Universiti Teknologi Malaysia Institutional Repository

Simulation of longitudinal surface settlement due to tunnelling using artificial neural network

Marto, Aminaton and Hajihassani, M. and Kalatehjari, R. and Namazi, E. and Namazi, E. (2012) Simulation of longitudinal surface settlement due to tunnelling using artificial neural network. International Review on Modelling and Simulations, 5 (2). pp. 1024-1031. ISSN 1974-9821 (Print); 1974-983X (Electronic)

Full text not available from this repository.

Official URL: https://www.praiseworthyprize.org/latest_issues/IR...

Abstract

A series of artificial neural networks modelling was conducted to investigate the ground deformation induced by tunnelling along the line 2 of Karaj urban railway, Iran. The tunnels were excavated using New Austrian Tunnelling Method. During excavation, surface settlement was monitored using optical survey points installed on the centre, left and right sides of the tunnel axis. The measured data have been used to establish an artificial neural network model to predict longitudinal surface settlement. This paper focuses on the prediction of ground deformation due to tunnelling using artificial neural networks, particularly longitudinal settlements in relation to the ground condition and tunnelling method. The obtained results demonstrate that artificial neural networks are applicable techniques for predicting longitudinal surface settlement due to tunnelling.

Item Type:Article
Uncontrolled Keywords:Longitudinal Surface Settlement, New Austrian Tunnelling Method
Subjects:T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Civil Engineering
ID Code:33509
Deposited By: Fazli Masari
Deposited On:10 Sep 2013 00:28
Last Modified:28 Jan 2019 03:50

Repository Staff Only: item control page