Tunnelling and Underground Space Technology最新文献

{"title":"Cataclastic deformation and alteration induced fault water inrush: Cross effect, hazard characteristics and identification method","authors":"","doi":"10.1016/j.tust.2024.105968","DOIUrl":"10.1016/j.tust.2024.105968","url":null,"abstract":"<div><p>Faults are the main adverse geological causing water inrush hazards in tunnels. The complexity and diversity of fault-induced water inrush often results in hazard response delays. This study proposes a typical hazard mode, i.e., the Cataclastic Deformation and Alteration Induced Fault Water Inrush (CD/A-WI). Integrating mineralogy, geochemistry, and microstructural analysis, this method investigates the cross effect of cataclastic deformation and alteration on the fault water inrush hazard. Microstructural analysis revealed the fault damage mechanism, while mineralogy and geochemistry clarified the surrounding rock’s alteration. The cataclastic deformation and alteration resulted in numerous fractures and fragmented breccias, creating primary fluid pathways that accelerate alteration processes. Consequently, alteration weakens the surrounding rock’s mechanical strength, intensifying rock mass failure and leading to water inrush hazards after tunnel excavation. The typical characteristics of the CD/A-WI include an abundance of breccias with cataclastic and loose structures and a notable increase in altered mineral types and contents, evidenced by microstructural elements like cataclastic flows. This mode was validated through its application in the Gaoligongshan Tunnel. The method and finding provide a basis for understanding the geological factors in tunnel hazard and offer valuable insights for designing and constructing comparable engineering projects.</p></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950053","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":"Compressive strength detection of tunnel lining using hyperspectral images and machine learning","authors":"","doi":"10.1016/j.tust.2024.105979","DOIUrl":"10.1016/j.tust.2024.105979","url":null,"abstract":"<div><p>Traditional tunnel lining strength detection techniques are mostly contact-based, with relatively low detection efficiency. This study innovatively proposes hyperspectral imaging method to rapidly detect tunnel concrete lining strength from a machine vision perspective. Hyperspectral cameras were employed in indoor experiments to capture hyperspectral images of concrete specimens with different compressive strength levels. The differences of concrete strength based on hyperspectral reflectance characteristics were analysed using hyperspectral images and machine learning algorithms. Firstly, the K-Nearest Neighbors (KNN) classification algorithm was used to predict the classification of the concrete hyperspectral dataset with accuracy mostly exceeding 90 %. The results indicate distinctive differences in hyperspectral reflectance characteristics among concrete specimens. Furthermore, compressive strength prediction of different concrete specimens was carried out using Principal component regression (PCR), Partial least squares regression (PLSR), and Least Squares Support Vector Machine (LSSVM) machine learning models on both original and Savitzky-Golay(S-G) processed spectral data. LSSVM and PLSR models performed excellently in the visible light spectrums(400–1000 nm), with LSSVM excelling in the near-infrared spectrums(900–1700 nm). Finally, the feasibility of using Hyperspectral imaging(HSI) technology to detect tunnel lining strength was demonstrated at the shield tunnel model site. The predicted results were validated by combining with strength values measured by the rebound hammer, and presented promoising research path for automated non-destructive detection of concrete tunnel lining strength.</p></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950351","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":"Monitoring interaction of shallowly buried, large-section, and long-distance twin box jacking tunnels with small spacing under the Beijing-Hangzhou Grand Canal","authors":"","doi":"10.1016/j.tust.2024.105973","DOIUrl":"10.1016/j.tust.2024.105973","url":null,"abstract":"<div><p>Field tunnel monitoring of stresses and strains is of critical importance for understanding the interaction behavior of twin tunnels, but it is rarely done for projects of twin box jacking tunnels. In this study, the optical frequency domain reflectometer (OFDR) sensing technique was employed to conduct field monitoring for a project of twin box jacking tunnels with a small spacing (5.4 m), a shallow minimum cover depth (4.39 m), a large cross-section (9.8 m × 5.9 m), and a long jacking distance (215.9 m) crossing the Beijing-Hangzhou Grand Canal. A scheme of laying circumferential and axial “W” shaped optical fibers was proposed to monitor the accumulated vertical misalignment and rotation of tunnel. Results indicate that small spacing could cause more significant compressive strains in the earlier constructed tunnel, and the maximum compression positions were in the crown and the wall near the second tunnel. In addition, the rotation angle decreased with the increment of tunnel spacing, when the spacing was lower than one times the box width. In the end, an axial monitoring scheme was discussed to evaluate the tunnel opening, and a horizontal misalignment scheme was derived to accomplish the full monitoring of tunnel misalignment in three directions.</p></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141951614","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":"Identification of rock discontinuities by coda wave analysis while borehole drilling in deep buried tunnels","authors":"","doi":"10.1016/j.tust.2024.105969","DOIUrl":"10.1016/j.tust.2024.105969","url":null,"abstract":"<div><p>Rock discontinuities are widely and randomly developed in deep buried tunnels and have a profound impact on construction safety, support design, and geological hazard prevention. Identifying these discontinuities while drilling is a critical but challenging task. This paper presents an innovative approach that leverages the coda wave analysis method to assess rock discontinuities during impact drilling in deep tunnels. Our method is facilitated by a drilling process detection (DPD) system, which records coda waves generated by impact drilling pit sources. We observe that coda waves, with dominant frequencies of 500 Hz to 1 kHz, can be detected in heterogeneous rock discontinuities featuring decimeter-scale discontinuities. Building upon this observation, we introduce a rock discontinuity index (RDI), which is a novel metric designed to highlight low-velocity anomalies associated with rock discontinuities along boreholes. To validate the efficacy of the approach, we conduct numerical simulations of checkerboard and random realistic rock models and perform field tests in deep buried tunnels. A borehole optical scanner is utilized to compare the identified rock discontinuity results. The results affirm that the coda wave-based method can reliably identify rock discontinuities by RDI peaks, even under highly heterogeneous geological conditions. The proposed method offers a practical means for identifying discontinuities and assessing geological conditions during impact borehole drilling.</p></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141951615","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":"Index for assessing spalling in tunnel lining based on displacement monitoring and crack mapping","authors":"","doi":"10.1016/j.tust.2024.105975","DOIUrl":"10.1016/j.tust.2024.105975","url":null,"abstract":"<div><p>Lining deformation, cracks, and spalling are the most crucial items to be checked during structural safety inspections of tunnels in operations. These three faults are often cited as indicators of structural safety and are used to determine the need for maintenance or repair operations. However, existing evaluation criteria do not account for how the quality of a tunnel’s lining structure varies over its life cycle. The present study examined the 30-year construction and repair records of a highway tunnel in southeastern Taiwan. This study also quantitatively analyzed the relationships among tunnel displacement, lining cracks, and concrete spalling. The results revealed that compared with the associated displacement, tunnel deformation after overall profile translation was compensated for was more representative of tunnel structural safety and lining spalling potential. Specially, when the cumulative tunnel deformation reaches 1 % equivalent radius and when the deformation rate reaches 40E-6/year, the potential for lining spalling is notable. Concrete spalling is common near closed, radial, acute-angle intersecting cracks in a tunnel and also in the vicinity of circumferential construction joints. If a tunnel intersects the potential sliding surface of a moving mass on a slope, the vicinity of this intersection should be evaluated for concrete spalling. The spalling potential of concrete increases with the crack density. For a tunnel in operations, crack densities of 1.0 and 1.5 m/m² and associated change rates reach 2.0 and 3.0 m/m²/year can be applied as thresholds for grading moderate and high spalling potential, respectively, in the tunnel lining.</p></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950352","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":"Shallow-buried subway station construction period: Comparison of intelligent early warning and optimization strategies for surface deformation risk","authors":"","doi":"10.1016/j.tust.2024.105978","DOIUrl":"10.1016/j.tust.2024.105978","url":null,"abstract":"<div><p>In the context of rapid urbanization, ensuring the safety of subway station construction is vital for the stability of urban infrastructure. Conventional intelligent construction risk prediction methods typically utilize large volumes of monitoring data for training to enhance model accuracy, often neglecting the relationship between the time-series width of the data and the prediction results. To address this issue, and to better serve the construction of shallow-buried subway stations at an earlier stage, this study proposed a bagging algorithm with an improved base learner combination strategy. This algorithm forms the basis for the Bayesian optimization-based random forest model (BA-RF) and the marine predators’ algorithm-optimized random forest model (MPA-RF). By examining trends in real-time data, such as surface and building settlements above the main structure, displacement at key points of the vertical shafts, and crown settlement, the short-term maximum values of key displacements were predicted. This study emphasized the impact of the time width of the input data on the accuracy of the predictive models. Through empirical analysis, the optimal time-series width was determined, allowing for effective short-term structural risk prediction and early warning using a smaller time series. The findings indicate that the BA-RF model, utilizing an improved base learner strategy, achieves higher prediction accuracy than the more complex MPA-RF model, effectively mitigating overfitting. Specifically, when the preceding measured data time widths were 5, 15, and 25 d, the BA-RF model’s mean absolute error was 0.168, 0.160, and 0.349, respectively, whereas the root mean square error was 0.853, 0.463, and 0.509, respectively. Combined with short-term future prediction applications at construction sites, it was demonstrated that appropriately selecting the time-series width can significantly enhance prediction accuracy even with relatively small data volumes. This study provides a method for selecting training data for intelligent risk management during subway station construction and offers practical data selection strategies for risk assessment in other large-scale construction projects. Thus, this method has significant scientific and practical applications.</p></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141960295","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":"An ensemble learning paradigm for subsurface stratigraphy from sparse measurements and augmented training images","authors":"","doi":"10.1016/j.tust.2024.105972","DOIUrl":"10.1016/j.tust.2024.105972","url":null,"abstract":"<div><p>The performance of computer vision-based techniques for stratigraphic modeling relies heavily on qualified training images to capture the complex stratigraphic connectivity. In geotechnical engineering, only limited training images are available for a specific site. Stochastic simulation modelling based on limited training data may be biased as the collected images that reflect prior geological knowledge may not encompass all potential stratigraphic patterns. Therefore, it is crucial to establish a high-quality, domain-specific training image database for effective stratigraphic modelling. In this study, an ensemble learning paradigm is proposed to tackle this issue and develop subsurface geological cross-sections from sparse data by reconstruction and redistribution of stratigraphic statistics revealed from limited training images. A domain-specific training image database is first established using generative adversarial networks (GAN) that enable the generation of arbitrary sized image samples from a single training image. Subsequently, multiple qualified image samples that are compatible with site-specific data are adaptively selected and utilized for the ensemble learning of geological cross-sections. The performance of the proposed framework is demonstrated using real geological cross-sections collected from a reclamation site and a tunnelling project in Hong Kong. The results indicate that the proposed method can effectively generate diverse image samples that encompass stratigraphic features beyond those reflected in a single training image. More importantly, the ensemble learning framework can capture the complex spatial stratigraphic connectivity of soil layers with enhanced prediction accuracy.</p></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950350","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":"Investigation on seepage evolution property of surrounding rock under the tunneling and water surge","authors":"","doi":"10.1016/j.tust.2024.105970","DOIUrl":"10.1016/j.tust.2024.105970","url":null,"abstract":"<div><p>The tunnel water surge seriously threatens the tunneling safety. Based on COMSOL numerical simulation, the tunneling model is established and the tunneling stress evolution law is studied. Based on the tunneling stress variation law, the water seepage test of tunnel surrounding rock is designed and carried out. It is studied that tunneling stress can be divided into the area of in-situ stress, supporting effect and stress stabilization. Moreover, the tunneling stress increases sharply in the supporting effect area. In the mechanical loading early stage of seepage test, that is, the in-situ stress area, the rock deformation and permeability are relatively stable. The post-peak failure stages are divided into passive and active unloading stages of <span><math><mrow><mfenced><mrow><msub><mi>σ</mi><mn>1</mn></msub><mo>-</mo><msub><mi>σ</mi><mn>3</mn></msub></mrow></mfenced></mrow></math></span>. In the <span><math><mrow><mfenced><mrow><msub><mi>σ</mi><mn>1</mn></msub><mo>-</mo><msub><mi>σ</mi><mn>3</mn></msub></mrow></mfenced></mrow></math></span> passive unloading stage, that is, the supporting effect area, the strain and permeability increase dramatically. It reflects the crack propagation and water surge process of tunnel surrounding rock. In the <span><math><mrow><mfenced><mrow><msub><mi>σ</mi><mn>1</mn></msub><mo>-</mo><msub><mi>σ</mi><mn>3</mn></msub></mrow></mfenced></mrow></math></span> active unloading stage, that is, in the stress stabilization area, the permeability first slows down and then rapidly decreases. It reflects the tunnel water surge weakening under the lining support action. Meanwhile, based on the rock porosity and statistical damage variables, the permeability evolution model is established. By comparation, the model calculated results are consistent to the seepage test data, which verifies the model validity. The permeability mathematical model can serve as a reference for the prediction of tunnel water surge node.</p></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141731966","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":"Long-term mechanical properties of steel fiber reinforced concrete under sulfuric acid attack","authors":"","doi":"10.1016/j.tust.2024.105977","DOIUrl":"10.1016/j.tust.2024.105977","url":null,"abstract":"<div><p>Steel fiber reinforced concrete (SFRC) has significant advantages for preparing pipes, however, concrete sewer pipes are susceptible to deterioration caused by biological acids (i.e., sulfuric acid). In this study, the mechanical properties—including cube compressive strength, axial compressive and flexural properties, and relative dynamic elastic modulus—of SFRC exposed to sulfuric acid for 36 months were monitored. Further, the evolution of the morphology, alkalinity, and mineral phases was also monitored. According to the morphology and pH evolution, SFRC showed rapid corrosion after 12 months of exposure, and the thicknesses of damaged and transition layers reached approximately 2 and 8 mm, respectively, after 36 months. Further, gypsum was formed and deposited on the specimen surface after exposure to sulfuric acid. Although the SFRC did not deteriorate after 12 months of exposure and still showed good mechanical properties, the cube compressive strength of SFRC showed a slight decrease after 36 months of exposure; however, the axial compressive load and flexural load capacities improved, and the flexural toughness also increased as a result of the exposure to sulfuric acid. This study provides valuable evidence for the potential application of SFRC in sewage environments.</p></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141729757","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":"Spatial distribution of excess pore water pressure and slurry infiltration zone in slurry shield tunneling","authors":"","doi":"10.1016/j.tust.2024.105965","DOIUrl":"10.1016/j.tust.2024.105965","url":null,"abstract":"<div><p>In the construction of slurry shield tunneling, the infiltration of slurry will cause excess pore water pressure in the surrounding soil. The distribution of excess pore water pressure and slurry infiltration zone are closely related to the stability of the tunnel face. Considering the influence of cutter head rotation and slurry specific gravity on pressure boundary conditions, this study proposed a multi-field coupling model to describe the dynamic transmission of excess pore water pressure and distribution of slurry infiltration range in three-dimensional. The temporal and spatial variation of soil pores characteristics parameters and slurry rheological properties owing to the deposition and diffusion of slurry particles is considered. The proposed model is verified by the in-situ testing measurements from in Beijing East Sixth Ring Road reconstruction project. In the prediction results, the spatial distribution of excess pore water pressure around the tunnel face appears bubble-shaped, and the shape of the slurry infiltration zone is close to flattened cake. The range of pressure dissipation and the thickness of particles infiltration zone are positively correlated with soil permeability coefficient, slurry pressure, while negatively correlated with the mass concentration of slurry. In the cases of low-permeability soil, appropriately increasing the content of slurry particles can improve the compactness of the filter cake.</p></div>","PeriodicalId":49414,"journal":{"name":"Tunnelling and Underground Space Technology","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141729756","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}