پیوندهای مفید
آمار
| تعداد نشریات | 8 |
| تعداد شمارهها | 435 |
| تعداد مقالات | 5,634 |
| تعداد مشاهده مقاله | 7,427,968 |
| تعداد دریافت فایل اصل مقاله | 6,216,017 |
بررسی روابط میان مولفههای ژئومکانیکی تاثیرگذار بر انتخاب روشهای استخراج زیرزمینی با رویکرد دیمتل فازی | ||
| نشریه مهندسی عمران امیرکبیر | ||
| مقاله 10، دوره 55، شماره 10، دی 1402، صفحه 2135-2148 اصل مقاله (1.86 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/ceej.2023.22268.7941 | ||
| نویسندگان | ||
| زینب جهانبانی1؛ مجید عطائی پور* 1؛ علی مرتضوی2 | ||
| 1دانشکده مهندسی معدن، دانشگاه صنعتی امیرکبیر، تهران، ایران | ||
| 2استاد دانشکده معدن و علوم زمین، دانشگاه نظربایف، آستانا، قزاقستان | ||
| چکیده | ||
| در وقوع ریسکهای ژئومکانیکی در معادن زیرزمینی نه یک فاکتور بهتنهایی، بلکه مجموعهای از فاکتورها در ارتباط با یکدیگر عمل میکنند. لذا انتخاب یک روش استخراج زیرزمینی مناسب و مطالعه ارتباط و اندرکنش موجود میان فاکتورهای ژئومکانیکی و زمینشناسی موثر در آن، قبل از شروع معدنکاری، میتواند در بیشینهسازی سود و بازیابی از منابع معدنی، افزایش بهرهوری و کاهش هزینههای تولید و افت ماده معدنی و در نهایت ایجاد یک محیط ایمن برای معدنکاران در زیر زمین بسیار مفید باشد. لذا با توجه به اهمیت موضوع، در این تحقیق با کاربرد روش دیمتل فازی به تحلیل ساختار حاکم بر پارامترها از دیدگاه اثرگذاری و چگونگی روابط آنها با یکدیگر و همچنین بررسی اهمیت هر یک از آنها پرداخته شد. برای اجرای این تکنیک، ابتدا پرسشنامههایی طراحی و در میان متخصصان توزیع و سپس 18 پرسشنامه برای ارزیابی پارامترها دریافت شد. در نهایت با اجرای این روش، بردارهای برتری (R+C) و ارتباط (R-C) و درنتیجه میزان اهمیت، اثرگذاری و اثرپذیری برای هر یک از پارامترها محاسبه شد. نتایج حاصل از تحقیق نشان میدهد که شاخصهای فاصلهداری ناپیوستگیها و سپس ساختارهای اصلی زمینشناسی کانسار (درزهها و ناپیوستگیها، گسلها، صفحات ضعیف و دایکها)، تاثیرگذارترین و امتیاز ردهبندی تودهسنگ و مدول تغییر شکلپذیری تودهسنگ به ترتیب تاثیرپذیرترین فاکتورها هستند. نمودار علّی ترسیم شده برای پارامترهای مؤثر در فرآیند انتخاب روشهای استخراج زیرزمینی و وقوع ریسکهای ژئومکانیکی در معادن زیرزمینی نیز نشان میدهد که پارامتر امتیاز ردهبندی تودهسنگ دارای بیشترین مقدار برتری است و از اینرو دارای بیشترین اهمیت در بین سایر پارامترها میباشد. | ||
| کلیدواژهها | ||
| معیارهای تاثیرگذار؛ انتخاب روش استخراج زیرزمینی؛ ریسکهای ژئومکانیکی؛ دیمتل فازی؛ مدلسازی ساختاری | ||
| موضوعات | ||
| استخراج معدن | ||
| عنوان مقاله [English] | ||
| Investigating the interaction of geomechanical factors influencing the underground mining method selection using fuzzy DEMATEL method | ||
| نویسندگان [English] | ||
| Zeinab Jahanbani1؛ Majid Ataee-pour1؛ Ali Mortazavi2 | ||
| 1Department of Mining Engineering, Amirkabir University of Technology, Tehran, Iran | ||
| 2School of Mining and Geosciences, Nazarbayev University, Astana, Kazakhstan | ||
| چکیده [English] | ||
| In the occurrence of geomechanical risks in underground mines, not only one factor, but a set of factors are closely related to each other. Therefore, choosing a suitable underground mining method and studying the relationship and interaction between the geomechanical and geological factors affecting it, before starting the mining process, can maximize profit and recovery, increase productivity, reduce production costs and ore losses, and finally create a safe environment for underground miners. Therefore, according to the importance of the subject, in this research, using the fuzzy DEMATEL method, the structure governing the factors was analyzed from the point of view of their influence and how they relate to each other, and also the importance of them. To implement this technique, first questionnaires were designed and distributed among experts, then 18 questionnaires were received to evaluate the factors. Finally, by implementing this method, the vectors of R, C, R+C, and R-C were calculated for each factor. The results show that the factors of discontinuity spacing and geological structures of the deposit have the highest (cause factors), and the criteria of Rock Mass Rating (RMR) and rock mass deformation modulus have the lowest impact (effect factors), respectively. The causal diagram drawn for the geomechanical factors influencing the underground mining method selection and the occurrence of geomechanical risks in underground mines, also shows that the Rock Mass Rating (RMR) factor has the highest prominence value and therefore has the most importance among all other parameters. | ||
| کلیدواژهها [English] | ||
| Influential criteria, underground mining method selection, geomechanical risks, fuzzy DEMATEL method, structural modeling | ||
| مراجع | ||
|
[1] M.A. Idris, Probabilistic stability analysis of underground mine excavations, Luleå tekniska universitet, Ph. D Thesis, 2014. [2] S. Gupta, U. Kumar, An analytical hierarchy process (AHP)-guided decision model for underground mining method selection, International journal of mining, reclamation and environment, 26(4) (2012) 324-336. [3] F.S. Namin, K. Shahriar, A. Bascetin, S. Ghodsypour, Practical applications from decision-making techniques for selection of suitable mining method in Iran, Gospodarka Surowcami Mineralnymi, 25 (2009) 57-77. [4] S. Alpay, M. Yavuz, A decision support system for underground mining method selection, in: International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, Springer, 2007, pp. 334-343. [5] B.C. Balusa, J. Singam, Underground mining method selection using WPM and PROMETHEE, Journal of the Institution of Engineers (India): Series D, 99(1) (2018) 165-171. [6] Z. Fu, X. Wu, H. Liao, F. Herrera, Underground mining method selection with the hesitant fuzzy linguistic gained and lost dominance score method, IEEE Access, 6 (2018) 66442-66458. [7] B.C. Balusa, A.K. Gorai, Sensitivity analysis of fuzzy-analytic hierarchical process (FAHP) decision-making model in selection of underground metal mining method, Journal of Sustainable Mining, 18(1) (2019) 8-17. [8] S. Bajić, D. Bajić, B. Gluščević, V. Ristić Vakanjac, Application of fuzzy analytic hierarchy process to underground mining method selection, Symmetry, 12(2) (2020) 192. [9] O. Ghazdali, J. Moustadraf, T. Tagma, B. Alabjah, F. Amraoui, Study and evaluation of the stability of underground mining method used in shallow-dip vein deposits hosted in poor quality rock, Mining of Mineral Deposits, 15(3) (2021) 31-38. [10] M.A. Ali, J.-G. Kim, Selection mining methods via multiple criteria decision analysis using TOPSIS and modification of the UBC method, Journal of Sustainable Mining, 20 (2021). [11] F.S. Namin, A. Ghadi, F. Saki, A literature review of Multi Criteria Decision-Making (MCDM) towards mining method selection (MMS), Resources Policy, 77 (2022) 102676. [12] M. Kiani, S.H. Hosseini, M. Taji, M. Gholinejad, Mining of Mineral Deposits, (2021). [13] E. Selerio Jr, J.A. Caladcad, M.R. Catamco, E.M. Capinpin, L. Ocampo, Emergency preparedness during the COVID-19 pandemic: Modelling the roles of social media with fuzzy DEMATEL and analytic network process, Socio-economic planning sciences, 82 (2022) 101217. [14] A. Muhafidzah, K. Ramli, Interdependency and Priority of Critical Infrastructure Information (Case Study: Indonesia Payment System), Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 6(3) (2022) 403-411. [15] H. Hamedi, A. Mehdiabadi, Entrepreneurship resilience and Iranian organizations: application of the fuzzy DANP technique, Asia Pacific Journal of Innovation and Entrepreneurship, 14(3) (2020) 231-247. [16] C. Valmohammadi, M.M. Khaki, Determinants for selection of projects for exploitation of mines in Iran, Resources Policy, 63 (2019) 101424. [17] A. Baykasoğlu, V. Kaplanoğlu, Z.D. Durmuşoğlu, C. Şahin, Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection, Expert systems with applications, 40(3) (2013) 899-907. [18] C.-J. Lin, W.-W. Wu, A causal analytical method for group decision-making under fuzzy environment, Expert Systems with Applications, 34(1) (2008) 205-213. [19] S.M. Lavasani, A. Zendegani, M. Celik, An extension to Fuzzy Fault Tree Analysis (FFTA) application in petrochemical process industry, Process Safety and Environmental Protection, 93 (2015) 75-88. [20] L.M. MIRI, J. Wang, Z. Yang, J. Finlay, Application of fuzzy fault tree analysis on oil and gas offshore pipelines, (2011). [21] S. Alpay, M. Yavuz, Underground mining method selection by decision making tools, Tunnelling and Underground Space Technology, 24(2) (2009) 173-184. [22] M. Ataei, M. Jamshidi, F. Sereshki, S. Jalali, Mining method selection by AHP approach, Journal of the Southern African Institute of Mining and Metallurgy, 108(12) (2008) 741-749. [23] M. Ataei, H. Shahsavany, R. Mikaeil, Monte Carlo Analytic Hierarchy Process (MAHP) approach to selection of optimum mining method, International Journal of Mining Science and Technology, 23(4) (2013) 573-578. [24] B.C. Balusa, A.K. Gorai, A comparative study of various multi-criteria decision-making models in underground mining method selection, Journal of The Institution of Engineers (India): Series D, 100(1) (2019) 105-121. [25] D. Bogdanovic, D. Nikolic, I. Ilic, Mining method selection by integrated AHP and PROMETHEE method, Anais da Academia Brasileira de Ciências, 84 (2012) 219-233. [26] H. Dehghani, A. Siami, P. Haghi, A new model for mining method selection based on grey and TODIM methods, Journal of Mining and Environment, 8(1) (2017) 49-60. [27] M. Iphar, S. Alpay, A mobile application based on multi-criteria decision-making methods for underground mining method selection, International Journal of Mining, Reclamation and Environment, 33(7) (2019) 480-504. [28] A. Karadogan, A. Kahriman, U. Ozer, Application of fuzzy set theory in the selection of underground mining method, Journal of the Southern African Institute of Mining and Metallurgy, 108(2) (2008) 73-79. [29] H. Karimnia, H. Bagloo, Optimum mining method selection using fuzzy analytical hierarchy process–Qapiliq salt mine, Iran, International Journal of Mining Science and Technology, 25(2) (2015) 225-230. [30] R. Mikaeil, M.Z. Naghadehi, M. Ataei, R. Khalokakaie, A decision support system using fuzzy analytical hierarchy process (FAHP) and TOPSIS approaches for selection of the optimum underground mining method, Archives of Mining Sciences, 54(2) (2009) 341-368. [31] M.Z. Naghadehi, R. Mikaeil, M. Ataei, The application of fuzzy analytic hierarchy process (FAHP) approach to selection of optimum underground mining method for Jajarm Bauxite Mine, Iran, Expert Systems with Applications, 36(4) (2009) 8218-8226. [32] G. Popovic, B. Djordjevic, D. Milanovic, Multiple criteria approach in the mining method selection, Industrija, 47(4) (2019). [33] M. Yavuz, The application of the analytic hierarchy process (AHP) and Yager’s method in underground mining method selection problem, International Journal of Mining, Reclamation and Environment, 29(6) (2015) 453-475. [34] A. Yazdani-Chamzini, S. Haji Yakchali, E. Kazimieras Zavadskas, Using a integrated MCDM model for mining method selection in presence of uncertainty, Economic research-Ekonomska istraživanja, 25(4) (2012) 869-904. [35] S. Heidarzadeh, A. Saeidi, A. Rouleau, Use of probabilistic numerical modeling to evaluate the effect of geomechanical parameter variability on the probability of open-stope failure: a case Study of the Niobec Mine, Quebec (Canada), Rock Mechanics and Rock Engineering, 53(3) (2020) 1411-1431. [36] M. Cai, Rock mass characterization and rock property variability considerations for tunnel and cavern design, Rock mechanics and rock engineering, 44 (2011) 379-399. [37] J.C. Langford, Application of reliability methods to the design of underground structures, Queen's University (Canada), 2013. [38] B.H. Brady, E.T. Brown, Rock mechanics: for underground mining, Springer science & business media, 2006. [39] D.M. Milne, Underground design and deformation based on surface geometry, University of British Columbia, 1997. [40] A. Palmstrom, H. Stille, Ground behaviour and rock engineering tools for underground excavations, Tunnelling and Underground Space Technology, 22(4) (2007) 363-376. [41] R. Rafiee, M. Ataei, R. Khalokakaie, S.M.E. Jalali, F. Sereshki, Determination and assessment of parameters influencing rock mass cavability in block caving mines using the probabilistic rock engineering system, Rock Mechanics and Rock Engineering, 48 (2015) 1207-1220. [42] R. Mishra, R. Kiuru, L. Uotinen, M. Janiszewski, M. Rinne, Combining expert opinion and instrumentation data using Bayesian networks to carry out stope collapse risk assessment, in: MGR 2019: Proceedings of the First International Conference on Mining Geomechanical Risk, Australian Centre for Geomechanics, 2019, pp. 85-96. [43] A.A. Antoniou, E. Lekkas, Rockfall susceptibility map for Athinios port, Santorini island, Greece, Geomorphology, 118(1-2) (2010) 152-166. [44] M. Pender, M. Free, Stability assessment of slopes in closely jointed rock masses, in: ISRM International Symposium-EUROCK 93, OnePetro, 1993. [45] E.T. Brown, Risk assessment and management in underground rock engineering—an overview, Journal of Rock Mechanics and Geotechnical Engineering, 4(3) (2012) 193-204. [46] E.T. Brown, Block caving geomechanics, (2002). | ||
|
آمار تعداد مشاهده مقاله: 713 تعداد دریافت فایل اصل مقاله: 816 |
||