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Abstract
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Article Information:
A Statistical Model for Prediction TBM Performance using Rock Mass Characteristics in the TBM Driven Alborz Tunnel Project
Hamed Rayat dust, Korosh Shahriar, Kave Ahangari and Hadi Kamali-Bandpey
Corresponding Author: Hadi Kamali-Bandpey
Submitted: March 12, 2012
Accepted: April 03, 2012
Published: December 01, 2012 |
Abstract:
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This study presents an attempt to model the TBM performance with respect to the rock mass
characteristics and site conditions of Alborz Service Tunnel. Alborz Service Tunnel is the longest tunnel (6.4
km and diameter 5.20) along Tehran Shomal Freeway in Iran. Many models and equations have previously been
introduced to estimate penetration rate of TBM based on properties of both rock and machine employing
various statistical analysis techniques. The statistical prediction model is set up by performing multi-linear
regression analysis techniques. In this study evaluate the rock mass characteristics such as UCS, volumetric
joint count (Jv), Joint Spacing (JS) and orientation of discontinuities in rock mass (α) on machine performance
based on the information obtained from field observations and geotechnical site investigations. A comparison
between the measured PR and predicted PR show that the correlation coefficient (R) between the predicted and
measured PR is 0.84 (R = 0.84).
Key words: TBM, penetration rate, regression, , , ,
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Cite this Reference:
Hamed Rayat dust, Korosh Shahriar, Kave Ahangari and Hadi Kamali-Bandpey, . A Statistical Model for Prediction TBM Performance using Rock Mass Characteristics in the TBM Driven Alborz Tunnel Project. Research Journal of Applied Sciences, Engineering and Technology, (23): 5048-5054.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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