Underground Space最新文献

{"title":"Evaluation of greenhouse gas emissions in subway tunnel construction","authors":"Yalin Guo ,&nbsp;Chen Dong ,&nbsp;Zheng Chen ,&nbsp;Shulei Zhao ,&nbsp;Wenhao Sun ,&nbsp;Wei He ,&nbsp;Lei Zhang ,&nbsp;Yiyuan Wang ,&nbsp;Nan Hu ,&nbsp;Chun Guo","doi":"10.1016/j.undsp.2024.12.001","DOIUrl":"10.1016/j.undsp.2024.12.001","url":null,"abstract":"<div><div>This study evaluates the greenhouse gas (GHG) emissions associated with the construction of subway tunnels, aiming to identify the primary sources of emissions and provide insights into emission reduction strategies. Using the civil engineering construction of specific tunnels of a subway line in Guangdong Province, China, as a case study, this research quantitatively analyzes the composition of GHG emissions across three stages: upstream building materials production, building materials transportation, and on-site construction. The results indicate that upstream building materials production and on-site construction collectively account for over 95% of the total GHG emissions during tunnel construction. The analysis further reveals that a small proportion of building materials and construction machinery accounts for the majority of total GHG emissions during tunnel construction, aligning with the Pareto principle. The findings emphasize the importance of accurate evaluation of high-impact building materials and construction machinery, particularly in contexts where basic energy consumption data are limited. Strategies such as utilizing recycled materials and enhancing machinery efficiency can lead to significant emission reductions. For instance, achieving a recycling rate of 10% to 30% for steel and concrete can reduce total GHG emissions from tunnel construction by 5.51% to 9.94%, while improving machinery efficiency by 10% to 30% can reduce emissions by up to 2.29%. These findings provide a scientific basis for low-carbon subway tunnel construction.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"22 ","pages":"Pages 263-279"},"PeriodicalIF":8.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental study on the modulus of soil reaction for plastic pipes buried in lightweight cellular concrete backfill","authors":"Yu-qiu Ye ,&nbsp;Jie Han ,&nbsp;Brad Dolton ,&nbsp;Md Wasif Zaman ,&nbsp;Robert L. Parsons","doi":"10.1016/j.undsp.2024.11.003","DOIUrl":"10.1016/j.undsp.2024.11.003","url":null,"abstract":"<div><div>The modulus of soil reaction, representing the stiffness of a soil surrounding pipes, is a critical parameter in the design of buried flexible pipes. This study conducted plate loading tests on corrugated polyvinyl chloride, smooth polyvinyl chloride, and high-density polyethylene pipes buried in lightweight cellular concrete (LCC) backfills at densities of 400, 475, 550, and 650 kg/m³ to investigate the pipe deformation behavior and moduli of soil reaction. In addition, this study examined the effects of the narrow trench condition on the pipe deformation and modulus of soil reaction. In these tests, the vertical and horizontal diameter changes of pipes under the vertical pressures applied through a hydraulic jack were measured. Test results reveal that the average moduli of soil reaction of plastic pipes within a wide trench backfilled by the LCCs at densities of 400, 475, 550, and 650 kg/m³ were back-calculated as 66, 99, 133, and 205 MPa, respectively, using the modified Iowa formula. Furthermore, the back-calculated moduli of soil reaction for LCCs exhibited linear relationships with their densities and unconfined compressive strengths and were higher than the recommended values for the commonly used soil backfills. Based on the vertical deformation criterion of 5% pipe diameter, the ultimate bearing capacities of flexible pipes buried in wide LCCs at densities of 475, 550, and 650 kg/m³ exceeded 500 kPa. The LCC with a narrow trench exhibited a lower modulus of soil reaction and ultimate bearing capacity but a larger pipe diameter change.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"22 ","pages":"Pages 153-167"},"PeriodicalIF":8.2,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental investigation and limit analysis of shield tunnel face failure mechanism in sand","authors":"Mengzhe Huo ,&nbsp;Weizhong Chen ,&nbsp;Jingqiang Yuan ,&nbsp;Guojun Wu ,&nbsp;Yunfa Li ,&nbsp;Yubiao Liu","doi":"10.1016/j.undsp.2024.11.002","DOIUrl":"10.1016/j.undsp.2024.11.002","url":null,"abstract":"<div><div>Shield tunneling in urban underground space necessitates tight control over support pressure at the tunnel face and a thorough insight into ground collapse mechanisms. This study conducts a model test and a theoretical validation to clarify the mechanisms of face failure and subsequent ground collapse in sand during earth pressure balanced shield (EPBS) tunneling operations. The experiment investigates the changes in soil pressure and surface subsidence patterns during shield tunneling and collapse stages, to elucidate the entire process of ground collapse triggered by shield tunneling disturbances. A novel methodology was proposed to ensure effective verification of the rotational failure mechanism, focusing on the collapse pit morphology and the critical collapse pressure. The results indicate that: (1) precise control over the shield tunneling and screw conveyor rotation speeds is essential for tunnel face stability; (2) the sand with low moisture content is prone to stepwise ground collapse under shield tunneling disturbances; (3) soil pressure measurements at the cutterhead are more indicative of face failure and imminent ground collapse than those from the soil chamber; (4) there is a consistent alignment between the rotational failure mechanism and observed collapse pit morphology, albeit with slight variations due to tunneling disturbances; (5) the experimentally determined critical collapse pressure is higher than the theoretical prediction, indicating an underestimation of risks in the current model. The study advances the understanding of the face failure mechanisms in shield tunnels, thereby providing insights into the design and safety of shield tunneling within engineering practices.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"22 ","pages":"Pages 137-152"},"PeriodicalIF":8.2,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multidimensional seismic fragility analysis of subway station structures using the adaptive bandwidth kernel density estimation and Copula function","authors":"Chunyi Cui ,&nbsp;Jingtong Zhao ,&nbsp;Minze Xu ,&nbsp;Chengshun Xu ,&nbsp;Hailong Liu ,&nbsp;Kunpeng Wang","doi":"10.1016/j.undsp.2024.10.004","DOIUrl":"10.1016/j.undsp.2024.10.004","url":null,"abstract":"<div><div>Structural damages during an earthquake are typically controlled by seismic demands, which are represented by the combination of amplitude of ground motion and cyclic load effects. Since traditional methods normally assume the lognormal distributions of seismic demands and resistance parameters, uncertainties are inevitably induced in the seismic fragility analysis. In this paper, the Copula function and adaptive bandwidth kernel density estimation method (ABKDE) are used to establish a novel multidimensional seismic fragility analysis framework. Based on the results of incremental dynamic analysis for subway station structures, ABKDE is adopted to establish single-parameter seismic fragility curves for both the maximum inter-story drift ratio (MIDR) and cumulated dissipated hysteretic energy (CDHE), respectively. Subsequently, the Copula function is used to formulate a bivariate seismic fragility function considering the correlations among seismic demand measures and establish the corresponding fragility curves. Finally, comparative analyses are conducted to evaluate seismic fragility curves using Copula-based dual and single-parameter damage models as well as the traditional damage models. It is found that the seismic fragility analysis method using the Copula function has the ability to gain a comprehensive consideration of the MIDR and CDHE during the damage process of subway station structures. Moreover, this newly developed seismic fragility analysis framework can capture the influence of the correlation between deformation and energy under various peak ground accelerations on structural damage. Thus, this framework can provide a scientific basis for predicting structural damage in subway stations subjected to varying intensities of ground motion while considering multiple damage indicators.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"22 ","pages":"Pages 110-123"},"PeriodicalIF":8.2,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D location estimation and tunnel mapping of autonomous driving robots through 3D point cloud registration on underground mine rampways","authors":"Heonmoo Kim,&nbsp;Yosoon Choi","doi":"10.1016/j.undsp.2024.10.003","DOIUrl":"10.1016/j.undsp.2024.10.003","url":null,"abstract":"<div><div>In this study, we developed a three-dimensional (3D) location estimation and tunnel mapping system to locate an autonomous robot in the rampway of an underground mine using 3D point cloud registration. A 3D point cloud of the mine tunnel was measured using a 3D light detection and ranging (LiDAR) sensor and registered using the iterative closest point (ICP) algorithm to estimate the 3D pose of the robot. This was combined with two-dimensional LiDAR, inertial measurement unit, and encoder sensors to estimate the 3D trajectory of the robot. Additionally, the 3D tunnel mapping was performed using the 3D trajectory of the robot and the 3D point cloud data of the tunnel. A comparison of the tunnel maps created using conventional surveying equipment and the robot indicated a mapping error of 0.2275 m and localization error of 0.2465 m confirming the excellent overall tunnel mapping and localization performance. The tunnel mapping areas were further compared by selecting areas with relatively high and low ICP matching accuracies; the calculated errors were 0.6186 and 0.2257 m in the areas with low and high accuracies, respectively. Furthermore, the accuracy of the ICP matching tended to be low in areas where the change in the pitch angle of the robot was large.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"22 ","pages":"Pages 1-20"},"PeriodicalIF":8.2,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliable prediction for TBM energy consumption during tunnel excavation: A novel technique balancing explainability and performance","authors":"Wenli Liu,&nbsp;Yafei Qi,&nbsp;Fenghua Liu","doi":"10.1016/j.undsp.2024.09.004","DOIUrl":"10.1016/j.undsp.2024.09.004","url":null,"abstract":"<div><div>Recently, AI-based models have been applied to accurately estimate tunnel boring machine (TBM) energy consumption. Although data-driven models exhibit strong predictive capabilities, their outputs derived from “black box” processes are challenging to interpret and generalize. Consequently, this study develops an XGB_MOFS model that cooperates extreme gradient boosting (XGBoost) and multi-objective feature selection (MOFS) to improve the accuracy and explainability of energy consumption prediction. The XGB_MOFS model includes: (1) a causal inference framework to identify the causal relationships among influential factors, and (2) a MOFS approach to balance predictive performance and explainability. Two case studies are carried out to verify the proposed method. Results show that XGB_MOFS achieves a high degree of accuracy and robustness in energy consumption prediction. The XGB_MOFS model, balancing accuracy with explainability, serves as an effective and feasible tool for regulating TBM energy consumption.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"22 ","pages":"Pages 77-95"},"PeriodicalIF":8.2,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-precision segmentation and quantification of tunnel lining crack using an improved DeepLabV3+","authors":"Zhutian Pan ,&nbsp;Xuepeng Zhang ,&nbsp;Yujing Jiang ,&nbsp;Bo Li ,&nbsp;Naser Golsanami ,&nbsp;Hang Su ,&nbsp;Yue Cai","doi":"10.1016/j.undsp.2024.10.002","DOIUrl":"10.1016/j.undsp.2024.10.002","url":null,"abstract":"<div><div>Current semantic segmentation models have limitations in addressing tunnel lining crack, such as high complexity, misidentification, or inability to detect tiny cracks in specific practical scenarios, which is crucial for precise assessment of tunnel lining health. We developed a novel approach called EDeepLab, aiming to achieve a higher precision detection and segmentation of lining surface crack. EDeepLab improves upon the original DeepLabV3+ framework by replacing its backbone network with an optimized lightweight EfficientNetV2. The amount of EfficientNetV2 block computation is reduced and a self-designed shallow feature fusion module is used to merge the layers to enhance parameter utilization efficiency. Furthermore, the normalization-based attention module and convolutional block attention module attention mechanisms are integrated to classify and process both high and low dimensional information features. This allows for comprehensive utilization of global semantic information and channel information, thereby enhancing the model’s feature extraction capability. Results in constructed metro-tunnel crack dataset demonstrate that the number of parameters is reduced from 144.45 M in the DeepLabV3+ to 99.80 M in the EDeepLab. EDeepLab achieves a mean intersection over union of 84.77%, mean pixel accuracy of 94.96%, and frames per second of 18.52 f/s. The proposed EDeepLab outperforms other models including U-Net, ResNet and fully convolutional networks in the quantitative analysis of tiny cracks and noise interference.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"22 ","pages":"Pages 96-109"},"PeriodicalIF":8.2,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bleed-off control on post-injection seismicity in enhanced geothermal systems","authors":"Iman R. Kivi ,&nbsp;Victor Vilarrasa ,&nbsp;Kwang-Il Kim ,&nbsp;Hwajung Yoo ,&nbsp;Ki-Bok Min","doi":"10.1016/j.undsp.2024.08.009","DOIUrl":"10.1016/j.undsp.2024.08.009","url":null,"abstract":"<div><div>Deep geothermal reservoirs could provide widespread access to clean and renewable energy around the world. However, hydraulic stimulation of these reservoirs to create sufficient injectivity and heat extraction has frequently induced earthquakes during and, in particular, after reservoir stimulation, which raises public concerns. This study aims to provide a possible explanation for post-injection seismicity and understand how it responds to well bleed-off as a common industrial practice to control such seismic activity. To this end, we perform coupled hydromechanical simulations of reservoir stimulation in a conceptual model comprising a deep granitic reservoir intersected by a network of long fractures and a nearby, critically-stressed fault. We find a combination of mechanisms triggering post-injection seismicity with time delays of several months after stopping injection: (1) poroelastic stressing that transmits normal and shear stress and causes undrained pressure buildup on the fault, (2) fracture-dominated pore pressure migration toward the fault, and (3) long-lasting along-the-fault pressure diffusion toward pre-stressed fault patches, promoted by dilation-induced fault permeability changes. In this setting, bleed-off causes rapid pressure decline in the near-wellbore region but marginal pressure changes farther away. The resulting attenuations of pore pressure and shear stress on the fault plane may not be enough to prevent fault reactivation. Bleed-off may counterintuitively accelerate fault slip by rapid relaxation of normal stress on the fault, which not only brings the stress state closer to failure conditions, but also accelerates pore pressure diffusion along the fault by slightly increasing its permeability. We show that bleed-off can effectively control post-injection seismicity only if rupture initiates from a structure in close proximity and with sufficient hydraulic connection to the wellbore. Future research should be directed toward the optimization of stimulation and post-stimulation design in light of the involved triggering mechanisms and through effective combination with subsurface characterization to control post-injection seismicity.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"22 ","pages":"Pages 21-38"},"PeriodicalIF":8.2,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning and FEM-driven analysis and optimization of deep foundation pits in coastal area: A case study in Fuzhou soft ground","authors":"Shuhong Wang ,&nbsp;Bowen Han ,&nbsp;Jianhui Jiang ,&nbsp;Natalia Telyatnikova","doi":"10.1016/j.undsp.2024.11.001","DOIUrl":"10.1016/j.undsp.2024.11.001","url":null,"abstract":"<div><div>To comply with the requirements of sustainable energy development, China has proposed the strategic goal of achieving dual carbon. Systematic and scientific development and utilization of urban underground space will provide critical support for reducing carbon emissions and enhancing carbon sink capacity. This paper examines the transmission and distribution ring pit project of Fuzhou Binhai New City, China, divided into four regions, where the selection of the support system is determined by the project’s characteristics. Stability is analyzed using in-situ monitoring data from the R4 area, and the deformation of the support system is predicted using machine learning. The predicted maximum lateral deformation of the support system may reach the warning value, necessitating corrections to the existing support parameters. On this basis, the deformation during foundation pit excavation is simulated, and the effects of key factors such as pile geometric parameters, pile penetration depth, and anchor cable insertion ratio on the deformation are analyzed. The study shows that pile deformation control is optimal when the support parameters include a 1.3 insertion ratio, a 20° anchor cable angle, and a 200 kN prestressing force, enabling the construction of the remaining three areas. This study can serve as a valuable reference for the design and analysis of deep foundation pits under special stratigraphic conditions in coastal areas.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"22 ","pages":"Pages 55-76"},"PeriodicalIF":8.2,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data augmentation-assisted muck image recognition during shield tunnelling","authors":"Tao Yan ,&nbsp;Shui-Long Shen ,&nbsp;Annan Zhou","doi":"10.1016/j.undsp.2024.10.001","DOIUrl":"10.1016/j.undsp.2024.10.001","url":null,"abstract":"<div><div>This paper proposed a framework for muck types identification based on data augmentation-assisted image recognition during shield tunnelling. The muck pictures were collected from the shield monitoring system above the conveyor belt. The data augmentation operations were then used to increase the quality of the original images. Furthermore, the Bayesian optimisation algorithm was employed to adjust the parameters of augmenters and highlight the features of the photos. The deep image recognition algorithms (AlexNet and GoogLeNet) were trained and enhanced by the augmentation images, which were used to establish the muck types identification models and assessed by the evaluation indices. Model efficiency was analysed through the performance and time cost of training and validation processes to select the optimal model for muck types identification. Results showed that the performance of identification models could be highly increased by data augmentation with Bayesian optimisation, and the enhanced GoogLeNet performed the highest efficiency for muck types identification.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"21 ","pages":"Pages 370-383"},"PeriodicalIF":8.2,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}