Tunnelling and Underground Space Technology最新文献_第8页

Enhancing convergence speed and accuracy of virtual field optimization method for microseismic source location in tunnels

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology

Pub Date : 2025-01-20 DOI: 10.1016/j.tust.2025.106366

Jian He , Huailiang Li , Binhong Li , Nuwen Xu , Junnan Wen , Yuedong Li

Accurate and rapid microseismic source location is the foundation for tunnel rockburst warning. Here, we present a novel location strategy that employs an improved mayfly algorithm (IMA) to enhance the convergence speed and accuracy of the virtual field optimization method (VFOM) for tunnel microseismic events. By optimizing the initial position of the mayfly population and the moving velocity of mayfly personals, we develop an IMA with superior convergence speed in searching for source locations. The proposed method utilizes paired microseismic receivers in the tunnel monitoring array to create hyperbolic surfaces. Then, the IMA is employed to rapidly and accurately determine the intersection point of all hyperbolic surfaces, defining it as the microseismic source location. We compare the IMA-VFOM with different error levels in seismic wave velocity or arrival time against other traditional location approaches based on travel time differences. The results confirm that the IMA-VFOM’s convergence speed is, on average, more than 4 times that of the MA-VFOM algorithm. Compared to conventional methods, the IMA-VFOM method demonstrates higher location accuracy and stability. The average location error of the proposed method is

4.0043 m

when applied to real rockburst microseismic events in tunnels.

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引用次数: 0

Tunnel intersection mechanics: Closed-form pseudo-3D approximations for deformation modeling and shear-failure prediction

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology

Pub Date : 2025-01-20 DOI: 10.1016/j.tust.2025.106394

Andreas Michael

Deformation modeling of underground tunnel intersections attempts to provide answers on the occurrence of localized structural instabilities under different, and possibly dynamically-changing, in-situ conditions. Design decisions hinge on these findings; since much of the stresses underground are compressive, shear-failure predictions provide outlines for maintaining structural stability on the intersections of underground tunnel excavations in anisotropic rock masses, such as those made using tunnel-boring machines (TBMs).

Three-dimensional (3D) deformations around the circumference of the orthogonal intersection plane of two tunnels are modeled using a pseudo-3D approximation approach established in petroleum engineering, which adjusts for stress interferences coming from each tunnel. The rationale for such approach is that the normal stresses on the circumference of the primary “Tunnel A” are used as inputs to evaluate the stresses on the base of a smaller, secondary “Tunnel B” which approximates the two tunnels’ intersection plane.

The resultant closed-form expressions are used as a boundary condition in a Mohr-Coulomb-type model for shear failures, in a cylindrical coordinate system. Dimensionless plots (“allowable stress diagrams”) provide the means to visually recognize whether the induced stresses on the tunnel intersection can trigger shear failure, or not. The dynamic impact of sediment settling is quantitatively assessed and non-orthogonal tunnel intersections are discussed.

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引用次数: 0

Fine controlled blasting of subsurface excavation for subway stations in soft–hard mixed-medium rock mass

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology

Pub Date : 2025-01-20 DOI: 10.1016/j.tust.2025.106407

Wanzhi Zhang , Jie Mei , Keguo Sun , Bangshu Xu

Drilling and blasting excavation methods along with primary arch-cover primary supports are frequently employed in the construction of urban subway stations. However, traditional blasting methods fail to control tunnel face flatness, overbreak, and underbreak in soft–hard mixed-medium rock mass owing to symmetric and invariable blasting parameters. The Shishan Road Station of Qingdao Metro Line 6 is located in a soft–hard mixed-medium rock mass. Traditional blasting excavation methods result in considerable over-excavation of the soft rock on the one side, forming a concave inside, and minor over- and under-excavation of the hard rock on the opposite side, forming a convex outside. Herein, numerical models were developed to analyze the rock damage caused by contour blasting in soft–hard mixed-medium rock mass. Different perimeter hole spacings, burden thicknesses, and charge weights were investigated to identify the optimal parameters. Based on these models, this study proposes an asymmetric blasthole pattern and charge parameters, such as a smaller spacing and charge weight on the soft rock side and deeper hole lengths on the hard rock side. In addition, higher delay times were suggested to control the blasting vibration. Field tests showed that the optimized blasting scheme effectively controlled the flatness, overbreak, and underbreak. The utilization rate of blast holes increased by 5%, the average overbreak area decreased by 57.3%, and underbreak did not occur. The blasting energy of a single initiation and the proportion of low-frequency energy decreased significantly, resulting in better control of rock damage caused by blasting vibrations.

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引用次数: 0

Time-dependent seismic fragility analysis of subway station structure subjected to chloride-induced corrosion

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology

Pub Date : 2025-01-20 DOI: 10.1016/j.tust.2025.106376

Zilan Zhong, Jiaxi Guo, Bu Zhang, Xiuli Du

Subway station structures near coast are at risk of corrosion caused by chloride, resulting in material and structural component deterioration over time and impacting overall performance during earthquakes. This study proposes a numerical framework for the time-dependent seismic fragility analysis of subway station structures, considering chloride-induced corrosion, based on the IDA method. This study utilizes finite element simulations of typical subway station structures in Qingdao, Shandong, China, focusing on nonlinear dynamic interactions between soil and structure, as well as the impact of chloride-induced corrosion on aging effects. The time-dependent damage states within subway station structures are determined through a nonlinear static pushover analysis. Subsequently, the IDA method is employed to generate time-dependent seismic fragility curves and surfaces specific to subway station structures. The numerical results indicate that the impact of chloride-induced corrosion on the subway station structure cannot be ignored. In the corrosion environment, the seismic performance assessment of subway station structures must take into account time-dependent damage states resulting from the degradation of material properties and the reduction in seismic capacity. The probability of a subway station structure exceeding various damage states monotonically increases during its service life. The subway station structure primarily suffers minor to moderate damage under the ground motion with a return period of 2450 or 10000 years, as it reaches its design service life.

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引用次数: 0

Probability analysis on tunnels in heterogeneous strata based on borehole data-driven conditional random fields and convolutional neural network

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology

Pub Date : 2025-01-18 DOI: 10.1016/j.tust.2025.106402

Gaoyu Ma , Chuan He , Zhengshu He , Rongmin Bai , Guowen Xu

Tunnels in heterogeneous strata always encounter spatially varied geological formations, causing asymmetric responses and localized failure in the supporting structure. The homogeneity assumption for surrounding strata, commonly adopted in tunnel design and construction, will neglect the inherent spatial uncertainty of rock mass and lead to the overestimation in tunnel bearing capacity. The conventional stochastic calculations for analyzing tunnel performance in heterogeneous strata also fail to reflect the statistical asymmetry in mechanical behaviors of supporting structure. With the application of mechanized equipment with built-in sensors in drilling and blasting construction, rock parameters at borehole locations can be promptly derived through the drilling data. This systematic on-site monitoring necessitates a rational and stationary extrapolation using rock parameters from the excavation face to the surrounding strata, as the inversion results provide a more precise depiction of the properties of surrounding strata and enable the dynamic design for supporting structure during construction. Therefore, an innovative approach was proposed in this research to conduct probability analysis on the mechanical behaviors of tunnels in heterogeneous strata based on conditional random field models. The statistical characteristics of random variables in these fields were constrained by the derived rock parameters on the excavation face using Hoffman method. The probability distributions of mechanical behaviors were analyzed for tunnels with both symmetric and asymmetric anchor cable systems. In addition, a trained convolutional neural network (CNN) model was implemented to reduce the computational resources required in massive numerical simulations. The tunnel deformation at different circumferential locations can be predicted with an acceptable accuracy and minimal time consumption that significantly facilitated the probabilistic assessments.

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引用次数: 0

Axial chain rockbursts in deep tunnels excavated via drilling and blasting

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology

Pub Date : 2025-01-18 DOI: 10.1016/j.tust.2025.106395

Hong-Pu Li , Ben-Guo He , Xiang-Rui Meng , Shengcun Yan , Tao Chen

Chain rockbursts have a long duration and significant hazards, severely affecting construction progress, yet their occurrence patterns and formation mechanisms remain unclear. Monitoring was conducted on a deeply buried tunnel in southwest China for axial chain rockbursts (ACRs) occurrences. The recorded ACRs (23 weak, 3 moderate, and 3 intense) were analyzed to reveal their patterns of occurrence, geological characteristics, and mechanisms of formation. ACRs were studied through geological surveys, analysis of on-site failure characteristics, and a series of laboratory tests. The findings indicate that ACRs are most likely to occur near river valleys, faults, and geological contact zones, where the overburden is significant, and the direction of major stress is perpendicular to the tunnel axis. In ACRs-prone regions, the content of brittle minerals in the surrounding rock tends to be relatively high. At the site studied, the proportion of plagioclase in the diorite ranges from 55 % to 65 %. ACRs are likely to be triggered when the dip of structural planes forms a small angle with the principal stress, and when their strike is parallel (or nearly parallel) to the tunnel axis, or when a group of structural planes intersects the tunnel axis at a small angle and is distributed along it. During tunnel excavation in areas prone to ACRs, appropriate measures should be sufficiently robust and ductile, aimed at enhancing the strength and ductility of the surrounding rock, with support structures closely following the excavation face. This investigation contributes to our understanding of ACRs and may help in designing methods for predicting and preventing their occurrence.

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引用次数: 0

Two-scale basalt fibers reinforced concrete shield tunneling segments for underground constructions 地下建筑双尺度玄武岩纤维增强混凝土盾构管片

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology

Pub Date : 2025-01-17 DOI: 10.1016/j.tust.2025.106383

Min Hou , Jiang Feng , Hougai Shi , Ruiyi Jiang , Hengyi Zhu , Hualin Fan

In this paper, two-scale Basalt fibers reinforced polymer (BFRP) rebars reinforced arch (BRRA) technique was developed through applying BFRP rebars to macroscopically reinforce concrete shield tunneling segments (STSs). BFRP minibars were mixed into concrete as the micro reinforcements. Six two-scale BRRAs were prepared with content of minibars changing from 0%, 0.5% to 1.5%. Full-scale flexural experiments were performed to reveal the mechanical performances of the BRRAs. With higher minibar content, the utilization ratio of the BFRP rebars is much greater and the BRRA has longer elastoplastic deformation, higher bearing capacity and better ductility. Long elastic deformation of BFRP rebars and reinforcing mechanism of BFRP minibars improve the bearing capacity and ductility of the BRRA.

本文通过将双尺度玄武岩纤维增强聚合物（BFRP）钢筋应用于混凝土盾构管段的宏观加固，发展了双尺度玄武岩纤维增强聚合物（BFRP）钢筋加固拱（BRRA）技术。将BFRP迷你棒掺入混凝土中作为微增强筋。制备了6种二标BRRAs，迷你棒的含量从0%、0.5%到1.5%不等。进行了全尺寸的弯曲实验，以揭示brra的力学性能。微棒含量越高，BFRP筋的利用率越高，BRRA的弹塑性变形时间越长，承载能力越高，延性越好。BFRP筋的长弹性变形和BFRP小筋的加固机理提高了BRRA的承载力和延性。

引用次数: 0

Real-time forecast of tunnel fire scenario and hazard based on external smoke images 基于外部烟雾图像的隧道火灾情景及危害实时预测

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology

Pub Date : 2025-01-17 DOI: 10.1016/j.tust.2025.106377

Jiaqi Cheng , Nie Yang , Saihua Jiang , Caiyi Xiong

In tunnel fires, conventional detectors are often obstructed by smoke and heat accumulation, impeding decision-making for firefighting and evacuation efforts. This work proposed a real-time prediction of tunnel fire heat release rate (HRR) and location by using external smoke images and deep learning algorithms. A 100-m tunnel was simulated. By varying fire HRR, location, and fuel type, a database of about 1.6 million external smoke images was formed, which was used to train a convolutional neural network (CNN) model and produced a R² of 0.99 and a small MSE less than 0.03. Results demonstrated that this intelligent method can accurately identify transient tunnel fire power and fire source location, with the HRR prediction error being less than 20 % and location error less than 1.5 m, irrespective of the stage of fire development or whether the fire is in a stationary or moving state. Results also showed that there are two ways of model training to ensure prediction accuracy while saving computational cost: 1) training by both front and side views of smoke at a single tunnel gate, and 2) training by only front views of smoke at both tunnel gates. This work contributed an intelligent method to assess tunnel fire scenarios and hazards from a safe distance, showcasing its potential application in smart tunnel fire protection and firefighting systems.

在隧道火灾中，传统的探测器经常受到烟雾和热量积累的阻碍，阻碍了消防和疏散工作的决策。本文提出了一种利用外部烟雾图像和深度学习算法实时预测隧道火灾热释放率（HRR）和位置的方法。模拟了一条100米长的隧道。通过改变火灾HRR、位置和燃料类型，形成约160万张外部烟雾图像的数据库，用于训练卷积神经网络（CNN）模型，得到R2为0.99，MSE小于0.03的小模型。结果表明，无论火灾处于何种发展阶段，无论火灾处于静止状态还是运动状态，该智能方法都能准确识别隧道瞬态火源和火源位置，HRR预测误差小于20%，定位误差小于1.5 m。结果还表明，在保证预测精度的同时节省计算成本，模型训练有两种方式：1)同时使用单个隧道门的正面和侧面烟雾视图进行训练；2)仅使用两个隧道门的正面烟雾视图进行训练。本研究提供了一种智能方法，从安全距离评估隧道火灾情景和危险，展示了其在智能隧道防火和消防系统中的潜在应用。

{"title":"Real-time forecast of tunnel fire scenario and hazard based on external smoke images","authors":"Jiaqi Cheng , Nie Yang , Saihua Jiang , Caiyi Xiong","doi":"10.1016/j.tust.2025.106377","DOIUrl":"10.1016/j.tust.2025.106377","url":null,"abstract":"<div><div>In tunnel fires, conventional detectors are often obstructed by smoke and heat accumulation, impeding decision-making for firefighting and evacuation efforts. This work proposed a real-time prediction of tunnel fire heat release rate (HRR) and location by using external smoke images and deep learning algorithms. A 100-m tunnel was simulated. By varying fire HRR, location, and fuel type, a database of about 1.6 million external smoke images was formed, which was used to train a convolutional neural network (CNN) model and produced a R<sup>2</sup> of 0.99 and a small MSE less than 0.03. Results demonstrated that this intelligent method can accurately identify transient tunnel fire power and fire source location, with the HRR prediction error being less than 20 % and location error less than 1.5 m, irrespective of the stage of fire development or whether the fire is in a stationary or moving state. Results also showed that there are two ways of model training to ensure prediction accuracy while saving computational cost: 1) training by both front and side views of smoke at a single tunnel gate, and 2) training by only front views of smoke at both tunnel gates. This work contributed an intelligent method to assess tunnel fire scenarios and hazards from a safe distance, showcasing its potential application in smart tunnel fire protection and firefighting systems.</div></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":"158 ","pages":"Article 106377"},"PeriodicalIF":6.7,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988132","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}

引用次数: 0

Investigating the mechanical behavior and failure mechanisms of rock bolts subjected to multiple impact loads using a newly developed experimental test apparatus 采用新研制的试验装置，研究了岩石锚杆在多重冲击载荷作用下的力学行为和破坏机制

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology

Pub Date : 2025-01-17 DOI: 10.1016/j.tust.2025.106388

Guiyang Yuan , Fuqiang Gao , Jinfu Lou , Jinghe Yang , Shuangyong Dong , Linpo Si

Understanding the behavior and failure mechanisms of rock bolts subjected to multiple impact loads is essential for improving the safety and performance of underground support systems. In this study, a series of experimental tests were performed to investigate the deformation, energy absorption, and failure mechanisms of pre-tensioned rock bolts under multiple impacts. The result indicates that with an increasing number of impacts, the rebound amount of rock bolts gradually increases, while the plastic deformation decreases. The energy absorbing ratio of the rock bolt decreases as the energy releasing ratio increases, leading to a decline in the rock bolt’s ability to absorb energy and an increase in brittleness. It was observed that the accumulation of plastic deformation consumes the yielding and strengthening stages of the rock bolt, making it prone to fracture at smaller deformations in later stages. It was also found that the final elongation of a rock bolt subjected to multiple impacts leading to fracture is significantly higher compared to a rock bolt subjected to a pure pull-out test. These insights have important implications for the design of rock bolt support systems in underground excavations.

了解锚杆在多重冲击载荷作用下的行为和破坏机制，对于提高地下支护系统的安全性和性能至关重要。本文通过一系列试验研究了预应力锚杆在多重冲击作用下的变形、吸能及破坏机理。结果表明：随着冲击次数的增加，锚杆回弹量逐渐增大，塑性变形减小；锚杆吸能比随着能量释放比的增大而减小，导致锚杆吸能能力下降，脆性增大。结果表明，塑性变形的累积消耗了锚杆的屈服和强化阶段，使得锚杆在后期较小变形时容易发生断裂。研究还发现，在多次冲击导致断裂的情况下，锚杆的最终伸长率明显高于单纯拉拔试验的锚杆。这些见解对地下基坑锚杆支护系统的设计具有重要的指导意义。

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引用次数: 0

Advancing spatial-temporal rock fracture prediction with virtual camera-based data augmentation 基于虚拟摄像机的数据增强技术推进岩石断裂时空预测

IF 6.7 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Tunnelling and Underground Space Technology

Pub Date : 2025-01-17 DOI: 10.1016/j.tust.2025.106400

Jiawei Xie , Baolin Chen , Jinsong Huang , Yuting Zhang , Cheng Zeng

Predicting rock fractures in unexcavated areas is a critical yet challenging aspect of geotechnical projects. This task involves forecasting the fracture mapping sequences for unexcavated rock faces using the sequences from excavated ones, which is well-suited for spatial–temporal deep learning techniques. Fracture mapping sequences for deep learning model training can be achieved based on field photography. However, the main obstacle lies in the insufficient availability of high-quality photos. Existing data augmentation techniques rely on slices taken from Discrete Fracture Network (DFN) models. However, slices differ significantly from actual photos taken from the field. To overcome this limitation, this study introduces a new framework that uses Virtual Camera Technology (VCT) to generate “virtual photos” from DFN models. The external (e.g., camera location, direction) and internal parameters (e.g., focal length, resolution, sensor size) of cameras can be considered in this method. The “virtual photos” generated from the VCT and conventional slicing method have been extensively compared. The framework is designed to adapt to any distribution of field fractures and camera settings, serving as a universal tool for practical applications. The whole framework has been packaged as an open-source tool for rock “photos” generation. An open-source benchmark database has also been established based on this tool. To validate the framework’s feasibility, the Predictive Recurrent Neural Network (PredRNN) method is applied to the generated database. A high degree of similarity is observed between the predicted mapping sequences and the ground truth. The model successfully captured the dynamic changes in fracture patterns across different sections, thereby confirming the framework’s practical utility. The source code and dataset can be freely downloaded from GitHub repository (https://github.com/GEO-ATLAS/Rock-Camera).

预测未开挖区域的岩石裂缝是岩土工程中一个关键而又具有挑战性的方面。该任务涉及利用已开挖岩面序列预测未开挖岩面的裂缝映射序列，这非常适合于时空深度学习技术。用于深度学习模型训练的裂缝映射序列可以基于现场摄影实现。然而，主要障碍在于高质量照片的可用性不足。现有的数据增强技术依赖于从离散裂缝网络（DFN）模型中获取的切片。然而，切片与实地拍摄的实际照片有很大不同。为了克服这一限制，本研究引入了一个使用虚拟相机技术（VCT）从DFN模型生成“虚拟照片”的新框架。该方法可以考虑相机的外部参数（如相机位置、方向）和内部参数（如焦距、分辨率、传感器尺寸）。对VCT和传统切片方法生成的“虚拟照片”进行了广泛的比较。该框架设计用于适应任何现场裂缝分布和相机设置，可作为实际应用的通用工具。整个框架被打包成一个用于生成岩石“照片”的开源工具。基于该工具还建立了一个开源基准数据库。为了验证该框架的可行性，将预测递归神经网络（PredRNN）方法应用于生成的数据库。在预测的映射序列和地面真实值之间观察到高度的相似性。该模型成功捕获了不同截面裂缝模式的动态变化，从而证实了该框架的实用性。源代码和数据集可以从GitHub存储库（https://github.com/GEO-ATLAS/Rock-Camera）免费下载。

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引用次数: 0