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Journal of Mining and Environment، جلد ۱۲، شماره ۱، صفحات ۲۸۱-۲۹۷
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عنوان انگلیسی Analysis of Grinding and Chipping Processes beneath Disc Cutters of Hard Rock Tunnel Boring Machines (Case study: Uma-Oya water Conveyance Tunnel, SriLanka)
چکیده انگلیسی مقاله Mechanized tunneling in rocks is based on fracture propagation and rock fragmentation under disc cutters. Rock chipping is an efficient kind of fragmentation process, while the grinding process may occur under special conditions. The cutter-head penetration is an appropriate parameter involved in order to distinguish between the chipping and grinding processes in rock cutting. In this work, the grinding and chipping processes are investigated in the Uma-Oya water conveyance tunnel in Sri Lanka. The Uma-Oya project is a water transfer, hydropower, and irrigation system in the SE part of the central highland region of Sri-Lanka. From a geological viewpoint, most parts of the tunnel route in the studied section consist of very strong and abrasive metamorphic rocks that potentially are susceptible to grinding occurrence during the boring process under disc cutters. In this work, firstly, data processing is performed in order to identify the boundary between chipping and grinding. Then the chipping and grinding processes are modeled using the practical numerical and artificial intelligent methods. In the numerical modeling stage, we try to make the modeling as realistic as possible. The results obtained from these modeling methods show that for the penetrations less than 3 mm/rev, the grinding process is dominant, and for the penetrations more than 3 mm/rev, rock chipping occurs. Also, in the numerical modeling, no significant fracture expansion is observed in the rock when the penetration is less than 3 mm/rev. Moreover, it can be seen in the numerical modeling of the chipping process that the propagated fractures come together and the chips are created.
کلیدواژه‌های انگلیسی مقاله Grinding and chipping phenomena, TBM penetration rate, TBM performance, Numerical Modeling, Artificial Neural Networks
نویسندگان مقاله Seyed M. Pourhashemi |
Department of Mining Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

K. Ahangari |
Department of Mining Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

J. Hassanpour |
School of Geology, College of Science, University of Tehran, Tehran, Iran

Seyed M. Eftekhari |
Department of Mining Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran

نشانی اینترنتی http://jme.shahroodut.ac.ir/article_1985_bb63344053a3ada4da611dbe8f356272.pdf
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