ABSTRACT:

Soft ground is a non-linear material with time-dependent characteristics. It causes major problems of supporting both during construction and during the operational life of an underground excavation due to swelling and squeezing phenomenon. Therefore, it is worth monitoring the swelling and squeezing behavior of soft grounds in underground excavations. Compensation method is one of the most famous methods for determining the in-situ pressure of such ground on support systems. The study presented herein aims to predict the variant stress of concrete lining due to time dependent pressure of soft rock based on the closure of pine distances before and after making the slots in compensation method. In order to establish predictive models, statistical and soft computing techniques such as multiple regression approach (MRA), artificial neural network (ANN) and adaptive network fuzzy inference system (ANFIS) were used, and prediction performances were then analyzed.

1 INTRODUCTION

Tunneling through soft rocks often encounters a gradual change in tunnel wall displacement or rock pressure during and after excavation. If structures like lining are installed in the tunnel, displacement will cause a pressure behind the structure. This timedependent phenomenon results mainly from two basic factors, swelling and squeezing. According to Barla (1995), squeezing is the time dependent large deformation of a rock mass, which occurs around a tunnel, and is essentially associated with creep caused by exceeding a limiting shear stress. He proposes that 'Deformation may terminate during construction or continue over a long time period (Dalgic, 2002). Swelling is a combination of physico-chemical reactions involving water and stress relief (ISRM, 1983). In argillaceous rocks (i.e. mudstone, shale, etc), swelling is caused by one or a combination of three mechanisms: mechanical, osmotic and intracrystalline (Einstein, 1996). Such time dependent behavior of rock masses causes considerable damage to the structures constructed in them.

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