A novel relationship for predicting the point of inflexion value in the surface settlement curve


TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, vol.43, pp.266-275, 2014 (SCI-Expanded) identifier identifier


Thanks to the technological developments in the tunneling and construction sector, the importance of underground structures is growing rapidly. In this sector, it is essential to protect buildings and other structures from the damage which could be caused by tunnel excavation. In this regard, it is important to predict ground behavior during excavation. So, it is necessary to recognize the nature of surface settlement above these types of grounds. The horizontal distance from the tunnel centerline to the point of inflexion on the surface settlement trough is one of the important parameters in surface settlement prediction. Researchers commonly use various empirical relationships for the estimation of the point of inflexion value. These relationships are not precise for calculating these values. Suggesting an accurate and new relationship requires a comprehensive investigation. Therefore, in this study we used both field and detailed numerical modeling approaches to investigate the effects of different parameters on the point of inflexion value. The selected parameters were the following: cohesion, angle of internal friction, tunnel depth, tunnel diameter, Poisson's ratio, Young's modulus, unit weight, face support pressure, and surface surcharge. Four of the largest tunnel construction projects, namely Istanbul, Tehran, Mashhad and Inonu tunnels were chosen. The three-dimensional finite difference code FLAC3D was used to model all conditions. A new relationship was formulated to estimate the point of inflexion value on the surface settlement trough which might be caused by tunneling excavation including not only Tunnel Boring Machine (TBM) but also other excavation type including New Australian Tunneling Method (NATM). The point of inflexion values obtained from the new equation was found to be in good agreement with the actual results from different case studies. (C) 2014 Elsevier Ltd. All rights reserved.