bluuebunny/crossref_metadata_2025_split huggingface dataset:
Load-bearing response of deep content mixing soft soil composite foundation based on the geotechnical centrifugal model test
Authors: Lin Y , Tang G , Ma X , Ma C Y , Wang Z 
Published: May 2024

Abstract
Deep cement mixing (DCM) is an effective method of treating soft underwater soil foundations. Currently, the real-time failure development of a composite foundation cannot be obtained by most model tests of DCM pile foundation reinforcement. In this study, a circuit device for identifying pile failure and that can reflect the real-time working state of piles arranged at different positions in a soft soil composite foundation was developed. By applying this device to a geotechnical centrifugal model test, the load-bearing response process of a bank slope reinforced with a soft-soil composite foundation and DCM piles was studied. The failure development law of the DCM piles, ultimate surcharge of the bank slope, failure mode of the foundation, and the pile-soil stress ratio were determined from the test results. The law obtained in this study provides a reference for the application of DCM piles in underwater soft soil foundation engineering.
Semi-analytical solution for one-dimensional coupling consolidation of original soil and electro-osmotic layer using horizontal electrodes
Authors: Li Jian-Ping , Luo Wen-Dong , Chen Zhang-Long 
Published: May 2024

Abstract
The application of horizontal electro-kinetic geosynthetics for electro-osmotic consolidation is becoming increasingly widespread. Such horizontal electrodes are typically arranged at intervals, allowing pore water in original soil to pass through the intervals and penetrate into the electro-osmotic layer. In this study, a one-dimensional semi-analytical solution for a double-layered electro-osmotic system incorporating the original soil was presented and verified. The effects of the soil properties on the consolidation process were investigated. Results revealed that original soil can achieve a significant consolidation effect, even better than electro-osmotic dredged soil. A smaller permeability coefficient of original soil significantly prolongs the consolidation time, while a thicker original soil can improve the average consolidation effect of the two layers. The proposed model provides new electrode arrangement ideas and theoretical support for horizontal electro-kinetic geosynthetics for electro-osmotic reinforcement.
Research on construction parameters of stone columns for liquefaction mitigation in coral reef sand areas
Authors: Liwen Hu , Xiaocong Liang , Mingxing Zhu , Meng Chen , Xiong Xu 
Published: May 2024

Abstract
For loose coral reef sand with high fines content located in strong earthquake zones, it is necessary to choose stone columns as a liquefaction mitigation ground improvement method that can consider both drainage and densification functions. Taking the Tibar Bay Port project in East Timor as an example, the bottom-feed technology of vibrating stone columns was developed, and typical coral reef sand sites with different fines contents were selected as trial test areas. Experimental research was performed to study the construction parameters for onshore and offshore stone column processes. Tests showed that the vibratory process control parameters, quality acceptance standards, and control procedures proposed through research meet the anti-liquefaction requirements for both drainage and densification effectiveness. The different construction characteristics of onshore and offshore stone columns were also analyzed. Considering the particularity of underwater stone column construction, the research results can be used for stone columns reinforced grounds similar to coral sand onshore and offshore.
Research on bearing capacity of piles with negative skin friction based on field test
Authors: Song-tao WEI , Bo LI , Jian-fei YU , Jun LIU 
Published: May 2024

Abstract
There are extensive deep soft soil layers in the coastal areas of China, and the drainage consolidation method is widely adopted for foundation pretreatment in these areas. However, there are still dozens of centimeters of post construction settlement, which may produce negative skin friction on the pile foundation. To accurately estimate the magnitude of negative skin friction, two prestressed high strength concrete pipe piles with different pile end holding layers were used to conduct field tests. The development law of negative skin friction of pile foundation with soil consolidation is studied by simulating different pre-load height conditions of soil around pile. The monitoring results of field tests indicate that with the soil settlement around the pile, the dragload increases gradually and the neutral point moves downward. When the relative displacement between the pile and soil is 87 cm, the neutral point position of the end bearing pile is approximately 44.6-m deep, and the dragload is about 3640 kN, while the friction pile is 30 m and 2160 kN. The analysis shows that if the pile foundation construction is carried out during the foundation pretreatment, the dragload is considerably large, and this may lead to excessive settlement and damage of the pile.
A modified Prandtl upper-bound solution of basal stability for narrow-deep excavations in undrained clay
Authors: Qiao Yaqing , Huang Maosong , Shi Zhenhao , Zhang Zhongjie , Wang Haoran 
Published: May 2024

AbstractIn recent years, the construction of narrow-deep excavations has been steadily developing. Narrow-deep excavations exhibit a clear size effect in the basal heave stability analysis. However, the classical Prandtl mechanism ignores the size effect and influence of the inserted depth of wall penetration. Based on this, a modified Prandtl failure mechanism that considers the above factors was proposed in this study. Subsequently, a practical equation was derived to simplify the analysis process and obtain the safety factor against basal heave. The upper-bound solution provides a convenient and concise method for basal heave stability analysis of narrow excavations in undrained clay, and its feasibility was verified by comparing it with the results obtained by finite element limit analysis. The results showed that the proposed failure mechanism can provide a better upper-bound solution for the safety factor of the basal stability of narrow excavations than the classical Prandtl failure mechanism.
Responses of metro shield tunnels to an adjacent deep excavation in Shanghai soft ground
Authors: Fang Yingang , Jia Jian , Xie Xiaolin 
Published: May 2024

Abstract
Deformation in metro shield tunnels is a consequence of conducting adjacent deep excavations. Accordingly, this research examines the response of existing metro shield tunnels in Shanghai’s soft ground to nearby deep excavations, focusing on how tunnel deformation correlates with the distance to the excavation. Utilizing actual measurement data from metro shield tunnels located 12-45 m from an 11.5-24.1-m-deep excavation, the study initiates with a project overview before analyzing the deformation data of the metro tunnels. This analysis includes the settlement and transverse convergence of both upward and downward lines. Furthermore, by integrating the settlement history curve and settlement increment ratio statistics, the study explores the deformation of the metro tunnels across different construction stages of the adjacent excavation. Additionally, the effect of the distance to the excavation on metro tunnel deformation is discussed, considering identical excavation depths, supporting stiffness, construction levels, and soil conditions. This investigation aims to provide insights applicable to similar cases and inform future research.
Inrushing failure characteristics of deep shaft structures in soft soils based on material point method simulation
Authors: Wang Yu-Mo , Qiao Yong-Kang , Peng Fang-Le 
Published: May 2024

Abstract
In areas with soft soil, inrushing may occur during the construction of deep shaft structures under high water pressures, causing destructive accidents. Most studies on inrushing have used the finite element method. However, it is difficult to achieve a large deformation simulation because of mesh limitations. The material point method is not constrained by the mesh, and the material properties and motion information of the material are stored at the material points. Therefore, it can be used to effectively simulate large soil deformations. In this study, a numerical model for a deep shaft structure in Shanghai was formulated using the material point method to simulate the evolution of inrushing failure. The likelihood of inrushing damage at different excavation depths was analyzed. Soil heave at the bottom of the pit in the absence of inrushing was examined. The structural and environmental factors affecting the inrushing process are discussed. Strategies have been proposed from different perspectives, such as structure, environment, and construction methods, to reduce the damage caused by inrushing, thereby providing a reference for the safer construction of deep shaft structures.
Field test on application of tip grouting in enlarged head cast-in-place bored pile
Authors: Zhang Jiaqi , Zhao Chunfeng , Zhao Cheng , Wu Yue 
Published: May 2024

Abstract
Pile tip grouting is an important technique for improving the bearing capacity of cast-in-place bored piles. This paper presents a field experimental study on the effects of tip post-grouting in an enlarged head cast-in-place bored pile. The bearing data of the pile before and after the grouting were obtained through two load tests. The settling rod method was used to monitor the settlement at three critical sections, including the pile bottom during loading, while the method of rebar stress gauge was employed to monitor the strain of the pile shaft. The study results indicate that post-grouting at the pile tip significantly enhanced the bearing capacity of the pile and helped control the settlement at the pile top. A comparison between the measured and calculated settlement values at critical sections demonstrates the applicability of the settlement rod method and strain gauge method. Post-grouting at the pile toe effectively improved the side friction of the pile, resulting in smaller axial forces in the lower part of the grouted pile under equivalent loads.
Boundary effect of foamed cement paste under the influence of air-coupled impact-echo
Authors: Wan X , Zhang Z , Ye G , Zhang Y , Liu H 
Published: May 2024

Abstract
The air-coupled impact-echo method has been increasingly utilized for the detection of cement-based materials. In this study, an air-coupled impact-echo system is developed. This system evaluates the response of cast-in-place foamed cement paste blocks subjected to air-coupled impact-echo. The shape factor is calculated based on the acquired impact-echo spectrograms to analyze the boundary effects of the blocks. The results show that the values of the shape factor vary with the impact location, as the impact location from the edges of the blocks affects the air-coupled impact-echo response. Accordingly, a dimensionless factor is proposed to evaluate the boundary effect of block-like foamed cement paste. This study contributes to the application of the air-coupled impact-echo method for the detection of foam cement paste.
Analysis of the shear wave velocity structure of a soft-hard interlayered rock slope based on surface wave and microtremor survey
Authors: Peng M , Liang Y Y , Liu L , Shen J , He L K , Xue J F , Qin X Z 
Published: May 2024

Abstract
The information regarding the layered structure is pivotal to the stability analysis of soft-hard interlayered rock slopes. The variation in the shear wave velocity offers insights into the characteristics of the strata structure within a rock slope. In this study, a joint analysis method that combines the multichannel analysis of surface waves (MASW) and the microtremor surface method (MSM) was used to identify the layered structure of a soft-hard interlayered rock slope located in the Shandong Province, China. The survey lines were positioned on slope crests. For the MASW, the receivers were placed in line with an active seismic source. The MSM method uses a concentric circular array comprising seven receivers. Fundamental-mode dispersion data were extracted from the active and passive microtremor sources. The 1D velocity models were then inverted from the combined dispersion curves using a surrogate optimization algorithm. A 2D velocity profile of the investigated slope was constructed through linear interpolation, and it exhibited distinct characteristics of high- and low-velocity interlayers, consistent with the borehole data. Our results demonstrate that the joint analysis method provides a complementary approach to image velocity profiling of slopes, thus contributing to enhanced investigation depth and resolution in shallow layers owing to the wider frequency range of the dispersion curves.
Spatiotemporal Prediction of Rainfall-induced Landslides Using Machine Learning Techniques
Authors: Xiong Jun , Pei Te , Qiu Tong 
Published: May 2024

Abstract
Landslides cause significant damage to infrastructure and loss of life. Landslide susceptibility map (LSM), as an important reference for landslide hazard assessment, indicates prone areas of landslides. However, conventional LSM only predicts the spatial distribution of potential landslides, which cannot fully explain the occurrence of landslides at different times. In the present study, a spatiotemporal LSM is conducted to predict landslides both in space and time. A landslide database containing 223 recorded landslide events in southwestern Pennsylvania is used. Fourteen topographic spatial factors and eight rainfall temporal factors are used for machine learning (ML). Four ML models are applied in the study, including Logistic regression (LR), Support vector machine (SVM), Random forest (RF), and Gradient boosting machine (GBM). The results show that through cross-validation, RF outperforms the other algorithms with a value 0.86 of the area under the receiver operating characteristic curve (AUC score). The optimal model is used to generate spatiotemporal LSMs. It is concluded that by introducing spatial and temporal information simultaneously, ML models have the capability of learning the pattern of landslide occurrence both in space and time, providing an effective assessment tool to reduce catastrophic loss of landslide hazards.
Shield tunnel leakage detection using distributed optical fiber
Authors: Liu Pengfei , Ma Minglei , Wang Jianxiu , Long Yanxia , Cao Ansheng , Li Huboqiang 
Published: May 2024

Abstract
Leakage in operating tunnels is a serious problem during operating stage. In order to realize non-destructive detection of leakage in an operating shield tunnel, an optical fiber temperature measurement method based on Raman scattering and infrared thermal imaging technology is developed. The working principle of leakage monitoring with Distributed Fiber Optic Temperature Sensor (DTS) combined with time domain reflectometry (OTDR) technology are introduced. The distributed measurement of temperature field is realized in a typical tunnel. Infrared thermal imager is used to perform thermal imaging on the leakage area, and the temperature difference between the leakage area and the non-leakage area is 3.6 °C, which can meet the requirements of distributed optical fiber side leakage temperature accuracy. This illustrates the feasibility of quantitative monitoring of leaks in distributed optical fiber temperature sensing systems. The reasonable arrangement of leakage monitoring fiber in distributed fiber temperature sensing system is discussed in practical engineering.
Assessment of load test program for reliability-based design of piles
Authors: Ma Xiangyu , Hu Jinzheng , Li Xueshan , Zhang Jie 
Published: May 2024

Abstract
Quantifying the uncertainty of the bearing capacity of piles is crucial in the context of reliability-based design (RBD) for pile foundations. The utilization of site-specific load test data plays a pivotal role in reducing the uncertainty associated with bearing capacity, thereby enhancing the overall design of pile foundations. However, prior to initiating a load test program, there exists uncertainty both in the outcomes of the program and the potential benefits it may yield. This research endeavors to develop a method that allows for assessing the effectiveness of a load test program before its execution. The structure of this paper is as follows: firstly, it introduces a framework for evaluating the utility of the pile load test (PLT) program. Subsequently, it constructs a pre-posterior analysis to examine the anticipated benefits derived from the load test program. Finally, the proposed methodology is elaborated upon through a detailed example. This paper is valuable for enhancing decision-making in optimizing pile load test programs.
Three-dimensional stochastic model for stratigraphic uncertainty quantification using Bayesian machine learning
Authors: Wang Hui , Wei Xingxing 
Published: May 2024

Abstract
Data-driven geotechnics is an emerging research field that contributes to the digitalization of geotechnical engineering. Among the numerous applications of digital techniques in geotechnical engineering, interpreting and simulating stratigraphic conditions with quantified uncertainty is an essential task and an open question in geotechnical practice. However, developing an uncertainty-aware integration of subjective engineering judgments (i.e., geological knowledge) and sparse objective site exploration results (i.e., borehole observations) is challenging. This investigation develops an effective three-dimensional stochastic geological modeling framework based on Markov random field (MRF) theory and Bayesian machine learning to characterize stratigraphic uncertainty. The proposed model considers both stratigraphic uncertainty (inherent) and model uncertainty (imperfect knowledge). A stratigraphic modeling example was studied to demonstrate the effectiveness of the proposed approach. We envision that this approach could be further generalized to industrial practices to improve risk control in geotechnical engineering.
Multi-sample joint localization method for intrusion sources around underground pipelines based on cross-correlation convolutional neural networks
Authors: Chai Fu , Zhou Biao , Xie Xiongyao , Zhang Zixin , Han Jianyong 
Published: May 2024

Abstract
Improving the safety monitoring of underground pipelines is crucial for maintaining the structural integrity of critical infrastructure systems. This study introduces an innovative multi-sample joint localization method (MSJLM) based on cross-correlation convolutional neural networks (CC-CNNs) to identify intrusion sources in the vicinity of underground pipelines. Traditional approaches to detecting and locating pipeline intrusions often rely on a solitary sensor monitoring point, making them susceptible to errors and limitations. Presently, widely used distributed optical fiber testing methods tend to yield imprecise localization. In contrast, the MSJLM proposed in this study harnesses data from multiple samples effectively and combines them via correlation analyses to enhance precision and reliability. The CC-CNN framework used to process the collected data is demonstrated to be highly effective in extracting spatial features and recognizing patterns.
Monitoring the hardening process of cemented soil with polymer optical fibre
Authors: Zhibin Z H L , Zhonghao W , Xianfeng MA 
Published: May 2024

Abstract
Cement-soil can effectively improve the mechanical characteristics of soft soil and reduce the deformation of foundations through the physical and chemical processes of cement hydration. After mixing cement with soft soil, the hydration reaction of cement consumes a certain amount of water, which leads to a decrease in the water content. The early strength of cement-soil refers to the undrained shear strength within a few hours of mixing. The initial setting time of cement-soil can reflect its early strength development. In this study, polymer optical fibre (POF) sensors are used to visually monitor the early strength of cement-soil with different cement contents; the monitoring results show that the POF sensor can effectively visualize the hydration process of cemented soil. The cement-soil hydration process is divided into three stages: the initial setting time of the cement-soil is 13-15 h, and the final is 33-41 h. Furthermore, the cement content significantly influences the initial and final setting times of cement-reinforced soil. As the cement content increases, the initial and final setting times of the cement–soil decrease. This study proposes a new method for monitoring the strength of cement-reinforced soils.
Real-time railroad track components inspection framework based on YOLO-NAS and edge computing
Authors: Tang Youzhi , Wang Yi , Qian Yu 
Published: May 2024

Abstract
The demand for efficient track inspection systems in the rapidly evolving rail transportation field is more pronounced than ever. Hence, this study combines deep learning and edge computing for railroad track component inspection, focusing on the YOLO-NAS architecture. Our objective was twofold: to harness the advantages of YOLO-NAS for accurate and high-speed detection while addressing the computational constraints of edge devices. Consequently, YOLO-NAS-S-PTQ model achieved a remarkable balance, with 74.77% mAP and 92.20 FPS, on the NVIDIA Jetson Orin platform. By deploying this model on an edge device and utilizing a multiprocessor pipeline, we observed an inference speed of 60.468 FPS, which was nearly double the rate of its single-threaded counterpart. Field tests further confirmed the efficiency of the model, demonstrating a recall rate of 80.77% and an accuracy of 96.64%. These findings underscore the potential of YOLO-NAS in transforming traditional rail component inspection methods, significantly reducing human interventions and potential errors.
Hyperspectral imaging features for structural stress state assessment: An experimental study
Authors: Wang C , Huang H , Zhou M 
Published: May 2024

Abstract
To explore the feasibility of hyperspectral machine vision for detecting stress states of underground structures, this study utilized a hyperspectral camera to acquire spectral datasets from the surfaces of concrete and sandstone specimens under different stress conditions. Machine learning models were established to predict stress states based on raw spectral data and data pre-processed using the Savitzky-Golay (S-G) method. The results indicated that satisfactory outcomes were obtained with no pre-processing and S-G pre-processing. In addition, the hyperspectral response characteristics of concrete and sandstone under different stress states were investigated. The hyperspectral dataset of sandstone was observed to yield higher predictive accuracy than that of concrete. Finally, a comprehensive analysis of the performances of the principal component regression, partial least squares regression, and least-squares support vector machine models was performed over various datasets in terms of computed model evaluation metrics.