One of the main issues involved during tunnel construction with tunnel boring machines is the tail gap grouting. This gap is between the external diameter of tunnel lining and the excavation boundary that is filled with high-pressure grouting materials. In this work, three different approaches of gap grouting modeling in the FLAC3D software are investigated with a special attention to the influence of the grout material hardening process. In the first approach, the grout is modeled as a liquid during injection, and considering the TBM advancement and its hardening time, the grout characteristics are changed to the properties of the solid grouting. In the second approach, the grouting material from the beginning of injection is considered with the properties of solid grouting in the model, and the liquid phase is ignored. In the third approach, without considering the back-filled grouting area in the model geometry, only the injection pressure is applied to the end of the shield and behind the installed segments. The validity of the approaches is evaluated with respect to the maximum ground surface settlement. All the three approaches estimate different surface settlement but the result of the first approach is closer to the monitoring data. Also as a sensitivity analysis, in this work, we investigate the effect of the elastic modulus of liquid and solid grouting materials on the amount of surface settlement that can help to gain a more accurate insight into the effect of grout mixture.

Earth Pressure Balance (EPB) tunnel boring machines are widely utilized for the excavation of subway tunnels. These machines leverage the pressure generated by the excavated materials within the excavation chamber to stabilize the tunnel face. The pressure in the excavation chamber is modulated by varying the speed of the screw conveyor, making the precise control of this rotation speed critically important. Such adjustments facilitate the management of the tunnel face and influence the overall settlement of the tunnel structure. This study models the tunnel excavation of Tabriz Metro Line 2, employing an EPB shield that operates under earth pressure conditions. The excavated material is accumulated in a chamber located behind the cutter-head, which generates the requisite pressure at the work face. This pressure is regulated through the screw conveyor mechanism. The simulation was conducted using a three-dimensional particle flow code based on the discrete element method. The findings indicate that when the pressure at the face is decreased to 50% of the maximum pressure exerted by the horizontal jacks of the shield drive, significant and hazardous ground surface settlements occur. Conversely, at elevated pressures, a consistent settlement of 1.9 cm was recorded. Additionally, a reduction in the cutter-head rotation speed from 2 rpm resulted in a decline of the work face, while an increase in speed corresponded with the same 1.9 cm settlement. The discrete element method effectively models the drilling process. The validity of the modeling outcomes was corroborated by data acquired from instrumentation.

The operation parameters of EPB-TBM have always been significant factors in tunnel constructions. So it is crucial to estimate the cutterhead torque and thrust force of the machine. In this study, by employing the multilayer perceptron artificial neural network (ANN-MLP) and multivariate regression (MVR) methods, the empirical models were developed to estimate the EPB operating parameters, including cutterhead torque and thrust force, in the rock section of the Tehran metro line 6, South extension (TML6-SE) project. In this section, the excavation was performed in a strong, blocky to massive rock. The machine was equipped with the disc cutters on the cutterhead as a cutting tool instead of rippers and drag bits. The mechanized excavation in this situation is unusual with using the EPB machines. The input data included the performance parameters such as penetration rate, earth pressure, cutterhead rotation speed, and cutter load. The statistical indices were used to verify the developed models. The results confirmed the accuracy of the models. The MAE loss function determined for torque in both training and testing stages predicted by the ANN was 0.0001 and 0.005, respectively. The MAE loss function determined for thrust force in both training and testing stages predicted by the ANN was 0.00016 and 0.010, respectively. The relationships between parameters in the dataset were investigated to obtain and offer new equations using the multivariable regression statistical method (MVR). The MAE loss function determined for cutterhead torque and thrust force was 0.0018 and 0.0010, respectively.

The total number of EPB-TBMs that were utilized for tunneling between 2005 and 2010 is approximately 350 units worldwide. One of the most critical adverse conditions is encountering abrasive soils and excessive wear on the cutting tools and the cutter head as has been reported in many EPB tunneling projects worldwide. In this project, the number of cutting tools replaced were 1169, including 654 rippers, 357 scrapers and 153 disc cutters. In this paper the influence of geological parameters and operational factors on tool wear is studied. The objective of the current study was to investigate tool wear on EPB machines through a case study and field measurements. This refers to assessment of the fundamental reasons for increases of TBM tool wear in certain ground conditions to find a correlation between geological conditions and operational parameters with cutter life in soft ground tunneling. This paper introduces the subject tunnel project in this case study, describes the Cutter life parameters as observed in this project and presents results from TBM operation’s and soil properties and their influence on tool wear. The results of this study show that by increasing TBM thrust, earth pressure and torque, the cutter consumption generally increases. Also, soil conditioning plays an important role in controlling cutter wear, so that the tool wear can be reduced even in coarse-grained soils by improving the soil conditioning parameters.

Before underground excavation, appropriate information is available to determine construction requirements and maintenance systems. However, this sort of information is not enough and the excavation is likely to encounter unpredictable damage. Resulted damage may inflict irreparable losses on installation and residential zones, in addition to disturbances in the exploitation systems. So, examining different parts and, specifically, controlling states of stress and deformation will considerably prevent disasters. Different methods of determining face pressure are evaluated. Plaxis-3D software is applied to measure the face pressure and the resulted settlement and heave on the ground surface are discussed in this paper. For this purpose, the Esfahan subway information is used as a case study.

One of the most critical problems of mechanized tunnelling is the abrasion of cutting tools. Soil abrasivity significantly reduces drilling efficiency and increases the operating costs of urban tunnels. There are extensive studies on abrasivity of rocks. However, limited studies have been performed on the influence of soil particle size distribution on tunnelling machine cutting tools. Despite the wide range of methods and devices for measuring soil abrasivity, so far, no standard and comprehensive method for measuring soil abrasivity have been presented. In this study, considering the effect of some effective parameters on the abrasion of cutting tools, a new laboratory machine to determine soil abrasivity was constructed. Then, using 8 different types of soil granulation, the effect of soil particle size distribution and density on cutting tool abrasion was studied. Also, using the Talbot curve, the abrasion values ​​of cutting tools in different particle sizes were compared. The results showed that the highest values ​​of cutting tools abrasion occur in soils with particle sizes according to the Talbot equation. As the soil granulation curve moves away from the Talbot curve, abrasivity decreases. Also, the maximum abrasion of cutting tools occurs in the amount of fine aggregate of 10% with an average abrasion percentage of 27.3%. By reducing the fine aggregate to values lower than 10%, the soil structure is disturbed and as a result, the average abrasion percentage of cutting tools decreases from 27.3% in soil with 10% fine aggregate to 2.37% in soil without fine aggregate. Also, by increasing soil density from 1.6 to 1.8, the average abrasion percentage of cutting tools increases from 8.1% to 31.4%.

1-Introdoction Occurrence of settlements associated with damaging adjacent structures is a dangerous phenomena due to tunnel excavation in the urban area. It may cause some dangers to the neighbors. Artificial intelligence as a new method applies to examine the relationship between different parameters and their impact on the geotechnical hazards incidents probability and severity. The amount of the settlement in EPB mechanized tunneling depends on several factors including 1) geological conditions and groundwater level, 2) tunnel characteristics (depth and diameter) and 3) drilling parameters (penetration rate, face pressure, back-fill grouting pressure, pitching angle of the machine). Due to the complexity of the settlement process in mechanized tunneling and the impossibility of using all of the useful parameters, the use of classical models such as regression and numerical methods is not efficient and has many problems (Suwansawat and Einstein, 2006). Therefore, the using of artificial intelligence models such as artificial neural networks and fuzzy methods frequently has been used to predict maximum settlement (Kim et al., 2001; Suwansawat and Einstein, 2006; Ocak and Seker, 2013; Show Fang et al., 2014; Moeinossadat et al., 2016; Nadiri et al., 2018). Artificial neural networks save time and decrease cost in modelling process. The analysis is based on artificial intelligence models by extracting the relationships between the factors affecting the settlement, such as tunnel depth and diameter, soil properties, and machine operation parameters. These models have been used to predict ground surface settlement in a number of tunneling projects. (Inanlou and Ahanghari, 2010; Rezazadeh Anbarani et al., 2013; Jafari et al., 2013; Santos and Celestino, 2008; Ocak and Seker, 2013; Dindarloo and Siami Irdemoosa, 2015; Mohammadi et al., 2015; Camos et al., 2016; Bouayad and Emeriault, 2017). In this research, in addition to solving previous research problems, a model is proposed that its results can be generalized to the other projects all over the world. The study area was selected as part of the Tabriz metro line 1, between the Qunqa and Gazran stations, which has suitable conditions in viewpoints of geological characteristics and tunnel specification that is very common and similar to other projects in this field. A fuzzy modeling method has been used to predict a maximum settlement in the study area, and its results are compared with the results of artificial neural networks which is used in previous studies. Also, considering the ability of each model, the combination of these models can take advantage of the simultaneous benefits of both models (Nadiri et al., 2013, 2014, 2015, 2018). So in this research, the Neuro-fuzzy model is used to combine individual artificial intelligence models to use the benefits of both models simultaneously...

Determination of the optimum soil conditioning parameters in the earth pressure balance-tunnel boring machines (EPB-TBMs) plays an important role in reaching an optimum thrust force and advance speed. Silty-clay (CL-ML) in line 1 of the Ahwaz metro project is used in order to find the conditioning parameters of slumps with different water contents and foam agents. The results obtained are a quantitative comparison between the parameters with different soil conditioning and water contents. Hence, the test results can be used to determine the most economical and technical conditioning parameters for a special condition of soil. The optimum quantity of foam expansion ratio (FER), foam injection ratio (FIR), percent ratio between the surfactant agent and the water volume (Cf), and cost for foam in this soil (based on the soil conditioning production cost) are 10, 157%, 2. 07, 248 units, respectively. Soil conditioning with the optimum parameters obtained are tested in a TBM in two stages during excavation of 140 rings. This results in a lower soil conditioning cost and almost 40% higher advance speed.