Proceedings of the 4th International Civil Engineering and Architecture Conference
CEAC 2024, 15–17 March, Seoul, South Korea
- 2025
- Book
- Editor
- Marco Casini
- Book Series
- Lecture Notes in Civil Engineering
- Publisher
- Springer Nature Singapore
About this book
This book collects the scientific proceedings presented during the “2024 The 4th International Civil Engineering and Architecture Conference” held in Seoul, South Korea, in March 2024 with the aim of showing the latest advancements in theoretical and applied research in the architecture, engineering, and construction sector (AEC). The book is organized into four main parts, namely (1) sustainable urban planning and architecture; (2) architectural and environmental design; (3) built environment materials and construction technology; and (4) civil engineering and construction management. The goal of the book is to provide readers with an overview of the ongoing transformation of the AEC industry presenting a thorough investigation of the emerging trends in the fields of green building design, construction, and operation.
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Table of Contents
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Frontmatter
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Structural Health Monitoring and Structural Reliability Assessment
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Frontmatter
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Intelligent Monitoring and Vision Based Vibration Measurement on Bridges
Weixing Hong, Xiaoqing Jia, Ahmed Silik, Mohammad Noori, Wael A. AltabeyThis chapter explores the application of computer vision (CV) technology for intelligent monitoring and vibration measurement on bridges. Traditional methods, such as contact-based sensors, are limited by complex installations and measurement inaccuracies. In contrast, CV-based methods provide non-contact, high-accuracy displacement measurements, enabling real-time structural health assessment. The study details the procedure for CV-based displacement measurement, including target tracking algorithms, camera calibration, and displacement calculation. It also discusses the analysis of fused displacement data using correlation dimension and wavelet analysis to detect and quantify bridge damage. The proposed method offers a comprehensive approach to bridge monitoring, facilitating early damage diagnosis and extending the lifespan of bridge structures.AI Generated
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AbstractIn managing the integrity of bridge structures, damage detection and safety evaluation are crucial. The most important factors that contribute to bridge deterioration are environmental and operational variability. Early monitoring is crucial to maintain and protect the bridge structure over its lifetime. This work therefore intends to use computer vision-based vibration measurement to detect and analyze the vibrations of bridges. The captured data is processed using advanced algorithms to extracted features-based displacement measurement to identify patterns and anomalies in the vibration data and finally assess the bridge condition. This approach can handle the complicated situations by increasing computational efficiency, treating uncertainties, and streamlining the decision-making process. Also, the approach provides useful insights and future trends for applying ML and vibration-based damage detection methods to bridge health monitoring. -
Applications of Structural Reliability Methods in Deformation and Buckling Analysis of Structures
Junho ChunThis chapter delves into the crucial role of structural reliability methods in evaluating the probability of failure within complex systems. It begins by defining structural reliability and its importance in design and safety considerations. The text then explores various methods for estimating structural reliability, including approximation methods like FORM and SORM, simulation techniques such as Monte Carlo Simulation and Subset Simulation, and metamodel-based approaches like Adaptive Kriging Monte Carlo Simulation and Hybrid Active Learning-based Kriging. Through detailed analysis and comparisons, the chapter highlights the strengths and limitations of each method, providing valuable insights into their practical implications. The discussion is complemented by numerical applications, such as the analysis of a 3D frame structure and a grid-shell structure, which demonstrate the effectiveness and computational efficiency of these methods in real-world scenarios. The chapter concludes by emphasizing the importance of accurate and efficient reliability analysis in modern engineering designs, particularly as structures become more complex.AI Generated
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AbstractEnsuring the resilience of contemporary society hinges upon achieving adequate reliability levels in structural systems during design and maintenance decisions. These processes are crucial for mitigating the risk of unforeseen failures, thus averting potential catastrophic damage or losses. Consequently, effective strategies for reliability assessment and optimization within the design phase of structures and other engineering systems are paramount. This paper delves into various reliability analysis methods, encompassing simulation-based, approximation, and Metamodel-based approaches, to enhance understanding of structural performance under uncertainties. The research reveals that while approximation methods may face accuracy challenges due to the nonlinearity of limit-state functions, they exhibit notable computational efficiency for designs with relatively small to medium-sized variables. Conversely, the Metamodel method may necessitate multiple design experiments for constructing accurate Kriging models, yet it demonstrates commendable computational efficiency and accuracy in structural reliability assessment. The paper further provides a comparative analysis of accuracy and efficiency through numerical examples of frame structure and grid-shell structure reliability assessment. -
Assessment and Retrofitting of Historical Over-Capping Timber Structure
Harun Alrasyid, Wahyuniarsih Sutrisno, Mudji IrmawanThe chapter delves into the structural assessment and retrofitting of historical over-capping timber structures, specifically focusing on the Surabaya Pasar Turi Railway Station. Built in 1900, this station features over-capping timber structures that have survived over a century. The chapter discusses the importance of structural assessments to ensure the safety and preservation of these historic buildings. It details the methods used, including visual inspections, ultrasonic pulse velocity tests, and humidity tests, to evaluate the condition of the teakwood structures. The chapter also highlights the significance of combining destructive and non-destructive testing to obtain accurate mechanical properties of the material. The findings from these tests form the basis for structural analysis and the design of retrofitting measures. The chapter provides a detailed account of the structural inspection process, the condition of the timber structures, and the design considerations for retrofitting. It offers valuable insights into the preservation of historic railway infrastructure and the application of modern engineering techniques to ensure their longevity.AI Generated
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AbstractThis paper shows the assessment process of a 100 year-old historical over-capping timber structure. Visual observation, destructive, and non-destructive tests were performed to obtain the material properties of the timber structures. Based on the visual inspection, several of the element timber structures experienced deterioration. The destructive samples were obtained to observe the mechanical properties of timber material. The samples were acquired at a location that did not disturb structure stability. The mechanical properties of timber material, such as bending stress, tension stress parallel to the grain, compression stress parallel to the grain, and compression stress perpendicular to the grain, are examined to gain the actual strength of the material based on disturbed samples. Ultrasonic Pulse Velocity and humidity tests were performed on-site as part of non-destructive tests. The structure analysis was performed based on existing material data. To obtain nominal stress, this basis design stress was multiplied with several coefficients such as wet service factor, temperature factor, beam stability factor, size factor, flat use factor, incising factor, repetitive member factor, and column stability factor. The structure analysis showed that the columns’ structure needs to be retrofitted. The proposed design for timber retrofitting is shown in this paper and has been conducted on the site. -
Machine Vision Approach of Bridges Crack Identification Based on the Fusion of UAV Vision and LiDAR
Zhu Runqiu, Lai Tinglin, Weixing Hong, Ahmed Silik, Mohammad Noori, Wael A. AltabeyThe chapter introduces a cutting-edge machine vision approach for bridge crack identification, leveraging the fusion of UAV vision and LiDAR technology. By extracting 3D imaging information, the method aims to automate and enhance bridge inspection processes. The core of the approach is a deep learning framework based on Convolutional Neural Networks (CNN), which is trained using data from UAV and LiDAR sensors. The chapter highlights the advantages of this fusion technique, demonstrating its ability to detect cracks with high accuracy, regression rate, and F-score. The method not only improves the efficiency and safety of bridge inspections but also provides objective and reliable data for structural assessments. The detailed methodology, results, and analysis presented in the chapter offer valuable insights into the future of automated infrastructure maintenance.AI Generated
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AbstractThe application of machine vision algorithms in 3D bridges imaging and bridges inspection based on the fusion of UAV vision and LiDAR has a history of several years. Nonetheless, there is still lack of system research articles about this technology, especially for deep learning models developed to solve these problems. This article first introduces a comparison between the bridges crack detection system for classic 2D by using UAV camera images collection only and 3D by fusion between imaging information of the UAV camera technique and LiDAR technique for one crack in common that is, the original information detected by these two technologies is the scattering point information of the target. Subsequently, a convolutional neural network (CNN) is used for UAV and LiDAR imaging information feature fusion, which enhances the ability to extract damage features of bridge structures, and uses data fusion application to fusion a LiDAR and UAV detection scatter points for cracks, which improves the accuracy of bridge structure damage target detection in the real-time. The author believes that this study can provide practical guidance for the development of the next generation bridges condition evaluation system. -
Theoretical Analysis of Grout Sleeve Defect Detection Based on Non-destructive Resistance Method
Zexian Du, Xiushu QuThis chapter explores the critical issue of grout sleeve defects in prefabricated concrete structures and the challenges associated with their detection. It delves into the limitations of current destructive and non-destructive testing methods, highlighting the need for a more efficient and non-invasive approach. The authors introduce a novel non-destructive resistance method that utilizes electrical conductivity changes to detect grout sleeve defects. They provide a detailed theoretical analysis, including resistance calculations for both insulating and non-insulating sleeves. The chapter also presents a practical device designed for this method, which aims to improve detection accuracy and facilitate on-site construction testing. The research concludes with a call for further experimentation to validate the method's precision and accuracy, emphasizing the potential for significant advancements in the quality control of prefabricated concrete structures.AI Generated
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AbstractThe grout sleeve has been widely used in prefabricated concrete structures as an important rebar connection technology. However, grout defects may occur due to manual miss operation or poor control approaches for quality, and the existing research on grout defects detection methods and accuracy are still insufficient, which seriously affects the construction quality and structural safety of prefabricated concrete structures. Therefore, there is an urgent need for a detection method that can detect the overall defects of specimen without damaging specimen and has higher detection accuracy. Based on this, a non-destructive resistance detection technology based on the conductivity of the slurry was proposed. Firstly, the basic principles of this detection technology were introduced, and a slurry fullness detection equipment was provided. Practice showed that using this equipment did not cause damage to the sleeve during the detection process, and the defective sleeve could be quickly repaired after detection, the defective sleeve strength was further improved. So this equipment can be promoted. In addition, analysis and resistance theoretical calculation were performed for insulating sleeves and non-insulating sleeves. The results showed that it is feasible to use the non-destructive resistance method to detect the resistance of grouting materials. However, when applying the non-destructive resistance method for detection, the rebars and sleeves must be insulated before construction to effectively avoid the error and interference of current in order to improve the accuracy of the test results. -
Structural Member Strength Prediction Using Backpropagation Neural Network: A Tool for Retrofitting Intervention Integrating Non-linear Static Analysis
Reymar S. Ledesma, Dante L. Silva, Christ John L. Marcos, Kevin Lawrence M. de JesusThe chapter focuses on predicting the strength of structural members using backpropagation neural networks, a tool crucial for retrofitting interventions in existing buildings. It addresses the deterioration of structural members due to age and environmental factors, emphasizing the importance of retrofitting for public safety. The study integrates non-linear static analysis and performance-based design to verify retrofitting alterations, adhering to guidelines from the Association of Structural Engineers of the Philippines and ASCE. The research employs nondestructive tests like ultrasonic pulse velocity and rebound hammer, comparing linear, quadratic, and neural network models to predict concrete compressive strength. Sensitivity analysis and Garson's algorithm are used to rank predictors' influence. The study also includes a case study of a reinforced concrete building, applying SeismoBuild software for pushover analysis and member checks. The results highlight the superiority of the neural network model in predicting compressive strength, making it a standout method for retrofitting and ensuring building resilience.AI Generated
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AbstractThe research was derived from extensive literature reading and addressed the gap in strengthening existing buildings. The study aims to create a model that would correlate the concrete's compressive strength to nondestructive tests (NDTs), establish the strength of in-situ structural members of an existing building using the model, and propose retrofitting intervention strategies as mitigation measures against ground motions. The study presents the artificial neural network (ANN) as the governing model for strength predictions over multi-linear and quadratic regressions. Sensitivity analysis gives prevalent insights into which factor influences the forecast among the input variables. This prediction model has been initiated to evaluate the in-situ strength of the case study building for the analysis following nonlinear static procedures. Two retrofitting interventions were then developed to compare with the performance of the existing three-story building. Predominantly, a performance-based design employing pushover analysis was done where the idealized curves were generated, projecting the base shear and displacements concerning the behavior of the building (ductile or inelastic behavior). This research evaluates the passing criteria of the building based on the performance objectives provided by American Society of Civil Engineers (ASCE) 41–17. The structural member checks in terms of member chord rotations, member shear forces, joint shear stress, and inter-story drifts in connection with the base shear and target displacements evaluation proposed the best retrofitting intervention. The research showed that Case II (retrofitting by shear walls) intervention provided the lowest base shear and passed the considered member checks than RC jacketed with FRP wrapping interventions. -
Intelligence Approach for Road Crack Detection Based on Real-World Measurement
Jia Meng, Weixing Hong, Abdoul Fatakhou Ba, Ahmed Silik, Mohammad Noori, Wael A. AltabeyThis chapter delves into the intricate challenges of road crack detection, emphasizing the limitations of manual inspection methods. It introduces a cutting-edge approach using a CNN-YOLOv5 hybrid module for detecting road cracks based on real-world measurements. The method involves collecting high-quality images with inspection vehicles, extracting 3D crack features, and training a CNN-YOLOv5 model for real-time detection. The chapter also covers camera calibration techniques, lens distortion correction, and image segmentation methods to enhance the accuracy of crack detection. The results demonstrate the effectiveness of the proposed method in improving the accuracy of road crack detection and estimating real-world crack areas. The chapter concludes by highlighting the potential for further advancements in segmenting cracks using deep learning and improving image quality for robust detection.AI Generated
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AbstractRoad crack detection and measurement is one of the most important challenges for driving safety. Although the problem has been studied for a long time, few researchers have been investigating the road crack real-world measurements. Here, we develop an intelligence approach that detects the road crack then applies image processing techniques for the segmentation and real-world measurements. Our method demonstrates to be able to detect and measure the crack real-world area. The present intelligence approach including improved architecture CNN-YOLOv5 (Convolutional Neural Network-You Only Look Once version5), YOLO-crack were proposed to improve the ability of the network to detect multiple cracks. On the one hand, YOLO-crack realizes cracks detection on images. In CNN-YOLOv5, a hybrid module is proposed, which combines CNN and YOLOv5 to extract sparse the multi-scale features expressed can avoid the loss of local information caused by dilated convolution. -
Research on Temperature and Humidity Cracks in Early Age of Track Slab of Double-Block Ballastless Track Structure
Mengxuan Ye, Zhiping Zeng, Peicheng Li, Roman Wan-WendnerThe chapter delves into the critical issue of early-age cracks in high-speed rail track slabs, specifically examining the effects of temperature and humidity. It establishes accurate finite element models to simulate the temperature and humidity fields, validating these models through extensive field tests. The research reveals that these environmental factors significantly impact the structural integrity of track slabs, leading to cracks that can compromise the safety and performance of high-speed rail infrastructure. The study not only provides a deep understanding of the mechanical properties of track slabs under varying conditions but also offers valuable insights into mitigating early-age cracks, making it a vital resource for professionals in the field.AI Generated
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AbstractBased on the finite element method (FEM), this paper considers the constitutive relationship of the early age of concrete materials to study the distribution of surface cracks in the track slab under the action of uneven temperature and humidity fields. The research results show that: (1) The temperature stress on the surface of the early-age track slab is relatively large, especially in the middle area of the slab; (2) The track slab during sprinkler curing period has the risk of cracking, and the uneven temperature field has a significant impact on the cracks around the sleeper; (3) The humidity stress of track slab is mainly concentrated on the areas connected to the sleepers; (4) During the natural curing period, the humidity stress value on the surface of the track slab is greater than the tensile strength of the concrete. Furthermore, the uneven humidity field can easily cause transverse cracks in the center area of the track slab surface.
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Geotechnical Engineering and Soil-Structure Interaction
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Frontmatter
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Soil-Structure Interaction, A Case Study of a Building in Cochabamba, Bolivia
Moisés Alejandro Sánchez Málaga, Walter Antonio Abujder OchoaThe chapter delves into the critical role of soil-structure interaction (SSI) in enhancing the seismic performance of buildings, using a case study of a building in Cochabamba, Bolivia. It discusses the importance of considering SSI in earthquake-resistant design, highlighting various methodologies and models, including those proposed by FEMA P-2091. The study examines the impact of SSI on the building's response to seismic loads, demonstrating how incorporating SSI models can significantly reduce seismic force demands and inter-story drifts. The research also explores the effects of soil flexibility, foundation damping, and embedment on the building's seismic performance, providing a comprehensive analysis of the benefits and challenges of implementing SSI in structural design. The chapter concludes by emphasizing the need for further investigation into taller structures with soft soils, underscoring the importance of SSI in ensuring the safety and stability of buildings in seismically active regions.AI Generated
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AbstractThe present investigation studies the incidence generated by the soil-structure interaction (SSI) in an existing building located in Cochabamba, Bolivia, following the implementation the proposed FEMAP-2091 models. In this sense, the structure was verified with seismic analysis methods, examining that the inelastic drifts do not comply with the value established for reinforced concrete. Next, the significance value of SSI was analyzed, indicating that the inertial effect is significant, and the SSI models can be applied. The real system was analyzed by separating the kinematic and inertial interaction. Initially, the kinematic interaction was incorporated with two variables: the reduction due to the foundation connection and the embedment effect, which reduces the design spectrum. On the part of the inertial interaction, the dynamic stiffnesses were calculated with the impedance functions of ASCE 4–17. The SSI variables were incorporated into the models proposed by FEMA P-2091; the first two models were performed by linear analysis, and the other three models were performed with nonlinear pushover analysis. The results indicate an increase in the structure's fundamental period when considering the soil's flexibility. Such a decrease generates a decrease in the seismic demand, a decrease in the drift range of 19.9–62.4%, and an increase in the period from 0.036 to 1.155% with the implementation of the SSI models. -
Seepage Characteristics and Water Surge Prediction in New Tunnels Under the Condition of Existing Tunnels in Karst Troughs and Valleys Area
Hanlin Li, Tao Yu, Xinzhen Li, Xiaowei Zhang, Xiaoguang JinThe chapter delves into the intricate dynamics of groundwater seepage and water surge prediction in newly constructed tunnels adjacent to existing ones in karst troughs and valleys. Utilizing deterministic and fuzzy mathematical models, the authors predict water inflow into tunnels, highlighting the significance of tunnel construction methods and hydrogeological conditions. The study employs the finite element software MIDAS GTS NX to establish a three-dimensional numerical model, simulating the excavation process and analyzing the changes in seepage fields and water inflow. The research reveals how the permeability coefficients of surrounding rock and waterproofing measures impact the seepage characteristics and water inflow rates. The findings offer valuable insights into managing groundwater interactions during tunnel construction, ensuring the stability and safety of new and existing tunnels.AI Generated
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AbstractWith the rapid development of transportation construction, the density of highway, railroad and subway tunnels crossing the same mountain range is getting higher and higher. The construction of new tunnels will destroy the seepage balance of the existing tunnels in the tunnel site area, affect the water inflow and pore water pressure of the first-built tunnels, and cause changes in the stresses of the tunnel surrounding rocks and even affect the operation safety of the existing tunnels. Taking Chongqing Tongluo Mountain Range (called Nanshan in Nanan District, Chongqing) as the background, the three-dimensional finite element analysis of the construction process of new tunnels is used to study the impacts of the construction of new tunnels between the Nanshan Tunnel and the Tongluo Mountain Tunnel on the drainage of the existing tunnels, as well as the seepage characteristics of the new tunnels and the prediction of the influx of water under the conditions of the existing tunnels. This study provides a reference for analyzing the evolution of the groundwater system caused by the construction of multiple tunnels in the karst valley area and predicting the amount of water inflow from the new tunnels. -
Generation of Simplified Models by an Adaptive Finite-Unit Method for Simulating Square Foundations in Layered Half-Space Undergoing Vibrations
Jun-Yang Shi, Yo-Xin ChangThis chapter delves into the use of the Adaptive Finite-Unit Method (AFUM) to create simplified models for simulating the dynamic behavior of rigid foundations embedded in layered soils undergoing torsional vibrations. The method involves arranging basic modeling units in parallel, derived from general oscillator models, to form candidate models. The optimal model is selected based on its accuracy in frequency-magnification response. The study validates the model through comparisons with rigorous solutions and finite element program results, demonstrating its effectiveness in simulating both surface and embedded square foundations. The proposed method offers a significant advancement in the field of dynamic soil-structure interactions, providing a reliable tool for engineers to design more resilient structures.AI Generated
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AbstractThis study investigates the dynamic interaction behavior of a rigid square foundation embedded in a layered half-space under torsional vibrations. An adaptive finite-unit method is used to create simplified models with discrete elements. Fifteen basic units, comprising linear springs, linear dampers, and concentrated polar mass inertia, are assembled according to specific principles to generate nineteen candidate models. The equivalent model theory is utilized to ascertain the physical parameters of each element. Three equivalent criteria are established accordingly between an actual soil-foundation system and a simplified soil-foundation system in terms of static responses, dynamic amplification factors, and dynamic dissipated energy factors. An optimization analysis using a sequential search method has been conducted to determine the optimal model for accurately simulating the dynamic torsional response of the foundation in a layered half-space. The optimal model with frequency-independent parameters is subsequently utilized to analyze the dynamic amplification factor of the soil-foundation system. The results of this study indicate that the optimal model accurately captures the dynamic interactions occurring under torsional loading, with the dynamic amplification factor closely aligning with those obtained from a finite element program. The findings confirm the viability of the suggested method, showcasing its capability to effectively simulate soil-foundation interactions in torsional foundation vibration problems. -
Study on Moisture Transfer Rule in Loess Slope Subject to Variable Seismic Acceleration
Xiaojun YinThe study investigates the moisture transfer rule in loess slopes subject to variable seismic acceleration, a critical factor in slope stability. Using a large-scale shaking table, the authors conducted tests on a loess slope model, analyzing moisture content changes at different slope positions under various seismic accelerations. The results reveal significant differences in moisture transfer patterns across different slope locations, with the shoulder being most affected, followed by the toe and surface. The study also finds that the impact of seismic acceleration on moisture transfer decreases with depth, and that water migration in loess increases initially and then decreases with increasing acceleration. Notably, the loess in the slope shoulder can liquefy at high seismic accelerations, highlighting the complex interplay between rainfall infiltration and seismic liquefaction in moisture transfer dynamics.AI Generated
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AbstractRainfall seepage is a main factor leading to landslides. Based on the field test of rainfall, the model of loess slope was made base upon similarity ratio. Firstly, the model was performed with 25 mm/h medium intensity artificial rainfall. Secondly, the model of loess slope has been operated by shaking table test. 12 humidity sensors were arranged along the slope toe, slope face and slope shoulder. The results of test showed that the humidity of the slope shoulder was the largest, followed by the slope toe, and the slope surface was the smallest. Different seismic accelerations have a significant impact on moisture transfer in loess slope, which were 200, 500 and 800 gal respectively. The change of humidity at 50 mm from the slope is obviously greater than 175 mm. Moisture transfer is composed of rainfall seepage and seismic liquefaction. As loaded to 800 gal, the loess has emerged to obvious loess liquefaction. The results of test showed that the seismic acceleration have a significant influence on the moisture transfer in loess slope. The change of humidity varies greatly with different slope positions. As the slope depth increases, the change of humidity smaller. When the depth from the slope is small, the change of humidity is the most in slope toe, and when the depth from the slope is large, the change of humidity is the most in slope shoulder. Studying the law of moisture transfer in loess slope after rainfall seepage can provide a theoretical basis for the design and treatment of loess slopes. -
Prediction of Water Influx in Operating Tunnels in Karst Valley Area
Yu Tao, Li Xinzhen, Zhang Xiaowei, Li Hanlin, Jin XiaoguangThe chapter delves into the complex issue of predicting water influx in operating tunnels situated in karst valley areas, highlighting the significance of hydrogeological conditions and construction methods. It introduces two primary analytical approaches: deterministic mathematical models, such as the water balance method and analytical equations like Goodman's empirical formulas, and fuzzy mathematical models, including artificial neural networks and time series analysis. The chapter also presents a case study of the Chongqing Nanshan Tunnel, detailing the geological and hydrogeological conditions, and employing numerical simulations to predict water influx. The study underscores the critical role of rainfall in influencing water influx, demonstrating a strong correlation between rainfall and tunnel discharge. The chapter concludes with a comparison of predicted water influx using various methods and highlights the importance of accurate hydrogeological parameters for precise predictions.AI Generated
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AbstractTunnel excavation breaks the original hydrological dynamic equilibrium in the tunnel site area, and promotes the alternation of water cycle; the groundwater system has been recovered to some extent during tunnel operation, but the extent of the recovery and the revelation on the prediction of water influx of the new tunnels in the tunnel site area still need to be studied in depth. Taking the operation tunnel of Chongqing Nanshan (NS) in the karst valley area as an example, based on the analysis of tunnel engineering geological conditions and hydrogeological conditions, the water influx of Nanshan Tunnel is predicted through the monitoring of water outflow from the mouth of the tunnel after the tunnel has been passed through, the measurement of the water influx in the tunnel operation period, and the numerical simulation analysis of tunnel inflow, and at the same time the water influx of the nearby operation tunnel of the Tongluo Mountain (TLS) Railway Transportation Tunnel is analyzed. The results show that the water influx in the right hole of NS Tunnel is more influenced by surface water, while the left hole is more influenced by groundwater and karst water. Rainfall and permeability coefficient of surrounding rock have great influence on the water influx of tunnel. It provides a reference for the study of the evolution law of groundwater system of multiple tunnel construction in karst trough valley area.
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- Title
- Proceedings of the 4th International Civil Engineering and Architecture Conference
- Editor
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Marco Casini
- Copyright Year
- 2025
- Publisher
- Springer Nature Singapore
- Electronic ISBN
- 978-981-9754-77-9
- Print ISBN
- 978-981-9754-76-2
- DOI
- https://doi.org/10.1007/978-981-97-5477-9
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