Tunnelling and Underground Space Technology最新文献

{"title":"Investigation of temperature and humidity impact on thermal comfort in deep underground tunnel during construction in hot climate: A case study in an underground hydropower station","authors":"Shengyu Liu ,&nbsp;Wentao Wu ,&nbsp;Xueqing Sun ,&nbsp;Hongxin Tian ,&nbsp;Jianwei Li ,&nbsp;Ronghui Zhou ,&nbsp;Bezoun Deborah Dembele ,&nbsp;Xiong Shen","doi":"10.1016/j.tust.2025.106669","DOIUrl":"10.1016/j.tust.2025.106669","url":null,"abstract":"<div><div>This study investigates the thermal and humidity conditions and their impact on workers’ thermal comfort during the construction of underground tunnels in hot climates. Wall temperature, air temperature, and humidity were measured within an underground hydropower station tunnel. The wall temperature at the tunnel entrance and bottom end was found to be 4 °C higher than in the middle section. Air temperature stabilized at 450 m from the entrance, while humidity stabilized at 1450 m from the entrance. A Computational Fluid Dynamics (CFD) model was employed to simulate these conditions, with results demonstrating good agreement with on-site measurements for both air temperature and humidity. Simulation outcomes revealed a vertical temperature difference of up to 20 °C near heat sources, underscoring the potential of increased ventilation rates as a viable solution to mitigate high temperatures at tunnel ends. Evaluations based on PMV (Predicted Mean Vote) and WBGT (Wet Bulb Globe Temperature) criteria indicated that areas adjacent to heat sources do not meet thermal comfort standards, highlighting that reliance on dry bulb temperature alone is insufficient for assessing thermal comfort during underground tunnel construction activities. These findings can inform the optimal design of ventilation and air conditioning systems throughout the construction of underground tunnels.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"162 ","pages":"Article 106669"},"PeriodicalIF":6.7,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143825660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on rock muck transfer performance of a hard rock TBM cutterhead","authors":"Mengdan Li ,&nbsp;Yan Li","doi":"10.1016/j.tust.2025.106637","DOIUrl":"10.1016/j.tust.2025.106637","url":null,"abstract":"<div><div>This study aims to solve the problem of low mucking performance of the large-diameter tunnel boring machine (TBM). The full-scale linear rock-breaking tests were conducted to analyze the size and shape of the rock muck produced under different test conditions. Based on the 3D laser scanning test, the digital 3D model of the real shape of irregular muck was obtained. The numerical simulation of the mucking process of a large-diameter cutterhead was constructed. The influences of the disc cutter system, the degree of joint development, the tunneling direction, and the TBM operational parameters (cutterhead rotational speed and penetration per revolution) on the mucking performance of the cutterhead were investigated. The results indicated that the disc cutter system has the effects of collision and diversion on muck. In the simulation model with the disc cutter system, the amount of the muck in the center buckets increases by a factor of 2.5. In the stratum with a high degree of joint development, the percentage of muck accumulated in front of the cutterhead and inside the cutterhead increases by 22% and 88%, respectively, and the mucking efficiency decreases by 8.8%. The mucking efficiency of the downhill advancement is lower, and the bucket offset angle can effectively improve the mucking efficiency. The mucking efficiency first increases and then decreases with the increase of the cutterhead rotational speed and penetration per revolution, and there are optimal critical values. The research results provide valuable insights for the optimal design of the mucking structure of the TBM cutterhead and the adjustment of the operational parameters of the machine.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"162 ","pages":"Article 106637"},"PeriodicalIF":6.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainty design optimization of the main bearing in tunnel boring machine based on the Kriging model with partial least squares","authors":"Xinqi Wang ,&nbsp;Lintao Wang ,&nbsp;Huashan Chi ,&nbsp;Bo Yuan ,&nbsp;Qingchao Sun ,&nbsp;Wei Sun ,&nbsp;Yunhao Cui","doi":"10.1016/j.tust.2025.106648","DOIUrl":"10.1016/j.tust.2025.106648","url":null,"abstract":"<div><div>During the tunnel boring machine work, the main bearing failure can cause great economic losses and safety hazards. However, the multiple uncertainties in the manufacturing, assembly and operation stage of the main bearing lead to the difficulty of its stable and reliable design, and the load-carrying capacity is hardly guaranteed. For that, an efficient uncertainty design optimization strategy for the main bearing is proposed by combining the Kriging model with partial least squares and a genetic algorithm. A five-degree-of-freedom static analysis model of the main bearing is established using the vector method to provide training samples and verified by the relative displacement test of the rings. The main influencing factors are screened based on sensitivity analysis. Considering uncertainties such as the structural dimensions, material properties and operating loads of the main bearing, a surrogate model is constructed to achieve an example study and compared with the initial design and deterministic optimization strategy. The results show that the fatigue life of the main bearing has increased by 43.01% compared to the initial design. The design robustness is improved and the design reliability is ensured compared to the deterministic optimization strategy. The method realizes the rapid acquisition of the optimal stable and reliable structure for the main bearing, which is an important reference value for the uncertainty design optimization for other types of large slewing bearings.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"162 ","pages":"Article 106648"},"PeriodicalIF":6.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Laboratory model tests and unstable collapse analysis of SPB shield machine tunnelling in saturated sand","authors":"Yunfa Li ,&nbsp;Guojun Wu ,&nbsp;Weizhong Chen ,&nbsp;Jingqiang Yuan ,&nbsp;Mengzhe Huo","doi":"10.1016/j.tust.2025.106631","DOIUrl":"10.1016/j.tust.2025.106631","url":null,"abstract":"<div><div>This paper aims to investigate the tunnelling stability of underwater slurry pressure balance (SPB) shields and the formation and evolution mechanisms of ground collapse following face instability. A laboratory SPB shield machine was employed to simulate the entire tunnelling process. Multi-faceted monitoring revealed the responses of soil pressure, pore water pressure, and surface subsidence during both stable and unstable phases. The morphological evolution characteristics of surface collapse pits were analyzed using three-dimensional scanning technology. The experimental results indicate that: (1) The key to stable tunnelling is balancing the pressure in the slurry chamber with the tunnelling speed, which ensures the formation of a filter cake in front of the cutterhead. (2) The torque of the cutterhead, soil pressure, and surface subsidence respond significantly and synchronously when the tunnel face becomes unstable, while the soil and water pressures are relatively less noticeable. (3) Excavation disturbance results in a gentler angle of repose and a wider range of collapse in the longitudinal direction of the collapsed pit. (4) A formula for predicting the duration of collapse is proposed, which effectively integrates the evolution patterns of the collapse pit and has been well-validated through comparison with the experimental results. This study provides a reference for the safe construction of tunnel engineering in saturated sand.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"162 ","pages":"Article 106631"},"PeriodicalIF":6.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143824471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of disc cutter wear of shield machines based on transfer learning","authors":"Yuxiang Meng ,&nbsp;Qian Fang ,&nbsp;Guoli Zheng ,&nbsp;Gan Wang ,&nbsp;Pengfei Li ,&nbsp;Shuang Chen","doi":"10.1016/j.tust.2025.106633","DOIUrl":"10.1016/j.tust.2025.106633","url":null,"abstract":"<div><div>Disc cutters serve as the primary device in shield machines for rock breaking during tunnel construction. Assessing the wear state of disc cutters is crucial for making timely replacement decisions. Several researchers have successfully predicted disc cutter wear with acceptable accuracy using Machine Learning (ML). However, ML models are often project-specific. The model trained on one project cannot be applied to the other project if the two projects have significant deviations, resulting in a waste of resources and effort. To address this issue, we propose a domain-adversarial-based transfer learning method to improve the generalization performance of ML models. In particular, we integrate the Domain-Adversarial Neural Network (DANN) with the Transformer. The proposed model makes domain discrimination and regression prediction for input parameters. The domain-adversarial mechanism makes the extracted features from input parameters share many commonalities and confuses data from different domains, which can improve the generalization performance of the model. The hyperparameter <em>λ</em> of the proposed model is used to balance the importance of domain discrimination and regression prediction. We validate the effectiveness of the proposed method in the second subsea tunnel in Qingdao, China. The south and service tunnels of the project are in similar strata conditions but have a significant difference in tunnel diameter. They share many commonalities in the wear characteristics of disc cutters. We set the service tunnel as the source domain and the south tunnel as the target domain. The model is trained and tested in the service tunnel, learning wear characteristics under different strata. Then, the pre-trained model is transferred to the south tunnel and fine-tuned with limited data to adapt to wear characteristics under different shields. Finally, the fine-tuned model is used to predict the wear values of the target data in the south tunnel. The domain-adversarial-based Transformer model outperforms FCN, LSTM and Transformer without the domain-adversarial mechanism and requires even limited target project data, unlike traditional models, which require extra training data. The proposed method can be applied in the early stage of related projects when data are scarce.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"162 ","pages":"Article 106633"},"PeriodicalIF":6.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143824474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effect of lining density on the seismic response of ground penetrating shield tunnels: Shaking table testing and simplified semi-analytical solution","authors":"Qi Wang ,&nbsp;Yong Yuan ,&nbsp;Tao Liu ,&nbsp;Haitao Yu ,&nbsp;Ioannis Anastasopoulos","doi":"10.1016/j.tust.2025.106622","DOIUrl":"10.1016/j.tust.2025.106622","url":null,"abstract":"<div><div>The Ground Penetrating Shield Tunnel (GPST) method optimizes construction in soft ground by eliminating deep vertical shafts, reducing construction time, and minimizing the environmental impact. The present study examines the effect of lining density on the seismic response of the tunnel. Large scale shaking table tests are conducted, comparing the response of two tunnel models with different lining densities. The segmental lining of the two tunnel models is constructed employing two different gypsum mixes, the first one with normal weight aggregates representing an ordinary lining, and the second one with lightweight aggregates representing a lightweight lining of 50% reduced density. Employing a detailed instrumentation system, the experimental results reveal the key differences in the seismic response of the two tunnel models, quantifying the effect of lining density. The derived insights are used to develop and validate a simplified semi-analytical model, which is subsequently employed for parametric analyses. The model is based on a beam resting on Winkler foundation approach, accounting for the variation of soil modulus with depth. The parametric analyses reveal a strong correlation between the dynamic response of the above-ground portion of the tunnel and lining density. The decrease of lining density leads to a decrease of the inertial response of the above-ground tunnel portion, and to a substantial decrease of its structural displacement. The lining density also has a significant effect on the frequency response of the tunnel, with its reduction leading to a shift of the tunnel’s natural frequency away from the predominant frequency of the soil, further reducing the inertial response of the tunnel.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"162 ","pages":"Article 106622"},"PeriodicalIF":6.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143824473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic analysis of fire casualties in an urban traffic tunnel considering the uncertainty of vehicle queue","authors":"Dong-Mei Zhang ,&nbsp;Rui Zhu ,&nbsp;Zhong-Kai Huang ,&nbsp;Lei Yu","doi":"10.1016/j.tust.2025.106619","DOIUrl":"10.1016/j.tust.2025.106619","url":null,"abstract":"<div><div>Fire accidents could lead to severe casualties, especially in urban traffic tunnels, due to the concentration of users and limited space. However, it is challenging to evaluate the fire casualties in tunnel fires due to the complicated development of fire environment and the uncertainty of personnel distribution, which is influenced by vehicle queue. In this paper, a prediction model on evaluating probability of fire casualties in urban traffic tunnels is proposed, considering the evolution of the thermal and carbon monoxide distribution, as well as the uncertainty of vehicle queue. Firstly, the general framework of the model is introduced and the procedure for generating the probability curve is outlined. Subsequently, each module of the model, including the evolution of the fire scenario, simulation of evacuation process, evaluation of fire casualty and fitting of probability curve is elaborated in details. Then, this model is applied to a three-lane traffic tunnel in Shanghai to investigate the influence of heat release rate, fire source locations and ventilation systems on the probability curves of fire casualty expectation. The results show that there is a certain correlation in the impact of heat release rate and fire source location on fire casualty expectation. Besides, the ventilation condition has a significant impact on fire casualty expectation. The expected values of fire casualty expectation under longitudinal ventilation system could sometimes be only one-tenth of those under the natural ventilation condition. This study makes some contributions to evaluating the personnel loss in tunnel fire and lays a foundation for assessing and improving resilience of tunnel.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"162 ","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semi-supervised ensemble model for TBM rock mass classification","authors":"Shaoxiang Zeng ,&nbsp;Yuanqin Tao ,&nbsp;Honglei Sun ,&nbsp;Yu Wang","doi":"10.1016/j.tust.2025.106632","DOIUrl":"10.1016/j.tust.2025.106632","url":null,"abstract":"<div><div>Rock mass classification is crucial for tunnel construction with tunnel boring machines (TBMs). Due to the limited measured rock data, existing machine learning-based classification methods often use empirically derived data to supplement the rock mass datasets for model training, which compromises the classification reliability. To address this issue, this study proposes a semi-supervised soft-voting ensemble (semi-supervised SVE) model for TBM rock mass classification, utilizing limited labeled data (i.e., data including measured rock mass grades) and extensive unlabeled data (i.e., data lacking measured rock mass grades). The model is initially pre-trained with limited labeled data, which include rock mass grades derived from a national code based on rock mass integrity and physical properties. The pre-trained model is then used to identify the rock mass grades of unlabeled data to produce pseudo labels. Multiple training iterations are conducted to incorporate the pseudo-labeled data, continuously expanding the training dataset of the proposed model. By integrating the boosting and bagging ensemble strategies through the soft voting method, the robustness of the proposed model in rock mass classification is enhanced. A high-quality dataset from the Yinchuo-Jiliao Project in China is used for illustration. The proposed model outperforms alternative supervised and unsupervised models on both labeled and unlabeled data. The superior performance on labeled data is directly evident from evaluation indices including precision, recall, and F1 score, whereas its effectiveness on unlabeled data is demonstrated indirectly through rock-breaking indices. A 5-fold random cross-validation shows that the soft-voting ensemble classifier is more robust than individual classifiers. In addition, the confidence level of the proposed model matches actual classification accuracy, providing useful insights into model uncertainty for decision-makers.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"162 ","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of tunnel face rock mass classification using an ensemble model enhanced by feature cross based on TBM boring data","authors":"Lei-jie Wu ,&nbsp;Le-chen Wang ,&nbsp;Shuang-jing Wang ,&nbsp;Yu Wang ,&nbsp;Xu Li","doi":"10.1016/j.tust.2025.106647","DOIUrl":"10.1016/j.tust.2025.106647","url":null,"abstract":"<div><div>In tunneling engineering, accurate prediction of rock mass classification at the tunnel face is crucial to ensure construction safety and efficiency. In this study, we propose a novel approach utilizing Tunnel Boring Machine (TBM) excavation data collected from the Yin-Chao project in China, to develop a rock mass classification model. The dataset comprises 401 sensors installed on the TBM, providing data on various mechanical control parameters during the excavation process. We conduct thorough data preprocessing, including feature selection and valid data extraction, to prepare the dataset for model training. Additionally, we implement an ensemble learning framework, integrating a feature cross enhanced network (E-DeepFM) with base models such as Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Decision Tree (DT), to enhance predictive performance. The results demonstrate that the integration of E-DeepFM significantly improves the predictive precision of the base models, particularly for SVM and KNN, as the <em>F</em>1 score from 0.827 to 0.877 for the SVM model and from 0.923 to 0.944 for the KNN model. Furthermore, interpretability analysis using SHAP values highlights the importance of cross features in enhancing model performance. This study contributes to the field of tunneling engineering by providing a reliable method for real-time rock mass classification during TBM excavation, thereby enhancing construction safety and efficiency.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"162 ","pages":"Article 106647"},"PeriodicalIF":6.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143824472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical solution of the evolution of railway subgrade settlement induced by shield tunnelling beneath considering soil stress release","authors":"Yao Shan ,&nbsp;Guankai Wang ,&nbsp;Weifan Lin ,&nbsp;Shunhua Zhou ,&nbsp;Frank Rackwitz","doi":"10.1016/j.tust.2025.106607","DOIUrl":"10.1016/j.tust.2025.106607","url":null,"abstract":"<div><div>With the increasing number of railway intersection projects, the ground movement induced by the construction of shield tunnels affects the safety of the existing railway subgrade. Consequently, the reliable prediction of settlement evolution in railway subgrades is important. Considering the influence of various construction parameters, this paper presents an analytical method for calculating the time-dependent evolution of railway subgrade settlement induced by shield tunneling beneath based on the Mindlin solution. In this method, the time parameters are introduced through coordinate transformation. It models soil loss due to shield tunneling as the gradual release of stress in the surrounding soil, treating the released stress as an equivalent additional load on the tunnel’s surrounding soil. Finally, the proposed method is validated by comparing it with existing literature and applied in a case study of a shield tunnel crossing a railway subgrade on the southeast coast. The results demonstrate that this method effectively predicts subgrade settlement induced by shield tunneling beneath, offering valuable guidance for engineering practice.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"162 ","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}