Pub Date : 2025-01-07DOI: 10.1016/j.undsp.2024.10.003
Heonmoo Kim, Yosoon Choi
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.
{"title":"3D location estimation and tunnel mapping of autonomous driving robots through 3D point cloud registration on underground mine rampways","authors":"Heonmoo Kim, 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}
Pub Date : 2024-12-30DOI: 10.1016/j.undsp.2024.09.004
Wenli Liu, Yafei Qi, Fenghua Liu
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.
{"title":"Reliable prediction for TBM energy consumption during tunnel excavation: A novel technique balancing explainability and performance","authors":"Wenli Liu, Yafei Qi, 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}
Pub Date : 2024-12-25DOI: 10.1016/j.undsp.2024.10.002
Zhutian Pan , Xuepeng Zhang , Yujing Jiang , Bo Li , Naser Golsanami , Hang Su , Yue Cai
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.
{"title":"High-precision segmentation and quantification of tunnel lining crack using an improved DeepLabV3+","authors":"Zhutian Pan , Xuepeng Zhang , Yujing Jiang , Bo Li , Naser Golsanami , Hang Su , 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}
Pub Date : 2024-12-18DOI: 10.1016/j.undsp.2024.08.009
Iman R. Kivi , Victor Vilarrasa , Kwang-Il Kim , Hwajung Yoo , Ki-Bok Min
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.
{"title":"Bleed-off control on post-injection seismicity in enhanced geothermal systems","authors":"Iman R. Kivi , Victor Vilarrasa , Kwang-Il Kim , Hwajung Yoo , 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}
Pub Date : 2024-12-16DOI: 10.1016/j.undsp.2024.11.001
Shuhong Wang , Bowen Han , Jianhui Jiang , Natalia Telyatnikova
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.
{"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 , Bowen Han , Jianhui Jiang , 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}
Pub Date : 2024-12-04DOI: 10.1016/j.undsp.2024.10.001
Tao Yan , Shui-Long Shen , Annan Zhou
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.
{"title":"Data augmentation-assisted muck image recognition during shield tunnelling","authors":"Tao Yan , Shui-Long Shen , 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}
Pub Date : 2024-11-30DOI: 10.1016/j.undsp.2024.09.003
Hao Luo , Ming Tao , Zhixian Hong , Gongliang Xiang , Chengqing Wu
The dynamic response and failure characteristics of tunnels vary significantly under various dynamic disturbances. These characteristics are crucial for assessing structural stability and designing effective support for surrounding rock. In this study, the theoretical solution for the dynamic stress concentration factor (DSCF) of a circular tunnel subjected to cylindrical and plane P-waves was derived using the wave function expansion method. The existing equivalent blast stress wave was optimized and the Ricker wavelet was introduced to represent the seismic stress waves. By combining Fourier transform and Duhamel’s integral, the transient response of the underground tunnel under near-field blasts and far-field earthquakes was determined in both the frequency and time domains. The theoretical results were validated by comparing them with those obtained from numerical simulations using ANSYS LS-DYNA software. Numerical simulations were conducted to further investigate the damage characteristics of the underground tunnel and evaluate the effect of initial stress on structural failure under both types of disturbances. The theoretical and numerical simulation results indicated that the differences in the dynamic response and damage characteristics of the underground tunnel were primarily due to the curvature of the stress waves and transient load waveform. The locations of the maximum DSCF values differed between near-field blasts and far-field earthquakes, whereas the minimum DSCF values occurred at the same positions. Without initial stress, the blast stress waves caused spalling damage to the rock mass on the wave-facing side. Shear failure occurred near the areas with maximum DSCF values, and tensile failure occurred near the areas with minimum DSCF values. In contrast, damage occurred only near the areas with maximum DSCF values under seismic stress waves. Furthermore, the initial stress exacerbated spalling and shear damage while suppressing tensile failure. Hence, the blast stress waves no longer induced tensile failure on the tunnel sidewalls under initial stress.
{"title":"Analysis of the dynamic response and damage characteristic for the tunnel under near-field blasts and far-field earthquakes","authors":"Hao Luo , Ming Tao , Zhixian Hong , Gongliang Xiang , Chengqing Wu","doi":"10.1016/j.undsp.2024.09.003","DOIUrl":"10.1016/j.undsp.2024.09.003","url":null,"abstract":"<div><div>The dynamic response and failure characteristics of tunnels vary significantly under various dynamic disturbances. These characteristics are crucial for assessing structural stability and designing effective support for surrounding rock. In this study, the theoretical solution for the dynamic stress concentration factor (DSCF) of a circular tunnel subjected to cylindrical and plane P-waves was derived using the wave function expansion method. The existing equivalent blast stress wave was optimized and the Ricker wavelet was introduced to represent the seismic stress waves. By combining Fourier transform and Duhamel’s integral, the transient response of the underground tunnel under near-field blasts and far-field earthquakes was determined in both the frequency and time domains. The theoretical results were validated by comparing them with those obtained from numerical simulations using ANSYS LS-DYNA software. Numerical simulations were conducted to further investigate the damage characteristics of the underground tunnel and evaluate the effect of initial stress on structural failure under both types of disturbances. The theoretical and numerical simulation results indicated that the differences in the dynamic response and damage characteristics of the underground tunnel were primarily due to the curvature of the stress waves and transient load waveform. The locations of the maximum DSCF values differed between near-field blasts and far-field earthquakes, whereas the minimum DSCF values occurred at the same positions. Without initial stress, the blast stress waves caused spalling damage to the rock mass on the wave-facing side. Shear failure occurred near the areas with maximum DSCF values, and tensile failure occurred near the areas with minimum DSCF values. In contrast, damage occurred only near the areas with maximum DSCF values under seismic stress waves. Furthermore, the initial stress exacerbated spalling and shear damage while suppressing tensile failure. Hence, the blast stress waves no longer induced tensile failure on the tunnel sidewalls under initial stress.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"21 ","pages":"Pages 331-351"},"PeriodicalIF":8.2,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143146750","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}
Pub Date : 2024-11-26DOI: 10.1016/j.undsp.2024.08.008
Yu Miao, Han-Wen Ji, Yang Shi
Assembled monolithic subway station partly synthesizes the advantages of cast-in-place and precast subway stations. However, the related seismic response analysis considering the influences of vertical ground motion and aboveground structure is still scant. In this study, we firstly performed the statistical analysis on bidirectional bedrock ground motion parameters (response spectrum, duration and envelope function) using KiK-net data, and obtained some suggested values of the above parameters. Then, four sets of artificial bedrock ground motions with statistical meanings were generated and a three-dimensional finite element analysis of the seismic response of an existing two-story three-span subway station was conducted. The main results are summarized below. (1) The significant damage to assembled monolithic station under far-field strong motion firstly occurred at side middle slab; middle slab, upper column and related grouting sleeve joints were more damage-prone. (2) When horizontal peak ground acceleration stayed constant, overall the damage of far-field motion was stronger than that of near-fault motion. (3) Vertical ground motion obviously accelerated the damage progresses of various structural members at various positions, then aboveground structure further enhanced the damages and vertical displacement responses of parts of top slab. (4) For the axial force time-history of upper column during far-field strong motion, aboveground structure uplifted the baseline, and vertical ground motion increased the amplitude and advanced the obvious drop of the baseline, among which the latter effect of vertical ground motion on assembled monolithic station was stronger than that on cast-in-place station. (5) Vertical ground motion enhanced inter-story displacement during far-field strong motion, among which the influence on the upper story of assembled monolithic station could be obviously amplified by aboveground structure, and the amplification effect lagged behind the influence of vertical ground motion. Based on the results of this study, some suggestions for the seismic design of subway station are also provided.
{"title":"Bidirectional seismic response of assembled monolithic subway station-aboveground structure system under artificial bedrock ground motions","authors":"Yu Miao, Han-Wen Ji, Yang Shi","doi":"10.1016/j.undsp.2024.08.008","DOIUrl":"10.1016/j.undsp.2024.08.008","url":null,"abstract":"<div><div>Assembled monolithic subway station partly synthesizes the advantages of cast-in-place and precast subway stations. However, the related seismic response analysis considering the influences of vertical ground motion and aboveground structure is still scant. In this study, we firstly performed the statistical analysis on bidirectional bedrock ground motion parameters (response spectrum, duration and envelope function) using KiK-net data, and obtained some suggested values of the above parameters. Then, four sets of artificial bedrock ground motions with statistical meanings were generated and a three-dimensional finite element analysis of the seismic response of an existing two-story three-span subway station was conducted. The main results are summarized below. (1) The significant damage to assembled monolithic station under far-field strong motion firstly occurred at side middle slab; middle slab, upper column and related grouting sleeve joints were more damage-prone. (2) When horizontal peak ground acceleration stayed constant, overall the damage of far-field motion was stronger than that of near-fault motion. (3) Vertical ground motion obviously accelerated the damage progresses of various structural members at various positions, then aboveground structure further enhanced the damages and vertical displacement responses of parts of top slab. (4) For the axial force time-history of upper column during far-field strong motion, aboveground structure uplifted the baseline, and vertical ground motion increased the amplitude and advanced the obvious drop of the baseline, among which the latter effect of vertical ground motion on assembled monolithic station was stronger than that on cast-in-place station. (5) Vertical ground motion enhanced inter-story displacement during far-field strong motion, among which the influence on the upper story of assembled monolithic station could be obviously amplified by aboveground structure, and the amplification effect lagged behind the influence of vertical ground motion. Based on the results of this study, some suggestions for the seismic design of subway station are also provided.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"21 ","pages":"Pages 291-312"},"PeriodicalIF":8.2,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147148","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}
Pub Date : 2024-11-20DOI: 10.1016/j.undsp.2024.08.007
Haoyu Wang , Jichen Xie , Jinyang Fu , Cong Zhang , Dingping Chen , Zhiheng Zhu , Xuesen Zhang
Small-section hydraulic tunnels are characterized by small spaces and various section forms, under complex environments, which makes it difficult to carry out an inspection by the mobile acquisition equipment. To resolve these problems, an arbitrarily adjustable camera module deployment method and the corresponding automatic image acquisition equipment with multi-area array cameras are proposed and developed. Such method enables the acquisition of full-length surface images of the hydraulic tunnels with different cross-section forms and diameters by a one-way travel, and the overlap rate and accuracy of the acquired image sets meet the requirements of three-dimensional reconstruction and panoramic image generation. In addition, to improve the speed and accuracy of traditional algorithms for tunnel surface defects detection, this paper proposes an improved YOLOv5s-DECA model. The algorithm introduces DenseNet to optimize the backbone feature extraction network and incorporates an efficient channel attention ECA module to make a better extraction of features of defects. The experimental results show that mAP, and F1-score of YOLOv5-DECA are 73.4% and 74.6%, respectively, which are better than the common model in terms of accuracy and robustness. The proposed YOLOv5-DECA has great detection performance for targets with variable shapes and can solve the problem of classification imbalance in surface defects. Then, by combining YOLOv5-DECA with the direction search algorithm, a “point-ring-section” method is established to allow rapid identification of common surface defects by detecting them layer by layer with the bottom image of the stitched panorama as the seed. The presented method in this paper effectively solves the problem that a single image fails to show the overall distribution of the defects and their accurate positioning in a whole large tunnel section and the effective features of defects in an excessively large panoramic image size are difficult to be captured by the neural network. Field applications demonstrated that the presented method is adequate for high-precision and intelligent surface defect detection and positioning for different small-section hydraulic tunnels such as circular, arch-wall, and box-shaped hydraulic tunnels.
{"title":"Rapid acquisition and surface defects recognition based on panoramic image of small-section hydraulic tunnel","authors":"Haoyu Wang , Jichen Xie , Jinyang Fu , Cong Zhang , Dingping Chen , Zhiheng Zhu , Xuesen Zhang","doi":"10.1016/j.undsp.2024.08.007","DOIUrl":"10.1016/j.undsp.2024.08.007","url":null,"abstract":"<div><div>Small-section hydraulic tunnels are characterized by small spaces and various section forms, under complex environments, which makes it difficult to carry out an inspection by the mobile acquisition equipment. To resolve these problems, an arbitrarily adjustable camera module deployment method and the corresponding automatic image acquisition equipment with multi-area array cameras are proposed and developed. Such method enables the acquisition of full-length surface images of the hydraulic tunnels with different cross-section forms and diameters by a one-way travel, and the overlap rate and accuracy of the acquired image sets meet the requirements of three-dimensional reconstruction and panoramic image generation. In addition, to improve the speed and accuracy of traditional algorithms for tunnel surface defects detection, this paper proposes an improved YOLOv5s-DECA model. The algorithm introduces DenseNet to optimize the backbone feature extraction network and incorporates an efficient channel attention ECA module to make a better extraction of features of defects. The experimental results show that mAP, and F1-score of YOLOv5-DECA are 73.4% and 74.6%, respectively, which are better than the common model in terms of accuracy and robustness. The proposed YOLOv5-DECA has great detection performance for targets with variable shapes and can solve the problem of classification imbalance in surface defects. Then, by combining YOLOv5-DECA with the direction search algorithm, a “point-ring-section” method is established to allow rapid identification of common surface defects by detecting them layer by layer with the bottom image of the stitched panorama as the seed. The presented method in this paper effectively solves the problem that a single image fails to show the overall distribution of the defects and their accurate positioning in a whole large tunnel section and the effective features of defects in an excessively large panoramic image size are difficult to be captured by the neural network. Field applications demonstrated that the presented method is adequate for high-precision and intelligent surface defect detection and positioning for different small-section hydraulic tunnels such as circular, arch-wall, and box-shaped hydraulic tunnels.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"21 ","pages":"Pages 270-290"},"PeriodicalIF":8.2,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147147","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}
Pub Date : 2024-11-15DOI: 10.1016/j.undsp.2024.08.006
Ziqi Liu , Xiaohui Cheng , Jie Xiao
A thermal–hydraulic-mechanical (THM) field coupling three-dimensional (3D) finite element (FE) program is developed for complex THM coupled problems in engineering practice. This 3D program incorporates a thermo-mechanical coupled constitutive model known as Tsinghua-Thermo-Soil. The program solves the hydraulic and mechanical fields together and the thermal field separately (i.e., the T-HM scheme). Validation is done against the analytical solutions of one-dimensional (1D) steady-state forced convection-conduction and 1D thermo-elastic consolidation processes. Additionally, effects of the dynamic viscosity coefficient and thermal expansion coefficient of water are analyzed for 1D thermo-elastic consolidation coupled problem. It is revealed that for soils in long-term consolidation and under high loading levels, convective effect is significant and the temperature distribution differs from that obtained by considering only heat conduction. A coupled THM problem of foundations involving an actual engineering energy raft is analyzed. The response of a linear elastic foundation under the combined effect of assumed long-term cyclic thermal loading and mechanical loading process is studied. The results demonstrate that heating leads to the locally accumulation of excess pore pressure and reduces settlement and differential settlement, while cooling has the opposite effects. Due to the heat injected into the foundation exceeding the heat extracted, the ground temperature within several meters of burial depth gradually increases over time, meanwhile the average differential settlement decreases.
{"title":"Development of an innovative THM fully coupled three-dimensional finite element program and its applications","authors":"Ziqi Liu , Xiaohui Cheng , Jie Xiao","doi":"10.1016/j.undsp.2024.08.006","DOIUrl":"10.1016/j.undsp.2024.08.006","url":null,"abstract":"<div><div>A thermal–hydraulic-mechanical (THM) field coupling three-dimensional (3D) finite element (FE) program is developed for complex THM coupled problems in engineering practice. This 3D program incorporates a thermo-mechanical coupled constitutive model known as Tsinghua-Thermo-Soil. The program solves the hydraulic and mechanical fields together and the thermal field separately (i.e., the T-HM scheme). Validation is done against the analytical solutions of one-dimensional (1D) steady-state forced convection-conduction and 1D thermo-elastic consolidation processes. Additionally, effects of the dynamic viscosity coefficient and thermal expansion coefficient of water are analyzed for 1D thermo-elastic consolidation coupled problem. It is revealed that for soils in long-term consolidation and under high loading levels, convective effect is significant and the temperature distribution differs from that obtained by considering only heat conduction. A coupled THM problem of foundations involving an actual engineering energy raft is analyzed. The response of a linear elastic foundation under the combined effect of assumed long-term cyclic thermal loading and mechanical loading process is studied. The results demonstrate that heating leads to the locally accumulation of excess pore pressure and reduces settlement and differential settlement, while cooling has the opposite effects. Due to the heat injected into the foundation exceeding the heat extracted, the ground temperature within several meters of burial depth gradually increases over time, meanwhile the average differential settlement decreases.</div></div>","PeriodicalId":48505,"journal":{"name":"Underground Space","volume":"21 ","pages":"Pages 352-369"},"PeriodicalIF":8.2,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143146710","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}
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