. It was observed that the largest portion of mica (31%) is accumulated in the size range of 0.3 to 2.0 mm. Afterward, gravity concentration and flotation experiments were carried out. Results proved that shaking table could produce a mica concentrate with grade of 74%. Also, according to the flotation tests, it seemed the best size fraction was -150+75, and after that, -100+150. Flotation in combination with attrition scrubbing produced a concentrate with 92% mica content and 70% recovery. Finally, with respect to the results of all implemented experiments, a processing flow sheet was proposed for mica reclamation from the mentioned waste disposal. 0 - 61 76 - - Seied Mohammad Raoof Hoseini Department of Mining Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran Iran raoofsmh@yahoo.com - - Ataalah Bahrami Department of Mining Engineering, Engineering Faculty, Urmia University, Urmia, Iran Iran abahrami@mail.urmia.ac.ir - - Mostafa Hosseinzadeh 3.Department of Mining Engineering, Engineering Faculty, Shahid Bahonar University, Kerman, Iran;Materials and Energy Research Center (MERC), Karaj, Iran Iran mostafac12@yahoo.com Flotation gravity separators mica flakes reclamation tailing disposal [1]. 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1 - Identification of Ti- anomaly in stream sediment geochemistry using of stepwise factor analysis and multifractal model in Delijan district, Iran https://ijmge.ut.ac.ir/article_57858.html 10.22059/ijmge.2016.57858 1 In this study, 115 samples taken from the stream sediments were analyzed for concentrations of As, Co, Cr, Cu, Ni, Pb, W, Zn, Au, Ba, Fe, Mn, Sr, Ti, U, V and Zr. In order to outline mineralization-derived stream sediments, various mapping techniques including fuzzy factor score, geochemical halos and fractal model were used. Based on these models, concentrations of Co, Cr, Ni, Zn, Ba, Fe, Mn, Ti, U, V and Zr showed anomaly and anomaly distributed in the andesitic volcanic rocks. In addition, an anomaly map of each element was also ascertained the most ideal results for the exploration of deposits. Anomaly element associations can be successfully used in future geochemical exploration works. According to stream sediment study, it characterized high anomaly of Ti deposits in the central and northern of the area and it confirmed by study of heavy mineral in sediments and litho-geochemical study in the andesitic unites. 0 - 77 95 - - Feridon Ghadimi Assistant professor, Department of Mining Engineering, Arak University of Technology, Arak, Iran Iran ghadimi@arakut.ac.ir - - Mohammad Ghomi 1-PhD of student, Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran, Iran, E-Mail: mghomi@aut.ac.ir 2- Instructor, Department of Mining Engineering, Arak University of Technology. Iran mghomi@aut.ac.ir - - Mojtaba Aref Sedigh M.Sc student, Department of Mining Engineering, Arak University of Technology, Arak, Iran Iran arefsedigh@yahoo.com Delijan Multifractal model Stepwise factor analysis Ti- anomaly

1 - Effects of Weak Layer Angle and Thickness on the Stability of Rock Slopes https://ijmge.ut.ac.ir/article_57859.html 10.22059/ijmge.2016.57859 1 This paper researches two key factors (angle and thickness) of a weak layer in relation to their influencing mechanism on slope stability. It puts forward the sliding surface angle and morphological model criteria for the control of rock slopes and realization of its failure mechanism. By comparing the Failure Modes and Safety Factors (Fs) obtained from numerical analysis, the influence pattern for the weak layer angle and thickness on the stability of rock slopes is established. The result shows that the weak layer angle influences the slope by validating the existence of the “interlocking” situation. It also illustrates that as the angle of the weak layer increases, the Fs unceasingly decreases with an Fs transformation angle. The transformation interval of the Fs demonstrates the law of diminishing of a quadratic function. Analysis of the weak layer thickness on the influence pattern of slope stability reveals three decrease stages in the Fs values. The result also shows that the increase in the thickness of the weak layer increases the failure zone and influences the mode of failure. Given the theoretical and numerical analysis of a weak layer effects on the stability of rock slopes, this work provides a guiding role in understanding the influence of a weak layer on the failure modes and safety factors of rock slopes. 0 - 97 110 - - Garmondyu Crusoe Jr China University of Mining and Technology Iran gernestcrusoe@yahoo.com - - Qing-xiang Cai China University of Mining and Technology Iran 2268076024@qq.com - - Ji-sen Shu Department of Surface mining and slope Engineering China University of Mining and Technology Iran jsshu888@126.com - - Liu Han China University of Mining and Technology Iran hanliucumt@163.com - - Yamah Barvor China University of Mining and Technology Iran yamahjayking@yahoo.com Slope stability Safety Factors Failure Modes Weak Layer

1 - A New Analytical Solution for Determination of Acceptable Overall settlement of Heap Leaching Structures Foundation https://ijmge.ut.ac.ir/article_57860.html 10.22059/ijmge.2016.57860 1 There are some artificial and natural materials on foundation of heap leaching structures. Geomembrane liner is the most important artificial isolated layer of these structures. The thickness of this layer is about 1 to 2 mm. Foundation overall settlement of such structures changes the primary length of the geomembrane layer. If the strain of geomembrane is more than allowable one, the layer will be fail and acid will leakage from the heap foundation. In this paper, foundation of the heap leaching structures is modeled with a hyperbolic curve and the length of geomembrane liner will be determined before and after loading. Next, with considering allowable strain of geomembrane materials, acceptable overall settlement of heap foundation is computed. Then, a design chart is presented for quick estimation of acceptable overall settlement of such structures. Finally, foundation overall settlement of a real case study (Tarom heap leaching structure) is determined with this approach. The analysis shows that geomembrane liner of this case may not fail due to foundation overall settlement. 0 - 111 120 - - Emad Khorasani School of Mining Engineering, College of Engineering, University of Tehran Iran emad.khorasani@yahoo.com - - mehdi amini School of Mining, College of Engineering, University of Tehran, Tehran Iran mamini@ut.ac.ir - - Saeed Soltani-Mohammadi Department of Mining Engineering, University of Kashan Iran saeedsoltani@kashanu.ac.ir heap leaching structures acceptable overall settlement geomembrane analytical method Tarom mine

1 - Estimation of the Ampere Consumption of Dimension Stone Sawing Machine Using of Artificial Neural Networks https://ijmge.ut.ac.ir/article_57861.html 10.22059/ijmge.2016.57861 1 Nowadays, estimating the ampere consumption and achieve to the optimum condition from the perspective of energy consumption is one of the most important steps to reduce the production costs. In this research it is tried to develop an accurate model for estimating the ampere consumption by using the artificial neural networks (ANN).In the first step, experimental studies were carried out on 7 carbonate rock samples in different conditions at particular feed rates (100, 200, 300and 400) and depth of cuts (15, 22, 30and 35mm) using a fully instrumented laboratory rig that is enable to change the machine parameters and measure the ampere consumption. In next step, a back propagation neural network was designed for modelling the sawing process for predicting the ampere consumption. The input network consisting of two parts: machine, work piece characteristics and the output of neural network was ampere consumption. This research evaluated the competencies of neural networks to estimate the ampere consumption in sawing process. The correlation coefficient between measured and predicted data in training and testing data is 0.95 and 0.97 respectively. The root mean square error (RMSE) for train and test data is 1.2 and 0.7 respectively. The results of this study showed that the ANNs can be used to estimate the ampere consumption with high ability and low error for industrial applications. Moreover, the cost of sawing machine ampere consumption can be accurately estimated using this neural model from some important physical and mechanical properties of rock. 0 - 121 130 - - Ahmad Aryafar Associate Professor, Faculty of Engineering, Department of Mining Engineering, University of Birjand, Birjand, Iran, P.O.Box: 97175-376 Iran aaryafar@birjand.ac.ir - - Reza Mikaeil Assistant Professor, Faculty of Engineering, Department of Mining Engineering Urmia University of Technology, Urmia, Iran Iran reza.mikaeil@gmail.com ampere consumption machine characteristic Neural Network rock characteristic

1 - An imperialist competitive algorithm for solving the production scheduling problem in open pit mine https://ijmge.ut.ac.ir/article_57862.html 10.22059/ijmge.2016.57862 1 Production scheduling (planning) of an open-pit mine is the procedure during which the rock blocks are assigned to different production periods in a way that the highest net present value of the project achieved subject to operational constraints. The paper introduces a new and computationally less expensive meta-heuristic technique known as imperialist competitive algorithm (ICA) for long-term production planning of open pit mines. The proposed algorithm modifies the original rules of the assimilation process. The ICA performance for different levels of the control factors has been studied and the results are presented. The result showed that ICA could be efficiently applied on mine production planning problem. 0 - 131 143 - - Mojtaba Mokhtarian Asl Sahand University of Technology Iran m.mokhtarian@mie.uut.ac.ir - - Javad Sattarvand Sahand University of Technology Iran jsattarvand@unr.edu Imperialist competitive algorithm Integer linear programming meta-heuristic methods Open pit mine production scheduling

1 - Transient Fluid Flow Modeling in Fractured Aquifer of Sechahoon Iron Mine Using Finite Element Method https://ijmge.ut.ac.ir/article_57863.html 10.22059/ijmge.2016.57863 1 Considering the fact that a large volume of iron reserve in the Sechahoon Iron Mine in Yazd Province has located under the water table, it is necessary to conduct a comprehensive study on water flow within the pit and its surroundings. The conceptual model of the aquifer was created using surface and underground geological information compared with water table data of the area of interest. In the data preparation stages, in order to create the numerical model, Logan and Lufran tests were studied to determine the hydrodynamic coefficients of the layers, precipitation and evaporation were investigated, and fractures and faults of the region, as a medium for flow channels in the hard formation, were also studied. The model was created in a transient state between 2000 and 2014. To validate its results, the water table was measured 4 times in the last 4 months of 2014. Considering the complexities in the heterogeneous fractured aquifer of the study area, numerical modeling results for the basin in a transient state present 90 percent correlation with field studies. Having investigated the water balance in the region, the boundary condition of the model was determined as the input water from the eastern south and the runoff water in the western north of the region. Since the general trend of faults in the area is north-south, variation in the water table is slight on north-south and intense on the east-west direction. On the other hand, due to the fact that the maximum flow is along the faults and fractures, the water table contour lines in different locations over the region are closed. 0 - 145 156 - - Mojtaba Darabi Faculty of Mining & Metallurgical Engineering, Yazd University, Yazd, Iran Iran m.darabi90@gmail.com - - Abdolhamid Ansari Faculty of Mining & Metallurgical Engineering, Yazd University, Yazd, Iran Iran h.ansari@yazd.ac.ir - - Nader Fathianpour Department of Mining Engineering, Isfahan University of Technology, Isfahan, Iran. Iran fathian@cc.iut.ac.ir - - Ahmad Ghorbani Faculty of Mining & Metallurgical Engineering, Yazd University, Yazd, Iran Iran aghorbani@yazd.ac.ir Sechahoon Iron Mine numerical modelling Fractured Formation Finite Element Method Feflow