Rock Mechanics
Alireza Afradi; Arash Ebrahimabadi; Mansour Hedayatzadeh
Abstract
Tunnel Boring Machines (TBMs) are extensively used to excavate underground spaces in civil and tunneling projects. An accurate evaluation of their penetration rate is the key factor for the TBM performance prediction. In this study, artificial intelligence methods are used to predict the TBM penetration ...
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Tunnel Boring Machines (TBMs) are extensively used to excavate underground spaces in civil and tunneling projects. An accurate evaluation of their penetration rate is the key factor for the TBM performance prediction. In this study, artificial intelligence methods are used to predict the TBM penetration rate in excavation operations in the Kerman tunnel and the Gavoshan water conveyance tunnels. The aim of this paper is to show the application of the Multivariate Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) for the TBM penetration rate prediction. The penetration rate parameter is considered as a dependent variable, and the Rock Quality Designation (RQD), Brazilian Tensile Strength (BTS), Uniaxial Compressive Strength (UCS), Density (D), Joint Angle (JA), Joint Spacing (JS), and Poisson's Ratio are considered as independent variables. The obtained results by the several proposed methods indicated a high accuracy between the predicted and measured penetration rates, but the support vector machine yields more precise and realistic outcomes.
Exploitation
H.R. Nezarat; Seyed M. E. Jalali; M. Nazari
Abstract
Knowledge of the airflow distribution inside a Tunnel Boring Machine (TBM) can create a safe working environment for workers and machinery. The airflow quality and the related mass flow rate in the ventilation system should be sufficient to dilute gases and remove dust inside the tunnel. In this work, ...
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Knowledge of the airflow distribution inside a Tunnel Boring Machine (TBM) can create a safe working environment for workers and machinery. The airflow quality and the related mass flow rate in the ventilation system should be sufficient to dilute gases and remove dust inside the tunnel. In this work, airflow distribution in the single shield TBM tunnel was studied using computational fluid dynamics. The finite volume-based finite element method was used in the simulation based on the 3D complex geometry of TBM. In order to validate the numerical results, the air velocity inside the Chamshir tunnel was measured experimentally at different sections. With a length of 7050 m and a final diameter of 4.6 m, the Chamshir water transport tunnel is located in the south of Iran. The results obtained show that there is not enough airflow in 59.6% of the TBM space in the current working conditions. In other words, there are many dead zones from the control cabin to the end of gantry 6 in the backup system. Several applicable scenarios were studied to remove the dead zone area and optimize the airflow velocity by employing high capacity jet fan in the ventilation system. The results show that the dead zone volume can be decreased by about 5.21% by increasing the airflow rate of the jet fan.
Rock Mechanics
Seyed S. Mousavi; M. Nikkhah; Sh. Zare
Abstract
In this work, we tried to automatically optimize the cost of the concrete segmental lining used as a support system in the case study of Mashhad Urban Railway Line 2 located in NE Iran. Two meta-heuristic optimization methods including particle swarm optimization (PSO) and imperialist competitive algorithm ...
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In this work, we tried to automatically optimize the cost of the concrete segmental lining used as a support system in the case study of Mashhad Urban Railway Line 2 located in NE Iran. Two meta-heuristic optimization methods including particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) were presented. The penalty function was used for unfeasible solutions, and the segmental lining structure was defined by nine design variables: the geometrical parameters of the lining cross-section, the reinforced feature parameters, and the dowel feature parameters used among the joints to connect the segment pieces. Furthermore, the design constrains were implemented in accordance with the American Concrete Institute code (ACI318M-08) and guidelines of lining design proposed by the International Tunnel Association (ITA). The objective function consisted of the total cost of structure preparation and implementation. Consequently, the optimum design of the system was analyzed using the PSO and ICA algorithms. The results obtained showed that the objective function of the support system by the PSO and ICA algorithms reduced 12.6% and 14% per meter, respectively.
Exploitation
S. Moosazadeh; H. Aghababaie; Seyed H. Hoseinie; B. Ghodrati
Abstract
Utilization is one of the main managerial factors that is applied for construction process analysis well. It directly affects the project duration and construction costs. Therefore, a utilization study in tunneling projects is essential. In this work, the utilization of an earth pressure balance Tunnel ...
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Utilization is one of the main managerial factors that is applied for construction process analysis well. It directly affects the project duration and construction costs. Therefore, a utilization study in tunneling projects is essential. In this work, the utilization of an earth pressure balance Tunnel Boring Machine (TBM) in Tabriz urban railway project was studied using the Monte Carlo simulation approach. For this purpose, the unit operation during one working shift such as boring time, ring building time, and locomotive travel time was recorded and saved in data base. In addition, the general down times such as TBM and back-up system maintenance, surface and tunnel logistic maintenance, cutting tools’ replacement, and locomotive delay times were recorded and considered in simulation. The results of this work show that the mean simulated project duration time of case study TBM is approximately 859 shifts and close to the real data with a difference of 0.92%. Finally, the average estimated utilization factor was found to be approximately 14%.
