Descriptive statistical analysis of TBM performance at Abu Hamour Tunnel Phase I
- PDF / 2,662,270 Bytes
- 11 Pages / 595.276 x 790.866 pts Page_size
- 84 Downloads / 123 Views
GEOMEAST2017
Descriptive statistical analysis of TBM performance at Abu Hamour Tunnel Phase I J. B. Stypulkowski 1 & F. G. Bernardeau 2 & J. Jakubowski 3 Received: 18 August 2017 / Accepted: 11 April 2018 # The Author(s) 2018
Abstract The Abu Hamour Surface and Ground Water Drainage Tunnel Phase I is a 9.5-km-long, 3.7-m-inside-diameter storm water tunnel about 30 m below ground surface. Integral to phase I of the project are 19 access shafts on the tunnel line. The authors performed a rock mass quality assessment program combining borehole logging, shaft wall mapping, and laboratory testing. The results, including RMR and Q estimates, are presented and their relation to tunnel boring machine (TBM) performance examined. Rock mass properties and TBM operational data and charts are discussed. The paper also presents the results of a regression analysis linking the TBM penetration rate (PR) (mm/min) and field penetration index (FPI) (kN/cutter/mm/rev) with some geotechnical and operational parameters aggregated by strokes. For this purpose, simple, interpretable, and fairly strong general linear regression models were estimated. Then, a predictive neural network regression model was built and evaluated, revealing considerable predictive potential of the data. Keywords EPB TBM . TBM performance . Penetration rate . Field penetration index . Multivariate regression . Neural networks
Introduction Mechanical properties of rock and rock mass largely affect the penetration indices; therefore, they are commonly used in TBM performance evaluation (Yagiz 2008; Hassanpour et al. 2011; Delisio and Zhao 2014; Benato and Oreste 2015). Similarly, RMR, Q, and other rock mass quality ratings contribute to many TBM performance models (Bieniawski et al. 2007; Barton 2000; Hamidi et al. 2010; Hassanpour et al. 2016; Salimi et al. 2017; Maji and Theja 2017). TBM data acquisition systems routinely collect steering and operational parameters for controlling and reporting purposes. Therefore, these data are also available for analyses and
This article is part of the Topical Collection on Geotechnical Engineering for Urban and Major Infrastructure Development * J. Jakubowski [email protected] 1
CDM Smith, Woodbury, NY, USA
2
CDM Smith, Doha, Qatar
3
Department of Geomechanics, Civil Engineering and Geotechnics, AGH University of Science and Technology, Krakow, Poland
empirical TBM performance models based on operational historical data and rock mass characteristics have been studied (Bruland 1998; Rostami et al. 2013; Jain et al. 2014; Maher 2017; Yagiz 2017). TBM performance evaluations, specifically penetration indices, advance rates, and cutter wear, are the features most frequently explained and predicted with the empirical models. Example of different applications of TBM data analysis and modeling can be the evaluation of probabilities of occurrences and quantification of risks, project time, and cost (Grasso and Soldo 2017). Earth pressure balance (EPB) TBM is an effective tunneling technology for a range of rock ma
Data Loading...
