Showing 6 results for تونل مترو
Volume 3, Issue 2 (4-2010)
Abstract
Shear strength characteristics of sand-gravel mixtures in high gravel contents
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Volume 4, Issue 1 (11-2010)
Abstract
One of the major problems in urban subway tunnels is tunnel stability analysis and determination of the safety factor, and the prediction of the settlement that caused to provide stability during the performance, and then at the time utilization structure. The objectives of this study is using different methods to predict and development of these methods by use of each other. In this paper, analyze and evaluate the stability of Tabriz Metro tunnel- Line 1 has been carried out using numerical methods, artificial neural networks and empirical equations. The two excavating methods used in Tabriz Metro tunnel- Line 1 (using machine TBM tunnel method and NATM). In the first part of this research, the excavated zone of the tunnel with NATM method has been analyzed using numerical method and surface settlement and amount of tunnel convergence in the tunnel walls have been predicted by this method. After that, surface settlement has been predicted using artificial neural networks and then it has been compared with obtained value from numerical method analysis and empirical relations. Then, based on these results, empirical relations of convergence - settlement have been modified for Tabriz Metro tunnel- Line 1. In the second part of the research, the TBM penetration rate was predicted by use of neural network which is an important parameter, when one faced with troublesome areas and is very useful to use appropriate pressure EPB for TBM.
, Gholam Lashkaripour, M Akbari,
Volume 5, Issue 2 (4-2012)
Abstract
Tunnel boring machines (TBM) are widely used in excavating urban tunnels. These kinds of machines have different types based on supporting faces and tunnel walls. One type of these machines, is the Earth Pressure Balance (EPB) type that was used in excavating the Line 1 Tunnel of Tabriz Metro. Different parameters such as geological conditions, rock mass properties, dip and machine specifications affect the efficiency of the machine. One method of predicting the efficiency of these machines is to estimate their penetration rates. In this study the value of TBM penetration rates are predicted by an artificial neural network. Predicting of this parameter is so effective for conducting in high risk regions by understanding the time of facing to these regions. The main result of this study is to forecast the penetration rate with an acceptable accuracy and to determine the effective parameters through sensitivity analysis measured by an artificial neural network.
Milad Masomi Aghdam, Mehdi Hosseini,
Volume 12, Issue 5 (12-2018)
Abstract
In the mechanized boring method, the factors affecting ground surface settlement can be mainly divided into five categories: geometric, geomechanic, boring machines working, operating and management parameters. In urban tunnels bored mainly in shallow soil bed, face pressure can be one of the factors preventing ground settlement. The Line A tunnel in Qom metro project is bored with an EPB (Earth Balance Pressure) mechanized boring machine. The effect of face pressure on ground surface settlement was analyzed in the present study according to five sections of the tunnel. These five sections were selected in different kilometers of the tunnel where settlement gauges were installed and the results could be validated. To investigate the effect of face pressure on maximum ground surface settlement, four pressure levels of 100 kPa, 150 kPa, 200 kPa, and 400 kPa were taken into consideration. These were 1, 1.5, 2, and 4 times of the initial face pressure level, respectively. The ground surface settlement was assessed at four pressure levels using the finite element software, PLAXIS 3D TUNNEL. The results were validated using ground-level instrumentation (settlement gauges) on all sections. The validation showed that the modeling results are in good agreement with the results obtained from settlement gauges. Comparison of the results indicated that a 4-fold increase in the face pressure led to a maximum decrease of 4.45 mm in the maximum settlement. Therefore, an increase in the face pressure can reduce settlement, although quite minimally. It was also found that an over-increased face pressure (face pressure over 200kPa) not only did not reduce the maximum ground surface settlement but also may lead to passive failure or uplift of ground surface ahead of the shield.
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Volume 12, Issue 5 (12-2018)
Abstract
In urban areas, it is essential to protect the existing adjacent structures and underground facilities from the damage due to tunneling. In order to minimize the risk, a tunnel engineer needs to be able to make reliable prediction of ground deformations induced by tunneling. Numerous investigations have been conducted in recent years to predict the settlement associated with tunneling; the selection of appropriate method depends on the complexity of the problems. This research intends to develop a method based on Artificial Neural Network (ANN) for the prediction of tunnelling-induced surface settlement. Surface settlements above a tunnel due to tunnel construction are predicted with the help of input variables that have direct physical significance. The data used in running the network models have been obtained from line 2 of Mashhad subway tunnel project. In order to predict the tunnelling-induced surface settlement, a Multi-Layer Perceptron (MLP) analysis is used. A three-layer, feed-forward, back-propagation neural network, with a topology of 7-24-1 was found to be optimum. For optimum ANN architecture, the correlation factor and the minimum of Mean Squared Error are 0.963 and 2.41E-04, respectively. The results showed that an appropriately trained neural network could reliably predict tunnelling-induced surface settlement.
Professor Hamidreza Nassery, Koosha Tamimi, Dr Farshad Alijani, Dr Sadegh Tarigh Azali,
Volume 17, Issue 3 (12-2023)
Abstract
The development of underground transportation activities in cities, such as tunnel boring, may exert short-term or long-term effects on the groundwater and springs of such areas. The construction of the tunnel of Tehran Metro Line 6 (TML6) through alluvium and carbonate rocks of Ali Spring has aroused concern due to the caused fluctuations in discharge and temporary dryness of the spring. The hydrochemical properties of the groundwater and catchment area were investigated to find a connection between the aquifers around the spring and determine the major aquifer feeding it. The estimated volume of water penetrated to the tunnel and the most greatly affected area by the water leakage into the tunnel was determined using analytical methods of water leakage into the tunnel and the DHI method. The statistics for precipitation with the changes in the discharge of the spring before and after the excavation of the metro tunnel were compared to evaluate the changes in the discharge of the spring with the precipitation in the area. The results showed that the metro tunnel excavation has dramatically affected the hydrological system of the area and discharge of the Ali Spring. Moreover, continuing the extraction may produce adverse effects on the discharge of other springs and wells and alter the flow system of the area temporarily or forever.
