Tunnel Boring Research Articles

Research on Mechanical Characteristics of TBM Cutter Bearing Based on DEM-MBD Coupled Simulation

Introduction: The cutter is a crucial excavation tool employed by Tunnel Boring Machines (TBM) for tunneling underground passages. During operation, it undergoes intense impact loads, which are transmitted to the bearings, thus posing a risk of bearing failure. Method: This paper combines the Discrete Element Method (DEM) and Multibody Dynamics (MBD) by establishing a coupled simulation patent model of the cutter and surrounding rock, various methods of cutter load profiles are compared. The study investigates the variation patterns of multi-directional rock-breaking loads on the cutter and validates the findings through wire-cutting experiments. Result: The research findings indicate that the discrepancies between the simulated and experimental mean values of the cutter's normal force and rolling force are 6.26% and 35.20%, respectively. The efficiency of cutter load transmission to the outer ring of the bearing is 99.10%, leading to the characterization of the vibration characteristics curve of the bearing's outer ring. Simultaneously, the mean square error of the cutter load obtained through the coupled method and traditional method is 78.50 kN and 76.10 kN, respectively. In comparison, the experimental load's mean square error is 99.20 kN, indicating that the coupled method better aligns with actual conditions. Conclusion: This research approach serves as a reference for TBM cutter performance analysis and bearing fatigue analysis.

Enhancement Seismic Response of a Bored Tunnel Using Isolation for the Challenge of a Faulted Rock Crossing

The tunnel boring method (TBM) is a widely used and effective tunneling technology in various rock mass quality circumstances. A “faulted rock mass” can range from a highly fractured rock mass to a sheared weak rock mass, making the ground conditions challenging for tunneling, especially for TBMs. “Faulted rock” significantly affects hard rock TBMs, primarily due to the TBM’s high geological risk and poor flexibility. TBMs require careful planning and preparation, starting with preliminary assessments. This study investigates the impact of establishing an isolation material between a circular tunnel and the adjacent faulting rock on seismic response. The two parts of the parametric analysis for the isolation material utilized in the model look at how changes in the mechanical characteristics of the material, such as the shear modulus of the rock and the fault, affect the stresses created in the tunnel. The second section examines how changes in the isolation width concerning the fault width affect the stresses and displacements produced in the tunnel. Additionally, the effectiveness of isolating the tunnel during sudden changes in the characteristics of the rock was investigated under seismic loading perpendicular to the tunnel and parallel to the tunnel. The finite element approach was utilized to model the TBM tunnel and the neighboring rock with a fault or sudden change in the rock using Midas/GTS-NX, simulating the interactions between the rock and the tunnel. Time-history analysis using the El Centro earthquake was conducted to calculate the stresses in the tunnels during seismic events. Peak ground accelerations between 0.10 g and 0.30 g were utilized for excitation. A time step of 0.02 s and a length of 10 s for the seismic event were used in the analysis, with traditional grout pea gravel vs. the isolation layer. Comparisons were made between the absolute stresses (the greatest possible values) in the normal tunnel section (Sxx) and those induced in the tunnel with traditional grout and with isolation. Furthermore, the study of vertical displacement was taken into consideration. The seismic isolation method is highly effective in improving the seismic safety of bored tunnels. The results show that the significant values of the ratio between the shear modulus of isolation and the surrounding soil should be between 0.2% and 0.4%. Where parts of the tunnel run through a fault, the effective length of isolation should be between one and two times the fault width. The dynamic behavior of the tunnel with isolation is better than that with traditional grout. Generally, when isolation is used for any length, it reduces the stresses at the area of sudden change. Consequently, engineering assessments from both structural and geotechnical engineering viewpoints are now required for these unique constructions. An underground structure’s safety should be evaluated by the designer to ensure that it can sustain various applied loads, taking into account seismic loads in addition to construction and permanent static loads. Tunnels may be especially vulnerable in areas where the composition of the soil or rock varies.

Energy-driven TBM health status estimation with a hybrid deep learning approach

This study provides a hybrid deep learning approach that enables the researchers to estimate the Tunnel Boring Machine (TBM) health status during excavation process using energy consumption data. By analyzing the energy forms and paths in the tunneling process, the key energy factors' consumption performance behavior affecting TBM safety is identified. The Ensemble Empirical Mode Decomposition (EEMD) method and a Convolution neural network-Long short term memory-Depth Neural Network (CNN-LSTM-DNN, CLDNN) model are integrated for Health Performance Parameter (HPP) prediction. A classification method is constructed by the Generative Adversarial Imputation Networks (GAIN) model for health status estimation. The SHapley Additive exPlanations (SHAP) method is performed to quantify the relationships between energy consumption and system health status. A tunneling case in Singapore is used to test the effectiveness of the developed methodology. It is found that (1) the proposed method provides TBM cutter wear and cooling oil prediction with a R-square (R2) of 0.8591 and 0.8727, respectively, and (2) classification results indicate that the estimation F1-score of 0.9863 can be achieved based on health status evaluation indicator (HSEI). The novelty of the proposed approach lies in its capabilities of (1) fully extracting and utilizing the energy consumption information in every regard to predict TBM health performance; (2) providing a good one-step-ahead health status estimation for the TBM excavation process. Therefore, this study proposes a feasible direction for the application of energy consumption data in TBM health status estimation.

A Novel Identification Approach Using RFECV–Optuna–XGBoost for Assessing Surrounding Rock Grade of Tunnel Boring Machine Based on Tunneling Parameters

In order to solve the problem of the poor adaptability of the TBM digging process to changes in geological conditions, a new TBM digging model is proposed. An ensemble learning prediction model based on XGBoost, combined with Optuna for hyperparameter optimization, enables the real-time identification of surrounding rock grades. Firstly, an original dataset was established based on the TBM tunneling parameters under different surrounding rock grades based on the KS tunnel. Subsequently, the RF–RFECV was employed for feature selection and six features were selected as the optimal feature subset according to the importance measure of random forest features and used to construct the XGBoost identification model. Furthermore, the Optuna framework was utilized to optimize the hyperparameters of XGBoost and validated by applying the established TBM dataset of the KS Tunnel. In order to verify the applicability and efficiency of the proposed model in surrounding rock grade identification, the prediction results of five commonly used machine learning models, Optuna–XGBoost, Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Decision Tree (DT), XGBoost, and PSO–XGBoost, were compared and analyzed. The main conclusions are as follows: the feature selection method based on RF–RFECV improved the accuracy by 8.26%. Among the optimal feature subset, T was the most essential feature for the model’s input, while PR was the least important. The Optuna–XGBoost model proposed in this paper had higher accuracy (0.9833), precision (0.9803), recall (0.9813), and F1 score (0.9807) than other models and could be used as an effective means for the lithological identification of surrounding rock grade.

Construction Mechanical Characteristics of TBM Pilot and Enlargement Method for Ventilation Tunnel of Wuhai Pumped Storage Power Station

Investigating the construction mechanics of a ventilation tunnel using the TBM (Tunnel Boring Machine) pilot and enlargement method with reliable rock mechanics parameters ensures the safety of on-site excavation operations. Leveraging the construction project of the ventilation tunnel at the Wuhai Pumped Storage Power Station, TGP sidewall forecasting was employed to explore the geological conditions within a 50 m range of the tunnel’s side. A systematic study of the construction mechanics of the TBM pilot and enlargement method was conducted, along with corresponding construction recommendations and engineering applications. This research indicates that sidewall forecasting can supplement the deficiencies in geological exploration reports, with excavation revealing conditions consistent with the forecast. Deformation at the interface, including the arch crown and sidewall, mainly concentrates during the construction phase from the completion of full-section excavation to the beginning of expansion. As the working face advances, the upper rock mass within the ventilation tunnel outline experiences tension, with stress concentration in the shoulder and bottom corner rock masses. The plastic zone before expansion primarily concentrates within the ventilation tunnel outline, shifting to the sidewall after expansion, with the left shoulder’s plastic zone depth slightly exceeding that of the right. The proposed method effectively ensures construction safety, and the research findings have valuable implications for similar projects.

The Effect of Seismic Load on TBM Structures for Metro Line 3 in Hanoi, Vietnam

Metro line 3 in Hanoi is being constructed using tunnels, which may affect nearby constructions. In addition, Hanoi’s earthquakes also pose risks to this Tunnel Boring Machine (TBM) line. This paper studies the impact of TBM construction on the surrounding houses along the line, as well as the impact of earthquakes on this line. A 3D numerical model was developed to simulate the static and dynamic behavior of TBM at station 9 in Metro Line 3. The results show that the maximum settlement at the ground surface under seismic load is significantly reduced from 4.6 mm to 0.1 mm when using the jet grouting method.

Numerical Simulation Study on the Mechanical Properties of the Surrounding Rock in Tunnel Boring Machine Inclined Shaft

Numerical Simulation Study on the Mechanical Properties of the Surrounding Rock in Tunnel Boring Machine Inclined Shaft

대심도 Shield TBM 터널의 IoT 스마트 안전관리시스템 구축에 관한 연구

The purpose of this study is to establish a smart safety management system during deep-seated Shield TBM(Tunnel Boring Machine)tunnel construction. During this work, the site is continuously managed and controlled audio-visually to identify and discover unexpected situations in advance. This study aims to contribute to preventing accidents during TBM (Tunnel Boring Machine) construction while performing efficient work by responding accurately. The system is composed of turn gates and vascular recognizers that can control workers'access, smart tags for tracking workers' location in real-time, emergency call systems, Workers motion sensor to detecting workers who are not moving, monitoring through CCTV cameras, PTZ (Pan Tilt Zoom), DOME, sensing systems detecting four major gases (02, CO, H2S, CH4) that can cause serious accident, loudspeakers, amplifiers, and two-way interphones, etc.
 As a result of this study, the IoT Smart Safety Management System for the Shield TBM Tunnel Construction in the deep underground construction site has been materialized to establish the Safety Management Control Center, safety management system for TBM Construction Machinery, tunnel internal safety management system, network system, and can make immediate response in case of emergency. This system can guarantee safety of workers who provide labor within the poor working environment of deep underground spaces. The IoT-based smart safety management system established in this study is expected to contribute a IoT to preventing industrial accidents at the site of underground deep-seated TBM tunnel construction (earth pressure type and Slurry shield TBM or Open TBM) over 40m in the future.

Carbon Footprint Evaluation in Tunnels Excavated in Rock Using Tunnel Boring Machine (TBM)

The generation of CO2 is an important element in assessing the environmental impact generated in a tunnel construction project, making this knowledge very useful for evaluating different alternatives. In this study, an analysis of the carbon footprint has been carried out, including the main elements during the construction phase of a tunnel employing a tunnel boring machine (TBM). The research proposes several options for an easy and quick calculation of CO2 generation in a design phase. Its determination can be crucial for decision-making before and during the execution of any tunnel in the near future. The estimation models have been validated based on real case studies, defining the carbon footprint of each construction element. The proposed procedure can apply to any tunnel. However, it should be noted that it is an approximate analysis, and the limitations described in each section should be considered. The main CO2 generator found in the construction process is the lining element; the percentage varies between 50% in tunnels with smaller diameters (4–5 m) and 75% for tunnels with larger diameters (9–10 m), followed by the auxiliary elements, 16%, and the operation of the tunnel boring machine itself, 11.2%, while the other parts remain in a range between 1.3 and 5.7%. This knowledge makes it possible to define the aspects on which efforts should be focussed to reduce the carbon footprint of the tunnel construction process.

Predicting advance rate and cutter life in TBM tunnelling using evolutionary algorithm

ABSTRACT Tunnelling with a Tunnel Boring Machine (TBM) offers several advantages over conventional tunnelling methods when covering long distances, particularly regarding time, safety, and environmental impact. Prior to starting a TBM project, performance analysis is a crucial stage necessary to inform the initial investment decision and project cost estimation. However, this analysis requires extensive fieldwork and laboratory studies. The Advance Rate (AR), calculated from the Utilization Factor (U) – the ratio of excavation time to total project time – is a widely accepted measure of TBM performance. Total project time encompasses various parameters, including boring time, cutter inspection and replacement times, and constant factors like re-gripping, service, and maintenance times. In this study, we employed analytical methods, statistical analysis, and genetic programming approaches to evaluate the AR and thus enhance TBM performance analysis. Gamma tests were conducted to identify interrelated parameters in TBM operations. The results from these tests showed that the Applied Force per Cutter (FN) and penetration values (together forming the Field Penetration Index or FPI) are useful in estimating cutter consumption. While FN can be determined through laboratory tests, its field determination is challenging. We have developed several charts and a function derived from genetic programming to estimate the AR of a TBM. The study demonstrated that this function, formulated using genetic programming, possesses strong predictive capability and can significantly improve TBM performance analysis.

Structural Optimization of the Main Bearing in a Tunnel Boring Machine Considering Clearance

Abstract An optimal design method for the main bearing of a tunnel boring machine is proposed. In this method, the fatigue life is used as the objective function. Structural parameters, including clearance, are considered as design variables. First, a quasi-static model of the main bearing and a calculation model of the fatigue life are established. The correctness of the theoretical method is verified by comparing it with the calculation results of the finite element method. Next, the influence of clearance on the load-carrying performance under external loads is analyzed. There is an optimal negative clearance for the axial loaded and radial rows. With the increase in the external loads, the optimal negative clearance gradually decreases. The variation laws of the load-carrying performance for the axial loaded and supporting rows affected by axial clearance mainly depend on the bias load degree of the main bearing. Finally, based on the optimal design model of the main bearing, the optimal internal structure is obtained using the genetic algorithm. The optimized fatigue life is improved by 92.2%. The load-carrying performance of the optimal main bearing has also been significantly enhanced compared to the initial design. Therefore, the proposed optimization method provides a practical approach to the main bearing design.

Study on the friction and wear performance of laser cladding WC-TiC/Ni60 coating on the working face of shield bobbing cutter

In order to solve the problem of shield hobbing cutter failure due to bias wear and chipping during tunnel boring, TiC-WC/Ni60 coating was prepared on the surface of H13 steel to improve the wear resistance of shield hobbing cutter. In this paper, four kinds of WC-TiC/Ni60 composite coatings with different content ratios of 5 wt% TiC+25 wt% WC, 10 wt% TiC+20 wt% WC, 15 wt% TiC+15 wt% WC and 20 wt% TiC+10 wt% WC were prepared on the surface of H13 steel by using the coaxial powder-feeding laser cladding equipment. The micromorphology, phase, hardness and friction and wear properties were fully studied. The results show that cross-sectional organization of the fused cladding layer mainly consists of columnar crystals, cytocrystals and equiaxial crystals; the hard phases in the fused cladding layer mainly consist of TiWC2, Cr4Ni5W, and Cr3C2, and so on; The microhardness of the cross-section of the fused cladding layer shows a trend of decreasing at first, then increasing and finally decreasing, and the highest hardness of the fused cladding layer occurs at the subsurface of the fused cladding layer; the friction coefficient of the fused cladding layer shows a trend of decreasing first and then increasing; the wear volume of the fused cladding layer is significantly lower than that of the substrate, and the wear volume of the 15 wt% TiC coating is the smallest of 1.313 mm3, which is 86.9 % lower than that of the substrate; the wear mechanism of the substrate is mainly abrasive wear and adhesive wear, and the wear mechanism of the fused cladding layer is mainly brittle spalling, abrasive wear and oxidative wear. The analysis of the experimental results shows that the surface properties of the coating are best when both TiC and WC contents are 15 wt%.

Tree-Based Solution Frameworks for Predicting Tunnel Boring Machine Performance Using Rock Mass and Material Properties

Tree-Based Solution Frameworks for Predicting Tunnel Boring Machine Performance Using Rock Mass and Material Properties

LABORATORY INVESTIGATION OF THE EFFECT OF SODIUM SILICATE AND BENTONITE ON THE MECHANICAL PROPERTIES OF THE GROUT BEHIND THE SEGMENT IN MECHANIZED EXCAVATION

Nowadays, the use of Tunnel Boring Machines (TBM) in tunnelling has increased in urban environments. One of the effective parameters in the excavation process is the use of grout behind the segments to prevent ground settlement and penetration into the tunnel. The investigation of the effects of two-component grout (bentonite and sodium silicate) on the mechanical properties of the grout plays a crucial role in mechanized excavation. Therefore, this article aims to investigate the effect of various parameters on the properties of the two-component grout. Eight different mixing designs were considered in this research. Gel-time tests, viscosity test, water bleeding test, uniaxial compressive strength tests (UCS), and direct shear tests were conducted for each mixing design. The UCS tests were performed for eight mixing designs and at four different ages of the grout, while the direct shear test was conducted for five mixing designs at the age of one day. The results showed that increasing the sodium silicate content from 4% to 9.4% reduced the Gel-time to 7 seconds, and increasing the bentonite content from 2.3% to 4.58%, increased the marsh funnel time to 12 seconds. The uniaxial compressive strength of the grout increased to 0.682 MPa at the age of 28 days. Finally, by conducting the direct shear test on the grout and obtaining the parameters of cohesion and internal friction angle, it was determined that these two parameters depend on the values of bentonite and sodium silicate, and they change with the increase or decrease of these grout components.

Research on Key Technology of Mechanical Construction of Connecting Passages

Conventional connecting passages construction usually uses mining method with freezing or grouting method of reinforcement, generally has a long construction period, high construction risk, costly problems, which has an urgent need for a mechanical way of construction technology to improve the speed and quality of construction. The critical technologies for the mechanical construction of connecting passages mainly include the design of the main tunnel and the connecting-passage segment, TBM fully enclosed launching and receiving, the waterproof design, and the design of the built-in pump chamber of the TBM. Its construction process mainly includes TBM assembly, sleeve installation, breaking of the tunnel door, the tunnel boring, the machine receiving, and the fabrication of the tunnel door seal. Based on the above vital technologies analysis, this paper demonstrates the significant advantages of the mechanical construction of the connecting passage with practical construction cases, which provides an essential reference for the subsequent research.

Comprehensive analysis of oversized cargo transportation market in Poland (2001-2022): Trends, regulations, and industry dynamics

The oversized cargo transportation market in Poland actively participates in developing the economy, providing services necessary for implementing large infrastructure and industrial projects on a national and European scale. Development and functioning of this sector in the EU and globally requires overcoming many organisational, technical and administrative barriers and difficulties, and the authors of several publications indicate how these services are developing. The current study contains a detailed analysis of data from 2001-2022. The paper characterises the changes in particular years, indicating the main causes of the occurring processes, and defines the existing trends. It presents the legal framework that regulates the functioning of the domestic market. Moreover, it discusses the number of permits and the value of fees for issuing permits collected by the General Directorate for National Roads and Motorways (Generalna Dyrekcja Dróg Krajowych i Autostrad, GDDKiA) over two decades. The article also evaluates trends concerning the number of licenses more than 50% decrease compared to the maximum in 2008. It assesses the course of changes in values, which in 2021 reached their highest level during the period under assessment. Furthermore, it discusses the differences that occurred in the number of permits issued and applications submitted in the years 2014-2022. It describes the structure of the number of permits issued in categories IV-VII in 2014-2020 and categories III-V in 2021-2022. It characterises the course of the largest operation in the history of Polish road haulage - the transport of an abnormally-sized TBM (Tunnel Boring Machine) - in terms of requirements and problems that occurred during the preparation and fulfilment of this order and were typical for the functioning of the sector. The evaluation provides the basis for summaries and conclusions on the Development and condition of the oversized cargo transportation sector in Polish road transport sector.

Physics-informed deep reinforcement learning for enhancement on tunnel boring machine's advance speed and stability

The traditional mode of Tunnel Boring Machine (TBM) operation is limited in their applicability and efficiency to meet the growing demand for underground spaces. Current methods to address this problem often lack physics interpretability and automatic adaptivity. In response to this issue, this paper describes an approach that integrates a physics-informed reinforcement learning (PIRL) algorithm into a TBM operation. The method combines a physics-informed machine learning (PIML) model and physics reward functions considering the working mechanism of earth pressure balance (EPB) TBMs, forming into a physics-informed Twin Delayed Deep Deterministic (pTD3) algorithm. The study reveals that the TBM performance can be improved by 69.3% using the pTD3 algorithm compared to manual operation. Integrating physics knowledge into reinforcement learning proves significantly effective in enhancing the TBM operations. The proposed method has the potential to revolutionize TBM operation and pave the way for more efficient, reliable, and automatic tunnel construction.

Soil Stabilisation prior to the Driving of the Tunnel Boring Machine under Buildings and Facilities During the Construction of the Sofia Metropolitan

Soil Stabilisation prior to the Driving of the Tunnel Boring Machine under Buildings and Facilities During the Construction of the Sofia Metropolitan

Experimental and numerical studies on mechanical behavior of pre-stressed infilled rock joints subjected to horizontal vibration loading

Underground jointed rock masses are usually subjected to a coupled effect of static pre-stress and vibration disturbance from rock-cutting in Tunnel Boring Machines (TBMs) tunneling. To investigate the mechanical behavior of pre-stressed infilled rock joints disturbed by horizontal vibration loading, a series of laboratory and numerical experiments were conducted, based on the in-situ vibration characteristics during TBM rock-cutting. The P-wave velocity and direct shear test techniques are combined to quantitatively characterize the damage of infilled rock joints. The experimental results reveal that the damage degree of rock joints exhibits a nonlinear increase with the increase of vibration frequency and amplitude, and the decrease of static pre-stress. Low static pre-stress (below 0.5 MPa), high vibration frequency (above 70 Hz) and high vibration amplitude (above 0.3 mm/s) are adverse factors to the stability of rock joints. From the PFC2D simulation, the contact force chain and contact force field were analyzed to elucidate the failure mechanism of infilled rock joints. The failure mode of infilled rock joints is closely related to the level of parameters, consisting with the results in laboratory experiments. In addition, the comparison of vibration results for weakly and strongly filling material demonstrates that grouting reinforcement enhanced the vibration resistance of in-situ jointed rock masses.

Classifying Rock Fragments Produced by Tunnel Boring Machine Using Optimized Convolutional Neural Network

Classifying Rock Fragments Produced by Tunnel Boring Machine Using Optimized Convolutional Neural Network