Development of Rock Engineering System-Based Models for Tunneling Progress Analysis and Evaluation: Case Study of Tailrace Tunnel of Azad Power Plant Project
Authors: S. Golmohammadi, M. Noorian Bidgoli
Abstract:
Tunneling progress is a key parameter in the blasting method of tunneling. Taking measures to enhance tunneling advance can limit the progress distance without a supporting system, subsequently reducing or eliminating the risk of damage. This paper focuses on modeling tunneling progress using three main groups of parameters (tunneling geometry, blasting pattern, and rock mass specifications) based on the Rock Engineering Systems (RES) methodology. In the proposed models, four main effective parameters on tunneling progress are considered as inputs (RMR, Q-system, Specific charge of blasting, Area), with progress as the output. Data from 86 blasts conducted at the tailrace tunnel in the Azad Dam, western Iran, were used to evaluate the progress value for each blast. The results indicated that, for the 86 blasts, the progress of the estimated model aligns mostly with the measured progress. This paper presents a method for building the interaction matrix (statistical base) of the RES model. Additionally, a comparison was made between the results of the new RES-based model and a Multi-Linear Regression (MLR) analysis model. In the RES-based model, the effective parameters are RMR (35.62%), Q (28.6%), q (specific charge of blasting) (20.35%), and A (15.42%), respectively, whereas for MLR analysis, the main parameters are RMR, Q (system), q, and A. These findings confirm the superior performance of the RES-based model over the other proposed models.
Keywords: Rock Engineering Systems, tunneling progress, Multi Linear Regression, Specific charge of blasting.
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[1] Yagiz, S. and H. Karahan, Prediction of hard rock TBM penetration rate using particle swarm optimization. International Journal of Rock Mechanics and Mining Sciences, 2011. 48(3): p. 427-433.
[2] Yagiz, S., Utilizing rock mass properties for predicting TBM performance in hard rock condition. Tunnelling and Underground Space Technology, 2008. 23(3): p. 326-339.
[3] Yagiz, S., et al., Application of two non-linear prediction tools to the estimation of tunnel boring machine performance. Engineering Applications of Artificial Intelligence, 2009. 22(4-5): p. 808-814.
[4] Grima, M.A., P. Bruines, and P. Verhoef, Modeling tunnel boring machine performance by neuro-fuzzy methods. Tunnelling and underground space technology, 2000. 15(3): p. 259-269.
[5] Okubo, S., K. Fukui, and W. Chen, Expert system for applicability of tunnel boring machines in Japan. Rock Mechanics and Rock Engineering, 2003. 36(4): p. 305-322.
[6] Yagiz, S., J. Rostami, and L. Ozdemir. Recommended rock testing methods for predicting TBM performance: Focus on the CSM and NTNU Models. in ISRM International Symposium-5th Asian Rock Mechanics Symposium. 2008. International Society for Rock Mechanics and Rock Engineering.
[7] Benardos, A. and D. Kaliampakos, Modelling TBM performance with artificial neural networks. Tunnelling and Underground Space Technology, 2004. 19(6): p. 597-605.
[8] Gokceoglu, C. and K. Zorlu, A fuzzy model to predict the uniaxial compressive strength and the modulus of elasticity of a problematic rock. Engineering Applications of Artificial Intelligence, 2004. 17(1): p. 61-72.
[9] Jalalifar, H., et al., Application of the adaptive neuro-fuzzy inference system for prediction of a rock engineering classification system. Computers and Geotechnics, 2011. 38(6): p. 783-790.
[10] Hudson, J., Rock engineering systems. Theory and practice. 1992.
[11] Hudson, J., A review of Rock Engineering Systems (RES) applications over the last 20 years, in Rock Characterisation, Modelling and Engineering Design Methods. 2013, Taylor & Francis. p. 419-424.
[12] Hudson, J. and J. Harrison, A new approach to studying complete rock engineering problems. Quarterly Journal of Engineering Geology and Hydrogeology, 1992. 25(2): p. 93-105.
[13] Skagius, K., M. Wiborgh, and A. Stroem, The use of interaction matrices for identification, structuring and ranking of FEPs in a repository system. Application on the far-field of a deep geological repository for spent fuel. 1995, Swedish Nuclear Fuel and Waste Management Co.
[14] Avila, R. and L. Moberg, A systematic approach to the migration of 137Cs in forest ecosystems using interaction matrices. Journal of environmental radioactivity, 1999. 45(3): p. 271-282.
[15] Velasco, H., et al., Interaction matrices as a first step toward a general model of radionuclide cycling: application to the 137 Cs behavior in a grassland ecosystem. Journal of radioanalytical and nuclear chemistry, 2006. 268(3): p. 503-509.
[16] AgĂĽero, A., et al., Application of the Spanish methodological approach for biosphere assessment to a generic high-level waste disposal site. Science of the total environment, 2008. 403(1-3): p. 34-58.
[17] van Dorp, F., et al., Biosphere modelling for the assessment of radioactive waste repositories; the development of a common basis by the BIOMOVS II reference biospheres working group. Journal of environmental radioactivity, 1999. 42(2-3): p. 225-236.
[18] Mavroulidou, M., S.J. Hughes, and E.E. Hellawell, A qualitative tool combining an interaction matrix and a GIS to map vulnerability to traffic induced air pollution. Journal of Environmental Management, 2004. 70(4): p. 283-289.
[19] Condor, J. and K. Asghari, An alternative theoretical methodology for monitoring the risks of CO2 leakage from wellbores. Energy Procedia, 2009. 1(1): p. 2599-2605.
[20] Benardos, A. and D. Kaliampakos, A methodology for assessing geotechnical hazards for TBM tunnelling—illustrated by the Athens Metro, Greece. International Journal of Rock Mechanics and Mining Sciences, 2004. 41(6): p. 987-999.
[21] Frough, O. and S.R. Torabi, An application of rock engineering systems for estimating TBM downtimes. Engineering Geology, 2013. 157: p. 112-123.
[22] Budetta, P., A. Santo, and F. Vivenzio, Landslide hazard mapping along the coastline of the Cilento region (Italy) by means of a GIS-based parameter rating approach. Geomorphology, 2008. 94(3-4): p. 340-352.
[23] Castaldini, D., et al., An integrated approach for analysing earthquake-induced surface effects: a case study from the Northern Apennines, Italy. Journal of Geodynamics, 1998. 26(2-4): p. 413-441.
[24] Ceryan, N. and S. Ceryan, An application of the interaction matrices method for slope failure susceptibility zoning: Dogankent settlement area (Giresun, NE Turkey). Bulletin of Engineering Geology and the Environment, 2008. 67(3): p. 375-385.
[25] KhaloKakaie, R. and M.Z. Naghadehi, The assessment of rock slope instability along the Khosh-Yeylagh Main Road (Iran) using a systems approach. Environmental earth sciences, 2012. 67(3): p. 665-682.
[26] Mazzoccola, D. and J. Hudson, A comprehensive method of rock mass characterization for indicating natural slope instability. Quarterly Journal of Engineering Geology and Hydrogeology, 1996. 29(1): p. 37-56.
[27] Naghadehi, M.Z., et al., A probabilistic systems methodology to analyze the importance of factors affecting the stability of rock slopes. Engineering Geology, 2011. 118(3-4): p. 82-92.
[28] Rozos, D., et al., An implementation of rock engineering system for ranking the instability potential of natural slopes in Greek territory. An application in Karditsa County. Landslides, 2008. 5(3): p. 261-270.
[29] Shang, Y., H.-D. Park, and Z. Yang, Engineering geological zonation using interaction matrix of geological factors: an example from one section of Sichuan-Tibet Highway. Geosciences Journal, 2005. 9(4): p. 375.
[30] Zhang, L., et al., An application of the rock engineering systems (RES) methodology in rockfall hazard assessment on the Chengdu-Lhasa highway, China. International Journal of Rock Mechanics and Mining Sciences, 2004. 41: p. 833-838.
[31] Shang, Y., et al., Retrospective case example using a comprehensive suitability index (CSI) for siting the Shisan-Ling power station, China. International Journal of Rock Mechanics and Mining Sciences, 2000. 37(5): p. 839-853.
[32] Shin, H.-S., et al., Methodology for quantitative hazard assessment for tunnel collapses based on case histories in Korea. International Journal of Rock Mechanics and Mining Sciences, 2009. 46(6): p. 1072-1087.
[33] Andrieux, P. and J. Hadjigeorgiou, The destressability index methodology for the assessment of the likelihood of success of a large-scale confined destress blast in an underground mine pillar. International journal of rock mechanics and mining sciences, 2008. 45(3): p. 407-421.
[34] Latham, J.-P. and P. Lu, Development of an assessment system for the blastability of rock masses. International Journal of Rock Mechanics and Mining Sciences, 1999. 36(1): p. 41-55.
[35] Faramarzi, F., M.E. Farsangi, and H. Mansouri, An RES-based model for risk assessment and prediction of backbreak in bench blasting. Rock mechanics and rock engineering, 2013. 46(4): p. 877-887.
[36] Faramarzi, F., H. Mansouri, and M.A.E. Farsangi, Development of rock engineering systems-based models for flyrock risk analysis and prediction of flyrock distance in surface blasting. Rock mechanics and rock engineering, 2014. 47(4): p. 1291-1306.
[37] Faramarzi, F., H. Mansouri, and M.E. Farsangi, A rock engineering systems based model to predict rock fragmentation by blasting. International Journal of Rock Mechanics and Mining Sciences, 2013. 60: p. 82-94.
[38] Hudson, J.A. and J.P. Harrison, Engineering rock mechanics: an introduction to the principles. 2000: Elsevier.
[39] Aalianvari, A., M.M. Tehrani, and S. Soltanimohammadi, Application of geostatistical methods to estimation of water flow from upper reservoir of Azad pumped storage power plant. Arabian Journal of Geosciences, 2013. 6(7): p. 2571-2579.
[40] Fattahi, H. (2018). "An estimation of required rotational torque to operate horizontal directional drilling using rock engineering systems." Journal of Petroleum Science and Technology 8(1): 82.
[41] Aghanabati, A., Geology of Iran. 2004: Geological survey of Iran.