Study of the influence of geotechnical parameters

Authors: S R Torabi H Shirazi H Hajali M Monjezi

Publish Date: 2011/10/15

Volume: 6, Issue: 4, Pages: 1215-1227

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Abstract

Alborz twin tunnel along with an exploratory or service tunnel between the two main tunnels are the longest tunnels section in Tehran–Shomal highway with 63 km length The service tunnel is designed to be used for geological investigations ventilation transportation during the construction of main tunnels water drainage ground improvement by grouting and emergency exit An open tunnel boring machine TBM of Wirth Company was used to drive this service tunnel With regard to the fact that in such mechanized tunneling projects performance of the TBMs is of the most importance which affects the economy and timing of the projects on the other hand geotechnical conditions of the region play a significant role in this respect this effect was investigated during this study In this study two main elements of the TBM performance including the rate of penetration and utilization factor were investigated using artificial neural network and Statistical Package for Social Sciences It is shown that geotechnical conditions have considerable effect on the rate of penetration Whereas utilization is largely affected by management and nonrock massrelated parameters including delays wasted times maintenance labor etc With regard to the available data four parameters including uniaxial compressive strength UCS friction angle Poisson’s ratio and cohesion were selected to be studied Based on assessments conducted using these approaches the rate of effectiveness of four selected parameters on penetration rate in a descending order was as follows UCS friction angle Poisson’s ratio and cohesion For increasing utilization it was concluded that minimizing time delays by good management is the most effective way Furthermore with regard to the relative error percentages and the coefficient of correlation of the input and output data it was concluded that the method artificial neural network yields more reliable results than the statistical approach

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