Rock mass classification in highway tunnel engineering during exploration phase and case study

• Autorzy: Yanqiang Du , Bing Xie

Identyfikatory

DOI

10.24425/ace.2023.145258

• Języki publikacji: EN

Abstrakty

EN

It is the foundation of tunnel engineering to classify the rock mass surrounding tunnels. However, it is not easy to precisely determine the class of rock mass in practice as sufficient geological exploration need to be completed before rock mass classification, and there exists some disputes referring to the rationalization of dozens of methods for rock mass classification through the world. The principles and procedures of the basic quality method, which are widely used in China, are presented in this paper, and the application process of the basic quality method is showed with a project case of Zhongnanshan highway tunnel which has operated in safety for nearly a decade. Then, both the advantages and disadvantages of the basic quality method are analyzed in terms of practical engineering applications. In consideration of the defects of the basic quality method, the concept of the subclassing of surrounding rock in grade III-V is developed in the end and the criterion is given to determine the subclass of rock mass. This study is aimed at providing some useful ideas and a reference for rock classification in highway tunnel engineering.

Słowa kluczowe

EN

tunnel engineering; highway tunnel; rock mass classification; earth pressure; basic method; quality method

PL

inżynieria tunelowa; tunel autostradowy; klasyfikacja górotworu; ciśnienie ziemi; metoda jakości; metoda podstawowa

• Wydawca: Komitet Inżynierii Lądowej i Wodnej PAN ; Politechnika Warszawska, Wydział Inżynierii Lądowej
• Czasopismo: Archives of Civil Engineering
• Rocznik: 2023
• Tom: Vol. 69, nr 2
• Strony: 141--153
• Opis fizyczny: Bibliogr. 21 poz., il., tab.

Twórcy

autor

Yanqiang Du

• Luoyang Institute of Science and Technology, School of Civil Engineering, Luoyang, China

• https://orcid.org/0000-0001-5385-5617

autor

Bing Xie

• Luoyang Institute of Science and Technology, School of Civil Engineering, Luoyang, China

• https://orcid.org/0000-0003-1934-7859

Bibliografia

• [1] H.I. Inyang, “Development of a preliminary rock mass classification scheme for near-surface excavation”, International Journal of Mining, Reclamation and Environment, vol. 5, no. 2, pp. 65-74, 1999, doi: 10.1016/0148-9062(92)92345-D.
• [2] S. Panthee, P. Singh, A. Kainthola, and T. Singh, “Control of rock joint parameters on deformation of tunnel opening”, Journal of Rock Mechanics and Geotechnical Engineering, vol. 8, no. 4, pp. 489-498, 2016, doi: 10.1016/j.jrmge.2016.03.003.
• [3] L. Fitriyantina, I.G.B. Indrawan, and D.P.E. Putra, “Application of RMR, Q, and Japanese rock mass classification systems for design of support systems of the Narogong Weir Diversion Tunnel, West Java, Indonesia”, Advance in Science and Technology, vol. 112, pp. 59-64, 2022, doi: 10.4028/p-3mtkle.
• [4] M. Khodadad, D. Fereidooni, and K. Diamantis, “An engineering geological assessment for the Darband dam site, NE of Iran, using eight rock mass classification systems”, Innovative Infrastructure Solutions, 2022, vol. 7, no. 2, pp. 1-16, 2022, doi: 10.1007/s41062-022-00741-y.
• [5] P. Szklennik, “Numerical determination of load of a model tunnel lining, taking into account different heights of soil backfill”, Archives of Civil Engineering, vol. 68, no. 3, pp. 289-305, 2022, doi: 10.24425/ace.2022.141886.
• [6] V.M. Khatik and A.K. Nandi, “A generic method for rock mass classification”, Journal of Rock Mechanics and Geotechnical Engineering, vol. 10, no. 1, pp. 102-116, 2018, doi: 10.1016/j.jrmge.2017.09.007.
• [7] K. Terzaghi, Theoretical soil mechanics. New York, USA: J. Wiley and Sons, Inc, 1943.
• [8] Y. Jiang, H. Yoneda, and Y. Tanabashi, “Theoretical estimation of loosening pressure on tunnels in soft rock”, Tunneling and Underground Space Technology, vol. 16, no. 2, pp. 99-105, 2001, doi: 10.1016/S0886-7798(01)00034-7.
• [9] A.K. Naithani, “Rock mass classification and support design using the Q-system”, Journal of the Geological Society of India, vol. 94, no. 4, pp. 443-443, 2019, doi: 10.1007/s12594-019-1336-0.
• [10] N. Barton, “Some new Q-value correlations to assist in site characterization and tunnel design”, International Journal of Rock Mechanics and Mining Sciences, vol. 39, no. 2, pp. 185-216, 2002, doi: 10.1016/S1365-1609(02)00011-4.
• [11] H. Sonmez and R. Ulusay, “Modifications to the geological strength index (GSI) and their applicability to stability of slopes”, International Journal of Rock Mechanics and Mining Sciences, vol. 36, no. 6, pp. 743-760, 1999, doi: 10.1016/S0148-9062(99)00043-1.
• [12] O. Frough, S.R. Torabi, and S. Yagiz, “Application of RMR for estimating rock-mass-related tbm utilization and performance parameters: A case study”, Rock Mechanics & Rock Engineering, vol. 48, no. 3, pp. 1305-1312, 2015, doi: 10.1007/s00603-014-0619-4.
• [13] P.J. Pells, Z. Bieniawski, S. Hencher, and S.E. Pells, “Rock quality designation (RQD): time to rest in peace”, Canadian Geotechnical Journal, vol. 54, no. 6, pp. 825-834, 2017, doi: 10.1139/cgj-2016-0012.
• [14] H. Ohashi, M. Kimura, and T. Hika, “The investigation of the rock-mass classification for the tunnel in an accretionary zone”, Journal of Tunnel Engineering JSCE, vol. 13, pp. 253-258, 2003, doi: 10.11532/journalte1991.13.253.
• [15] N. Hasegawa, S. Hasegawa, and T. Kitaoka, “Applicability of neural network in rock classification of mountain tunnel”, Materials Transactions, vol. 60, no. 5, pp. 758-764, 2019, doi: 10.2320/matertrans.ZM2019809.
• [16] Y. Nishitsuji and R. Exley, “Elastic impedance based facies classification using support vector machine and deep learning”, Geophysical Prospecting, vol. 67, no. 4, pp. 1040-1054, 2019, doi: 10.1111/1365-2478.12682.
• [17] F. Xinyu, J. Zhixian, B. Xueliang, Y. Tianjun, and L. Yong, “Comprehensive evaluation model of entropy-weighted fuzzy”, Journal of Engineering Geology, vol. 27, no. 6, pp. 1236-1243, 2019, doi: 10.13544/j.cnki.jeg.2018-310.
• [18] R. Gholami, V. Rasouli, and A. Alimoradi, “Improved RMR rock mass classification using artificial intelligence algorithms”, Rock Mechanics and Rock Engineering, vol. 46, no. 5, pp. 1199-1209, 2013, doi: 10.1007/s00603-012-0338-7.
• [19] A. Pękala and F. Puch, “Influence of environmental factors on physical and mechanical characteristics of the opoka-rocks”, Archives of Civil Engineering, vol. 67, no. 4, pp. 337-350, 2021, doi: 10.24425/ace.2021.138503.
• [20] TB 10003-2016 Code for Design on Tunnel of Railway. China Railway Eryuan Engineering Group CO. LTD.
• [21] S.F. Guo, S.W. Qi, and S. Charalampos, “A-BQ, a classification system for anisotropic rock mass based on China National Standard”, Journal of Central South University, vol. 27, no. 10, pp. 3090-3102, 2020, doi: 10.1007/s11771-020-4531-7.