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Research on automation and intelligent operation of tunnel boring machine (TBM) is receiving more and more attention, benefiting from the increasing construction data. However, most studies on TBM operations optimization were trained by the labels of human drivers' decisions, which were subjective and stochastic. As a result, the control parameters suggested by these models could hardly surpass the performance of a human driver, even the possibility of subjective incorrect decisions. Considering that the geomechanical feedback to TBM under drivers' actions is objective, in this paper, a transformer-based model called the geological response for tunnel boring machine (GRTBM), is proposed to learn the relationship between operation-adjust and TBM monitoring changes. Additionally, with the model-based offline reinforcement learning, this paper provided a novel approach to optimizing the TBM excavation operations. The decision processes, recorded in the Yin-song TBM project for a waterway tunnel in Jilin Province of China, were used for the validation of the model. By adopting an implicit perception of geological conditions in the GRTBM model, the suggested method achieved the desired state within a single action, greatly outperformed the practical adjustments where 500 s were taken, revealing the fact that the proposed model has the potential to surpass the capability of human beings. [ABSTRACT FROM AUTHOR]

In recent years, tunnel-boring machines (TBMs) have been widely applied in deep coal mining. Turning is an inevitable challenge in TBM tunneling, and a TBM turning roadway exhibits greater instability than a straight roadway, as engineering experience has indicated. This study aimed to explore the failure mechanism and evaluate the support performance of a deep-turning roadway. Several numerical models were established to investigate the deformation of the roadway, the stress distribution, and the failure zone of the surrounding rocks under different tunneling conditions. The results show that the tunneling depth influences the failure pattern of the turning roadway: deep tunneling with high in situ stress can cause asymmetric failure of the turning roadway, while shallow tunneling with low in situ stress does not. Moreover, the change in turning radius, namely the change in roadway geometry, does not influence the stability of the turning roadway. In addition, the support actions for both the straight and turning roadways do not differ significantly, and the amount of controlled deformation of the surrounding rocks is proportional to their natural deformation. [ABSTRACT FROM AUTHOR]

Copyright of China Rubber Industry is the property of Editorial Office of China Rubber Industry and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To study the breaking differences between CS hob and BT hob under hard rock (rust rock) and soft rock (red sandstone), and reveal their adaptability in the two rock formations, the vertical breaking experiments of two hobs are conducted. Then, the rock breaking load, rock breaking difficulty coefficient, and rock breaking efficiency of the two hobs in different hob spacings are analyzed and discussed. The result denotes that the CS hob has a greater rock breaking load and rock breaking difficulty compared to the BT hob. Meanwhile, when the breaking object changes from hard rock (rust rock) to soft rock (red sandstone), both types of hobs' rock breaking loads decrease, but the CS hob's decrease is significantly greater than the BT hob's. Meanwhile, the optimal hob spacing for the CS hob increases from 40 mm to 50 mm, whereas for the BT hob, it remains at 30 mm. Considering the rock breaking load and rock breaking efficiency of the hobs together, the CS hob is found to be more suitable for soft rock formation, while the BT hob is more suitable for hard rock formation. [ABSTRACT FROM AUTHOR]

Background: Tuberculous meningitis (TBM) is a severe central nervous system (CNS) infection with a challenging diagnosis due to inadequate detection methods. This study evaluated current clinical detection methods and their applicability. Methods: A cohort of 514 CNS infection patients from 2018 to 2020 was studied. Data on general demographics, Cerebrospinal Fluid (CSF) analysis, epidemiology, and clinical outcomes were collected. TBM patients were identified, and the sensitivities of mmetagenomic next-generation sequencing (NGS), GeneXpert, and microbial culture were compared. Kappa statistic assessed the consistency between methods. Results: Among the patients involved, TBM (29%) and neurosyphilis (25%) were the two most prevalent CNS infections. CSF analysis indicated that 76% of patients had leukocytosis, suggesting a potential CNS inflammation. In TBM cases, 92.5% had elevated CSF protein and leukocyte counts. Moreover, the percentage of positive mNGS results was 55.6%. GeneXpert and MTB cultures alone had lower sensitivity, but combined use resulted in a 53.4% positive rate. Conclusions: This study highlights the high sensitivity of mNGS, comparable to GeneXpert and MTB culture. The combined methods are cost-effective and straightforward, and can partially substitute for mNGS, offering valuable alternatives for TBM diagnosis and providing insights into multiple diagnostic strategies in clinical practice. [ABSTRACT FROM AUTHOR]

Brittleness is an important mechanical property of rock. Accurately evaluating rock brittleness and its influence on the TBM tunnelling performance is necessary. In this work, via two practical engineering cases, with the aim of overcoming the difficulty of penetrating extremely hard rock (breccia fused tuff) in the Z huxi project, the influence of rock brittleness on the TBM tunnelling performance was studied via comparative analysis with that Nabang project. Seven commonly used rock brittleness indices based on stress‒strain curves were summarized, and a brittleness evaluation method suitable for extremely hard rock was determined by introducing the normalized specific energy to obtain brittleness indices for two lithologies (breccia fused tuff and biotite hornblende plagioclase gneiss) in two projects. The influences of rock brittleness on penetration and the specific energy were compared and analysed. The results showed that the brittleness indices B 3 and B 5 were more suitable for evaluating rock brittleness. Rock brittleness influenced the TBM tunnelling performance, but this influence gradually decreased with decreasing uniaxial compressive strength ( UCS ), which is obviously less than that of the rock strength. When the UCS was lower than 150 MPa, the TBM tunnelling parameters could be adjusted within a significant margin to eliminate the influence of rock brittleness, which could be ignored when predicting the tunnelling performance. When the UCS was greater than 150 MPa, rock brittleness imposed a notable influence on the tunnelling performance, which must be considered when predicting the tunnelling performance. This research could provide reference data for evaluating the hard rock brittleness index and accurately predicting the TBM tunnelling performance in engineering practice. [ABSTRACT FROM AUTHOR]

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Background Tuberculous meningitis (TBM) is a severe central nervous system (CNS) infection with a challenging diagnosis due to inadequate detection methods. This study evaluated current clinical detection methods and their applicability. Methods A cohort of 514 CNS infection patients from 2018 to 2020 was studied. Data on general demographics, Cerebrospinal Fluid (CSF) analysis, epidemiology, and clinical outcomes were collected. TBM patients were identified, and the sensitivities of mmetagenomic next-generation sequencing (NGS), GeneXpert, and microbial culture were compared. Kappa statistic assessed the consistency between methods. Results Among the patients involved, TBM (29%) and neurosyphilis (25%) were the two most prevalent CNS infections. CSF analysis indicated that 76% of patients had leukocytosis, suggesting a potential CNS inflammation. In TBM cases, 92.5% had elevated CSF protein and leukocyte counts. Moreover, the percentage of positive mNGS results was 55.6%. GeneXpert and MTB cultures alone had lower sensitivity, but combined use resulted in a 53.4% positive rate. Conclusions This study highlights the high sensitivity of mNGS, comparable to GeneXpert and MTB culture. The combined methods are cost-effective and straightforward, and can partially substitute for mNGS, offering valuable alternatives for TBM diagnosis and providing insights into multiple diagnostic strategies in clinical practice.

Abstract Understanding the distribution of cutting force provides a foundation for the design and optimization of cutterhead layout. The simulation of rotary cutting with a large cutting radius remains a challenge for laboratory tests. In this study, taking the driving condition of the Mawan Tunnel located in the Guangdong-Hong Kong-Macao Greater Bay Area as a case study, a full-scale rotary cutting platform with large cutting radius was used to investigate the rock-breaking effects. Rotary cutting with cutting depths of 1–8 mm and cutting radii of 200–1400 mm were carried out on the granite testing platform using a 19-in disc cutter. The normal force, rolling force, and side force during the cutting process were systematically monitored. Moreover, the time–frequency characteristics of the rock breaking process and the effects of cutting depth, cutting radius and stress state on the average and peak loads were investigated. The results show that the average normal force and rolling force increased with increasing cutting depth, while the side force was less affected by cutting depth through the Boltzman model analysis. The average normal force and rolling force were not significantly affected by the cutting radius, but the average side force decreased as a power function with increasing cutting radius, and showed a stable side force when the installation radius exceeded 1000 mm. The dominant frequency of the cutting force was 0–1.2 Hz, exhibiting notable low-frequency characteristics. Additionally, the ratio of peak to average (RPA) with respect to triaxial cutting force demonstrated an increase with the growth of cutting depth, while RPA in terms of side force exhibited a corresponding growth with the increasing cutting radius. In particular, the cutting force characteristics of the cutterhead obtained in this study can inform the layout of disc cutters and real-life TBM operations, thereby avoiding severe overloading of internal disc cutters.

Abstract Brittleness is an important mechanical property of rock. Accurately evaluating rock brittleness and its influence on the TBM tunnelling performance is necessary. In this work, via two practical engineering cases, with the aim of overcoming the difficulty of penetrating extremely hard rock (breccia fused tuff) in the $$Z{\text{huxi}}$$ Z huxi project, the influence of rock brittleness on the TBM tunnelling performance was studied via comparative analysis with that $$Nabang$$ Nabang project. Seven commonly used rock brittleness indices based on stress‒strain curves were summarized, and a brittleness evaluation method suitable for extremely hard rock was determined by introducing the normalized specific energy to obtain brittleness indices for two lithologies (breccia fused tuff and biotite hornblende plagioclase gneiss) in two projects. The influences of rock brittleness on penetration and the specific energy were compared and analysed. The results showed that the brittleness indices $$B3$$ B 3 and $$B5$$ B 5 were more suitable for evaluating rock brittleness. Rock brittleness influenced the TBM tunnelling performance, but this influence gradually decreased with decreasing uniaxial compressive strength ( $$UCS$$ UCS ), which is obviously less than that of the rock strength. When the $$UCS$$ UCS was lower than 150 MPa, the TBM tunnelling parameters could be adjusted within a significant margin to eliminate the influence of rock brittleness, which could be ignored when predicting the tunnelling performance. When the $$UCS$$ UCS was greater than 150 MPa, rock brittleness imposed a notable influence on the tunnelling performance, which must be considered when predicting the tunnelling performance. This research could provide reference data for evaluating the hard rock brittleness index and accurately predicting the TBM tunnelling performance in engineering practice.

Establishing an accurate predictive model for response parameters is the foundation of control parameter optimization for tunnel boring machines (TBMs). However, existing research mostly focuses on mean values during stable stages, and lacks real-time prediction throughout the entire process, failing to meet the demand for fine-tuned parameter recommendations. This paper proposes the weight matrix method for feature selection, which provides specific numerical values and rankings of each feature's contribution. A deep learning model based on temporal convolutional network (TCN) is proposed to achieve real-time prediction of cutterhead torque (T) and total thrust (F), which is compared with the gated recurrent unit (GRU) and long short-term memory (LSTM). The proposed method was validated on the Yinchao project, and the results demonstrated that (1) the weight matrix method outperforms the Pearson coefficient method in terms of model accuracy, and (2) the TCN model performs better than GRU and LSTM. The method proposed in this paper achieves high precision in predicting T and F , and holds promise as a core algorithm for automatic control in TBM and providing crucial support for TBM's advancement into the era of autonomous driving. [ABSTRACT FROM AUTHOR]

Knowing accurate values of rock engineering parameters in hard rock condition is the key in estimating and adjusting TBM performance. In this study, TBM penetration per revolution (Pr) as driving parameter, TBM operational parameters including cutterhead torque (Tq), field penetration index (FPI), thrust force (Th), cutter load (Fn), cutterhead rotational speed revolution per minute (RPM), and also cutterhead diameter as a mechanical machine specification are used to predict geomechanical parameters including rock quality designation (RQD) and unconfined compressive strength (UCS) based on reverse analysis in three types of strong rocks (Tuff, Andesite, Diorite) along the Southern lot of Kerman water transfer tunnel; KrWCT. A soft computing method called least squares-support vector machine (Ls-SVM), is trained using operating and driving data as well as rock engineering parameters gathered from the KrWCT project which is excavated in hard rock condition using double shield TBM. Due to the lack of access to the excavation face in mechanized tunneling, the collection of geomechanical data on the rock mass is possible only through the examination of excavated material and limited inspections during cutterhead repairs. Therefore, this paper has tried to predict and classify the rock engineering factors using some indicators related to machine performance, mechanical specification, and TBM operational parameters. Among the data collected during the pre-construction and construction phases of the project, the dataset was classified into 42 zones, and the reasonable distribution intervals of the main tunneling factors corresponding to each zone were defined. New empirical equations are developed to estimate the properties of igneous rocks based on linear and non-linear multivariable regression (MR). Several loss functions were used to assess the performance and precision of the applied methods. The results of the proposed models indicate an acceptable and reliable accuracy. Highlights: TBM data predicts rock engineering properties in complex geological condition. Forecasting RQD and UCS in deep tunnels through strong rocks using reverse analysis. Developing empirical models for calculating UCS and RQD based on statistical analysis. Detailed analysis of Ls-SVM supervised network for rock geomechanical prediction. Examining model accuracy with various statistical indices and loss functions. [ABSTRACT FROM AUTHOR]

Introduction: Patients presenting with head and neck squamous cell carcinoma of unknown primary (HNSCCUP) remain challenging clinical scenarios as large variation exists in practices used to locate the primary. Objective: The objective of this systematic review is to review of the literature and offer recommendations for oropharyngeal biopsies in HNSCCUP. Method: Pubmed, Medline and Embase were searched to identify studies from inception to October 2021. The Preferred Reporting Items for Systematic Reviews and Meta‐analyses (PRISMA) guidelines were followed. Results: A total of 483 articles were included and screened, 41 studies met the inclusion criteria, including over 3400 patients from the original articles (122 of these patients were reported on in two sequential articles by a single author – table 1) and 4 large metaanalyses including 1852 patients. The primary site identification rate following random biopsies or deep tissue biopsies is less than 5% in most studies. The mean detection rate following ipsilateral tonsillectomy is 34%; two pooled analyses indicate that the mean detection rate following tongue base mucosectomy is 64%, with this figure rising when the tonsils are negative. Conclusions: High level evidence is lacking, with heterogeneity in the reported studies. Published meta‐analyses are based on retrospective data. There is little evidence supporting the practice of random/non‐directed oropharyngeal biopsies. Available evidence supports palatine tonsillectomy and tongue base mucosectomy compared to deep tissue biopsies. [ABSTRACT FROM AUTHOR]

Various models have been proposed to estimate the TBM penetration rate. Generally, the input parameters of these models can be divided into two categories: Machine parameters and geological engineering parameters. The engineering geological parameters will significantly influence the penetration rate if the machine operational parameters are kept within a reasonable near-optimal range. However, while some performance prediction models can be used for many common project settings, they have lower accuracy in certain applications. This study compared the observed penetration rate of a hard rock TBM with those predicted by MCSM, Norwegian University of Science and Technology (NTNU), Farrokh–Rostami, and Ramezanzadeh’s models in the Kerman water tunnel (KWT). Next, joint survey data are collected from the different zones of the KWT. For this purpose, a 3D discrete fracture network (DFN) model code was generated in Mathematica© version 13. The joint data’s orientation, persistence, and spacing were used to develop a 3D-DFN model for estimating the blockiness rate (BR) index. The BR index is the actual joint intensity in 2D (P21) and 3D (P32). In this study, the BR index is the newest rock mass parameter introduced and used to predict the penetration rate of TBM. This index can serve as a rock mass parameter that provides excellent and realistic results for predicting penetration rate (PR). The corresponding determination coefficient values of the PR with P32 and P21 are R2 = 0.96 and R2 = 0.98, respectively, and with CIA and UCS, are R2 = 0.42 and R2 = 0.49, respectively. Furthermore, using the DFN model showed its potential to be an accurate and reliable method for the overall estimation of the in-situ rock mass fragmentation, which highly controls the penetration rate of TBM. Research Highlights: The penetration rate of a hard rock TBM was compared with the NTNU, MCSM, Farrokh-Rostami, and Ramezanzadeh predictive models in the Kerman water tunnel (KWT). A 3D-Discrete fracture network (DFN) model code was generated. Four different zones of KWT were studied to discriminate rock mass parameters or intact rock parameters that affect the penetration rate of TBM. The BR index is the newest rock mass parameter that has been introduced and used to predict the penetration rate of TBM. The Blockiness Rate (BR) index as rock mass parameters has verified that it highly influences the penetration rate of TBM. [ABSTRACT FROM AUTHOR]

In order to study the rock-breaking process of a 17-inch disc-type cutterhead in a full-face tunnel boring machine (TBM), we utilized the discrete element method software EDEM to analyze the in-fluence of relevant parameters (cutter spacing, penetration depth, installation radius, phase difference) on rock-breaking loads and efficiency. Firstly, validate the rationality of the discrete element model for the disc cutter rock-breaking process. Subsequently, establish a simulation of sequential rock-breaking with multiple rotating disc cutters and analyze the load characteristics as well as specific energy consumption. Simulation results indicate that within certain parameter ranges, an increase in cutter penetration depth leads to an increase in average load force, while an increase in cutter spacing and installation radius initially results in an increase in average load force followed by a decrease. An increase in phase difference results in an initial decrease in average load force followed by an increase. Based on orthogonal tests, a combination of rock-breaking parameters with values of 100 mm for cutter spacing, 8 mm for penetration depth, 650 mm for installation radius, and 45° for phase difference was found to yield lower specific energy consumption. This method can provide reference for cutter arrangement and cutterhead performance prediction. [ABSTRACT FROM AUTHOR]

Two series of experiments were carried out to examine pressurised bentonite slurry infiltration into saturated sand columns. Three types of sand were examined, and water–bentonite and water–bentonite–sand slurries were used in series 1 and 2, respectively. Series 1 investigated the effect of sand particle size and series 2 examined the effect of the fine-sand particle content in the slurry. Scanning electron microscopy (SEM) imaging was used to observe the morphological features of the dry slurry-infiltrated sand samples. A solution for the infiltration distance during mud spurt for water–bentonite–sand slurry infiltration was verified using the data from series 2. The infiltration test results showed that the hydraulic conductivity of the slurry-infiltrated coarse sand for slurry in series 2 was lower than that in series 1. Visual observations and the SEM images showed that sand particles were bound to a bentonite film, indicating that, during infiltration, the channels for fluid flow among the sand particles are blocked by the bentonite particles adhered to the sand particles. The solution for the infiltration distance during mud spurt for water–bentonite–sand slurry infiltration showed good agreement with the experimental results. [ABSTRACT FROM AUTHOR]

This paper introduces a test system for microwave-assisted dual-mode mechanical cutting of hard rock under true triaxial compression. The test system was developed by Northeastern University, China, to simulate the cutting and breaking of hard rock by a tunnel boring machine (TBM). The test system is mainly composed of a dual-mode mechanical cutting subsystem, a true triaxial loading subsystem and a high-power microwave presplitting subsystem. The system performs dual-mode cutting under true triaxial stress, applies a single sensor to monitor the three-dimensional force of the cutter head, and integrates the reduction in the vibration and resistance to torsion during the cutting process. Mechanical cutting tests of basalt under different amounts of microwave irradiation and true triaxial stress conditions were conducted in Chifeng, Inner Mongolia, China. The results showed that microwave radiation presplitting effectively improved the efficiency of mechanical rock breaking. However, after 180 s of microwave irradiation, true triaxial high stress inhibited the mechanical breaking of basalt in terms of the overall excavation depth. During the tests, each system performed stably. The test results verified the reliability of the test system. Highlights: A true triaxial stress microwave-assisted mechanical dual-mode cutting test system is independently developed. The proposed system simulates rock breaking by a microwave-assisted roadheader under different ground stress conditions. The cutting test system innovates in three main facets: it carries out a dual-mode cutting test system in rock breaking; it realizes a unified monitoring output of a single sensor for the three-dimensional force; and it integrates the seismic resistance and torsion resistance to create a smooth system body. As the cutting test is conducted, the effective influence range of microwave radiation on rock is verified, and the degree of influence of true triaxial high stress on microwave-assisted mechanical cutting is revealed, providing guidance for deep microwave-assisted rock breaking of roadheaders. The necessity and feasibility of the system development is thus verified. [ABSTRACT FROM AUTHOR]

Tunnel boring machines (TBMs) are used to excavate tunnels in a manner where the rock is constantly penetrated with rotating cutter heads. Fine particles of the rock minerals are thereby generated. Workers on and in the vicinity of the TBM are exposed to particulate matter (PM) consisting of bedrock minerals including α-quartz. Exposure to respirable α-quartz remains a concern because of the respiratory diseases associated with this exposure. The particle size distribution of PM and α-quartz is of special importance because of its influence on adverse health effects, monitoring and control strategies as well as accurate quantification of α-quartz concentrations. The major aim of our study was therefore to investigate the particle size distribution of airborne PM and α-quartz generated during tunnel excavation using TBMs in an area dominated by gneiss, a metamorphic type of rock. Sioutas cascade impactors were used to collect personal samples on 3 separate days. The impactor fractionates the dust in 5 size fractions, from 10 µm down to below 0.25 µm. The filters were weighted, and the α-quartz concentrations were quantified using X-ray diffraction (XRD) analysis and the NIOSH 7500 method on the 5 size fractions. Other minerals were determined using Rietveld refinement XRD analysis. The size and elemental composition of individual particles were investigated by scanning electron microscopy. The majority of PM mass was collected on the first 3 stages (aerodynamic diameter = 10 to 0.5 µm) of the Sioutas cascade impactor. No observable differences were found for the size distribution of the collected PM and α-quartz for the 3 sampling days nor the various work tasks. However, the α-quartz proportion varied for the 3 sampling days demonstrating a dependence on geology. The collected α-quartz consisted of more particles with sizes below 1 µm than the calibration material, which most likely affected the accuracy of the measured respirable α-quartz concentrations. This potential systematic error is important to keep in mind when analyzing α-quartz from occupational samples. Knowledge of the particle size distribution is also important for control measures, which should target particle sizes that efficiently capture the respirable α-quartz concentration. [ABSTRACT FROM AUTHOR]

Hard rock tunnel boring machines (TBMs) are increasingly widely used in tunnel construction today; however, TBMs are deeply buried underground and have a low perception of the underground surrounding rock conditions and excavation parameters. In order to ensure the safety of TBM digging, this paper describes the research carried out relating to the accurate prediction of TBM digging parameters and the precise prediction of tunnel surrounding rock grades. Based on the on-site excavation parameters and geological data of a certain water diversion project in Xinjiang, the thrust, torque, rotational speed, net excavation speed, construction speed, and excavation specific energy of the stable section of TBM excavation are selected as the input parameters for the model. A convolutional neural network optimized–long short-term time series prediction model (CNN-LSTM model) is established to predict the excavation parameters under various levels of surrounding rock conditions. The research results indicate that the CNN-LSTM model has a high prediction accuracy, with most data having a relative prediction error rate (Er) within 10%, root mean square error (RMSE) within 5%, mean absolute percentage error (MAPE) within 10%, and goodness of fit (R2) above 0.9. The model can assist in parameter setting, engineering planning and disposal of high-risk holes in the TBM digging process, and improve the safety level of TBM digging. [ABSTRACT FROM AUTHOR]

The construction of tunnels in conditions of dense urban development affects buildings, structures, and engineering communications located at the surface. In this work, through dispersion analysis, factors influencing the settlement of the earth's surface and buildings during tunneling were selected. Subsequently, a model based on statistically significant parameters that can predict deformations at the pre-design stage was created. This research was conducted using data from geotechnical monitoring obtained during the construction of underground structures, with information about the technological parameters of shield tunneling in the construction of the single-track lines of the Moscow Metro using TBM with face-support pressure and engineering–geological conditions. In the obtained model, there is a clear dependency between the additional displacement of the monitoring object located above the projected tunnel and the average face-support pressure causing the mentioned deformations. The response is also affected by the soil deformation model at the tunnel face, the depth of the tunnel, and the soil excavation for the installation of one ring. [ABSTRACT FROM AUTHOR]

Mud caking on shield cutterhead is a critical issue for tunnel safety, and temperature and duration are factors that can affect the characteristics of mud cake. Therefore, the aim of this study is to explore the characteristics of different temperatures and action times on the adhesion and hardness of red-bed geological mud cake. A self-designed experimental apparatus was used to simulate the adhesion of mud cake on the cutterhead. The adhesion and hardness of the mud cake were analyzed through mud cake shedding tests and hardness tests. In addition, water film theory is used to analyze the adhesion mechanism of the mud cake. The results indicate that temperature and duration are key factors affecting mud cake shedding. Within the range of 25~150 °C, mud cake shedding efficiency is positively correlated with temperature and duration. However, temperatures above 150 °C promote the sintering of the mud cake, reducing its shedding efficiency. The hardness of the mud cake increases with temperatures above 150 °C, where the mud cake hardens and sinters, increasing the difficulty of shield tunneling. The water content of mud cake is influenced by temperature and time, affecting the amount of mud cake shedding. As the water content increases, the shedding initially decreases and then increases, reaching its minimum at about 30%, where the adhesion is strongest. By controlling the temperature and time, the water content can be optimized, improving the handling of mud cake. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Water content is an important factor affecting the rock-breaking efficiency of tunnel boring machine (TBM) disc cutters. However, limited efforts have been made to study the fracturing mechanism of sandstone excavation by TBM disc cutters under varying water content conditions. To investigate the breakage behavior of water-soaked sandstone by TBM disc cutters, five sets of penetration tests on sandstone specimens with different water content levels were performed. The tests were conducted using a modified RYL-600 computer-controlled rock shear rheometer. An acoustic emission (AE) monitoring system was utilized throughout the entire process to track the AE activity of the specimens. The force–depth curves of the penetration process at various water content levels were investigated. The effects of water content on AE characteristics, rock fracture properties, and specific energy were analyzed. The results indicate that AE activity can be divided into three stages: quiet period, slow rise period, and active period. With increasing water content, peak penetration force, consumed energy, and specific energy decrease gradually, while chip volume increases. Water promotes mutual penetration of surface and internal cracks of the specimen, resulting in the formation of larger chip volumes. These findings provide theoretical guidance for designing and improving TBM cutter head parameters in water-rich soft rock formations. [ABSTRACT FROM AUTHOR]

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents the outcomes of a sequence of three-dimensional numerical simulation models conducted in linear cutting mode, employing the LS-DYNA software. The primary objective was to scrutinize the side force values exerted on the gauge cutters. To accomplish this, an assortment of simulation models was meticulously constructed and executed, employing the Lagrange and SPG computational algorithms, along with the JHC and RHT constitutive material models. By comparing the outcomes of these models with the linear cutting experiments documented in the literature, specifically concerning the Colorado red Granite, it was determined that the SPG computational algorithm and the RHT constitutive material model proved to be the most suitable for simulating rock-cutting scenarios. Building upon the chosen computational algorithm and constitutive material model, a series of numerical models was then crafted to simulate the penetration of gauge cutters in both longitudinal and transverse orientations relative to their tips. Subsequently, the applied side forces were extracted, and a statistical model was developed to accurately predict the side forces experienced by the gauge cutters, yielding a coefficient of determination of 93%. [ABSTRACT FROM AUTHOR]

Introduction. One of the effective approaches to assessing the impact of tunnel construction works involves a comprehensive approach to problem-solving, including determination of the face-support pressure to ensure the stability of the tunnel face and assessment of additional surface movements that occur during tunnel construction. This approach is justified by the fact that actual displacements can be close to predicted ones when the optimal face-support pressure is selected and there is no face loss of soil, which could lead to unforeseen deformations. However, it should be noted that the method for calculating pressure presented in the current standard is a preliminary forecast and requires constant adjustment of the pressure during tunnel construction works.Materials and methods. In this work, the authors adapted Melan’s problem formulation with a horizontal load parallel to the surface to assess the change in the stress-strain state of the soil mass before tunnel face excavation due to the application of the face-support pressure. The problem formulation corresponds to the stage of work preparation before excavation of the soil for the installation of a precast concrete lining ring into its design position.Results. Based on the analytical equations formulated in the MathCAD software environment, isopoles of vertical and horizontal stresses, and vertical deformations were created. The obtained isopoles were compared with isopoles generated in the Plaxis 2D software using similar parameters to validate the results. Additionally, isopoles of the soil mass under the influence of the face-support pressure, considering self-weight stresses, were obtained to establish a more realistic stress-strain state of the mass in which a tunnel is being constructed.Conclusions. The analysis of the research results has shown that the isopoles are quantitatively and qualitatively similar to each other. The method proposed by the authors can be adapted with appropriate modifications to adjust the face-support pressure during construction, which is necessary both to ensure the stability of the tunnel face during construction and to minimize the impact of the face-support pressure on the ground surface.

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. [ABSTRACT FROM AUTHOR]

Accurate evaluation of cutter life at different cutter positions on the cutter head is helpful to determine the time of cutter change and reduce the time of cutter wear measurement, which is of great significance to improve the tunneling efficiency of tunnel boring machine (TBM) projects. Unfortunately, there is no unified cutter life evaluation index now. The field data of cutter wear are collected from a section of a long TBM tunneling water conveyance tunnel in China. Two kinds of cutter life evaluation indexes (based on the radial wear extent of cutter rings and replacement number of cutter rings) are selected and the variation rule between these two kinds of indexes with cutter installation radius is statistically analyzed. The results show that the regression relationships between the two kinds of cutter life evaluation indexes and installation radius mainly present linear functions and quadratic functions. Those regression relationships are affected by factors such as wear type, installation angle, cutter spacing, influence width, and allowable limit wear extent of cutter rings. Considering the calculation accuracy of the evaluation index, the actual working conditions of the disc cutter, and ignoring the influence of tunnel diameter, it is recommended to preferentially choose the radial wear extent of cutter rings per unit rolling distance as the evaluation index of cutter life. The research results can provide a reference for the selection of cutter life evaluation index, prediction of disc cutter life at different cutter positions, and establishment of cutter life prediction mode. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The advance rate (AR) of tunnel boring machines (TBMs) plays a pivotal role in evaluating their efficiency in tunnel engineering projects. This study focuses on the development of precise prediction models for TBM performance employing advanced algorithms, including gene expression programming, time series analysis, multivariate regression, artificial neural networks, particle aggregation algorithms, genetic algorithms, adaptive neural fuzzy inference systems, and support vector machines. The AR, serving as a performance metric, becomes the specific target for prediction models. A test database comprising 3597 datasets was curated from a tunneling project at the Sar Pol Zahab, Bazi Daraz water transfer tunnel. Utilizing 21 parameters as input variables, intelligent AR models were formulated based on comprehensive training and testing patterns, incorporating geological features and the key machine parameters influencing AR. Quantitative evaluation of the models involved statistical indicators such as root mean square error (RMSE), coefficient of determination (R2), and variance calculation. Comparative analysis based on RMSE, MAE, MAPE, VAF, and R2 superior gene expression function models showed that the gene expression algorithm with 1.41, 0.66, 6.33, 98.88, and 0.95 ahead of the nose is better than other approaches. These results underscore the efficacy of the gene expression programming-based model, suggesting its potential to yield a novel functional equation for accurate TBM performance prediction. [ABSTRACT FROM AUTHOR]

The complex red-bed geology is primarily composed of iron-rich sedimentary rock layers with clay minerals as a major component. The soil water content exceeds 30%, and its high viscosity and water content lead to the easy formation of mud cake on the cutterhead, endangering the safety and progress of construction, which poses a significant challenge for tunnel boring machines (TBMs). The use of dispersants to eliminate mud cake is a common method in engineering projects. This paper presents an improved disintegration experiment instrument to study the disintegration characteristics of mud cake from the red-bed geology under different dispersant solutions, proposing a dispersant formulation suitable for the red-bed geology of the Haizhu Bay Tunnel project. The results indicate that mud cake samples exhibit a moderate disintegration effect in pure water. Furthermore, it has been observed that the disintegration effect decreases as the thickness of mud cake increases. Sodium silicate solution was not suitable for treating the red-bed geological mud cake, while sodium hexametaphosphate and oxalic acid solutions had a good promoting effect on the disintegration of red-bed geological mud cake. However, there was a threshold for the dispersant concentration; exceeding this threshold actually worsened the disintegration effect. Ultimately, the engineering application of a 10% oxalic acid solution, which proved effective in disintegrating the mud cake, significantly enhanced the excavation efficiency in the Haizhu Bay Tunnel project. [ABSTRACT FROM AUTHOR]

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