Modeling Microtunnel Boring Machine Penetration Rate Using a Mechanistic Approach
Publication: Journal of Construction Engineering and Management
Volume 148, Issue 11
Abstract
Predicting the productivity of microtunneling construction projects is challenging, due to the complexities of this trenchless excavation method. One of these complexities is estimating the microtunnel boring machine (MTBM) penetration rate due to the complex nature of the interactions between the MTBM and the ground. In the present study, a novel mechanistic approach based on the theory of contact mechanics is proposed to determine the underlying mechanics of the MTBM penetration rate. Using the proposed mechanistic approach, an analytical model of the MTBM penetration rate is developed, and a mechanistic relationship between the MTBM penetration rate and its influential factors, namely soil properties, operational loads, and cutterhead characteristics, is established. The proposed approach is expected to provide substantial mechanistic insight with respect to MTBM penetration rates by (1) modeling penetration rates of MTBMs into soils, (2) identifying the factors that influence penetration rates based on a fundamental theoretical approach, and (3) providing a useful tool for evaluating MTBM penetration rates based on the combined influences of ground properties, operational loads, and cutterhead characteristics.
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Data Availability Statement
All models generated or used during the study are available from the corresponding author upon reasonable request. Case study data used in this research were provided by a third party. Direct requests for these materials may be made to the provider indicated in the Acknowledgements.
Acknowledgments
This project was supported by a Collaborative Research and Development Grant (CRDPJ 532148) from the Natural Sciences and Engineering Council of Canada. The authors would like to thank the Shanghai Construction Group Canada Corp. for their continued support and for providing case study data.
References
ASCE. 2015. Standard design and construction guidelines for microtunneling. ASCE/CI 36-15. Reston, VA: ASCE.
Bamford, W. F. 1984. “Rock test indices are being successfully correlated with tunnel boring machine performance.” In Vol. 2 of Proc., 5th Australian Tunneling Conf., 9–22. Barton, ACT, Australia: Institution of Engineers Australia.
Bruland, A. 1998. “Hard rock tunnel boring.” Ph.D. thesis, Dept. of Civil and Environmental Engineering, Norwegian Univ. of Science and Technology.
De Myttenaere, A., B. Golden, B. Le Grand, and F. Rossi. 2016. “Mean absolute percentage error for regression models.” Neurocomputing 192 (Jun): 38–48. https://doi.org/10.1016/j.neucom.2015.12.114.
Elwakil, E., and M. Hegab. 2018. “Probabilistic estimation for microtunneling projects’ penetration time.” In Proc., ICCREM 2018: Construction Enterprises and Project Management, 27–33. Reston, VA: ASCE. https://doi.org/10.1061/9780784481752.004.
Farmer, I. W., and N. H. Glossop. 1980. “Mechanics of disc cutter penetration.” Int. J. Rock Mech. Min. Sci. & Geomech. Abstr. 17 (6): A123–A124. https://doi.org/10.1016/0148-9062(80)90769-x.
Farrokh, E., J. Rostami, and C. Laughton. 2012. “Study of various models for estimation of penetration rate of hard rock TBMs.” Tunnelling Underground Space Technol. 30 (Jul): 110–123. https://doi.org/10.1016/j.tust.2012.02.012.
Gong, Q., H. Xu, J. Lu, F. Wu, X. Zhou, and L. Yin. 2022. “Rock mass characteristics model for TBM penetration rate prediction—An updated version.” Int. J. Rock Mech. Min. Sci. 149 (Jan): 104993. https://doi.org/10.1016/j.ijrmms.2021.104993.
Gong, Q. M., and J. Zhao. 2009. “Development of a rock mass characteristics model for TBM penetration rate prediction.” Int. J. Rock Mech. Min. Sci. 46 (1): 8–18. https://doi.org/10.1016/j.ijrmms.2008.03.003.
Graham, P. C. 1976. “Rock exploration for machine manufacturers.” In Exploration for rock engineering, edited by Z. T. Bieniawski, 173–180. Rotterdam, Netherlands: A.A. Balkema.
Hassanpour, J., J. Rostami, M. Khamehchiyan, and A. Bruland. 2009. “Developing new equations for TBM performance prediction in carbonate-argillaceous rocks: A case history of Nowsood water conveyance tunnel.” Geomech. Geoeng. 4 (4): 287–297. https://doi.org/10.1080/17486020903174303.
Hassanpour, J., J. Rostami, M. Khamehchiyan, A. Bruland, and H. R. Tavakoli. 2010. “TBM performance analysis in pyroclastic rocks: A case history of Karaj Water Conveyance Tunnel.” Rock Mech. Rock Eng. 43 (4): 427–445. https://doi.org/10.1007/s00603-009-0060-2.
Hegab, M., G. R. Smith, and O. M. Salem. 2006. “Soil penetration modeling in microtunneling projects.” J. Constr. Eng. Manage. 132 (6): 598–605. https://doi.org/10.1061/(ASCE)0733-9364(2006)132:6(598).
Hegab, M. Y. 2005. “Prediction of productivity for microtunneling projects in bidding phase.” In Proc., Construction Research Congress 2005: Broadening Perspectives, 1–10. Reston, VA: ASCE. https://doi.org/10.1061/40754(183)55.
Innaurato, N., R. Mancini, E. Rondena, and A. Zaninetti. 1991. “Forecasting and effective TBM performances in a rapid excavation of a tunnel in Italy.” In Proc., 7th Int. Congress ISRM, 1009–1014. Rotterdam, Netherland: A.A. Balkema. https://doi.org/10.1016/0148-9062(93)92171-L.
Jamshidi, A. 2018. “Prediction of TBM penetration rate from brittleness indexes using multiple regression analysis.” Model. Earth Syst. Environ. 4 (1): 383–394. https://doi.org/10.1007/s40808-018-0432-2.
Johnson, K. L. 1985. Contact mechanics. Cambridge, UK: Cambridge University Press. https://doi.org/10.1002/zamm.19890690713.
Khademi Hamidi, J., K. Shahriar, B. Rezai, and J. Rostami. 2010. “Performance prediction of hard rock TBM using rock mass rating (RMR) system.” Tunnelling Underground Space Technol. 25 (4): 333–345. https://doi.org/10.1016/j.tust.2010.01.008.
Lislerud, A. 1988. “Hard rock tunnel boring: Prognosis and costs.” Tunnelling Underground Space Technol. 3 (1): 9–17. https://doi.org/10.1016/0886-7798(88)90029-6.
Luo, R. Y., and M. Najafi. 2007. “Productivity study of microtunneling pipe installation using simulation.” J. Infrastruct. Syst. 13 (3): 247–260. https://doi.org/10.1061/(ASCE)1076-0342(2007)13:3(247).
Oreste, P., and G. Spagnoli. 2022. “Probabilistic estimation of the advancement rate of the Tunnel Boring Machines on the basis of rock mass characteristics.” Geomech. Geophys. Geo-Energy Geo-Resour. 8 (2): 1–20. https://doi.org/10.1007/s40948-022-00384-4.
Ozdemir, L., R. Miller, and F. D. Wang. 1978. Mechanical tunnel boring, prediction and machine design. Alexandria, VA: National Technical Information Service.
Rostami, J., and L. Ozdemir. 1993. “A new model for performance prediction of hard rock TBMs.” In Proc., Rapid Excavation and Tunneling Conf., 793–809. Reston, VA: ASCE.
Roxborough, F. F., and H. R. Phillips. 1975. “Rock excavation by disc cutter.” Int. J. Rock Mech. Min. Sci. Geomech. Abstr. 12 (12): 361–366. https://doi.org/10.1016/0148-9062(75)90547-1.
Sapigni, M., M. Berti, E. Bethaz, A. Busillo, and G. Cardone. 2002. “TBM performance estimation using rock mass classifications.” Int. J. Rock Mech. Min. Sci. 39 (6): 771–788. https://doi.org/10.1016/S1365-1609(02)00069-2.
Sargent, R. G. 2013. “Verification and validation of simulation models.” J. Simul. 7 (1): 12–24. https://doi.org/10.1057/jos.2012.20.
Snowdon, R. A., M. D. Ryley, and J. Temporal. 1982. “A study of disc cutting in selected British rocks.” Int. J. Rock Mech. Min. Sci. Geomech. Abstr. 19 (3): 107–121. https://doi.org/10.1016/0148-9062(82)91151-2.
Tarkoy, P. J. 1975. “Rock hardness index properties and geotechnical parameters for predicting tunnel boring machine performance.” Ph.D. thesis, Dept. of Civil Engineering, Univ. of Illinois at Urbana–Champaign.
Ueki, M., C. T. Haas, and J. Seo. 1999. “Decision tool for microtunneling method selection.” J. Constr. Eng. Manage. 125 (2): 123–131. https://doi.org/10.1061/(ASCE)0733-9364(1999)125:2(123).
Wang, R., X. Guo, J. Li, J. Wang, L. Jing, Z. Liu, and X. Xu. 2020. “A mechanical method for predicting TBM penetration rates.” Arabian J. Geosci. 13 (335): 1–15. https://doi.org/10.1007/s12517-020-05305-x.
Yagiz, S., and H. Karahan. 2011. “Prediction of hard rock TBM penetration rate using particle swarm optimization.” Int. J. Rock Mech. Min. Sci. 48 (3): 427–433. https://doi.org/10.1016/j.ijrmms.2011.02.013.
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© 2022 American Society of Civil Engineers.
History
Received: Jan 27, 2022
Accepted: Jul 11, 2022
Published online: Sep 14, 2022
Published in print: Nov 1, 2022
Discussion open until: Feb 14, 2023
ASCE Technical Topics:
- Boring
- Construction engineering
- Construction equipment
- Construction methods
- Design (by type)
- Drilling
- Engineering fundamentals
- Equipment and machinery
- Geomechanics
- Geotechnical engineering
- Geotechnical investigation
- Load factors
- Microtunneling
- Penetration tests
- Soil mechanics
- Soil properties
- Structural design
- Tunneling
- Tunnels
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