bluuebunny/crossref_metadata_2025_split huggingface dataset:
Crack monitoring for municipal sewer pipes using DFOST
Authors: Yuan Xun , Liu Yuepeng , Lin Peiyuan 
Published: May 2024

Abstract
The distributed fiber optic sensing technique (DFOST) provides an effective solution for long-term deformation monitoring of sewer pipelines under operation conditions due to occurrence of cracks. However, optical fibers attached on the pipeline wall might fail to capture all cracks as they are usually highly spatially scattered, resulting in misjudgment of pipe structural conditions. To address this challenge, this paper presents a novel deployment approach of distributed fiber optic monitoring system for pipeline cracks. First, the working principle of optical frequency domain reflectometry (OFDR) is explained. Second, the production of concrete pipe specimens with different optical fiber sensors deployment schemes is shown in detail. Finally, a comprehensive analyse of the results of visual inspection and fibre optic monitoring is completed. To evaluate the performance of this approach, experimental data from various cases were considered. The conclusion of this paper provides theoretical and empirical support for the application of distributed fiber optic sensors for pipeline cracks monitoring.
Tunnel indirect damage identification algorithm based on service train dynamic response time series
Authors: Li Qi , Zeng Kun , Xie Xiongyao 
Published: May 2024

Abstract
In this study, a tunnel indirect damage identification algorithm based on a service train dynamic response time series was proposed. First, the principles and processes of the proposed algorithm are introduced. The instantaneous frequency and spectral entropy of the trend and seasonal terms of the train dynamic response decomposed by Seasonal and Trend decomposition using Loess are calculated, respectively, to further extract the time-frequency features of the signal. The calculated sequence is input into the Bi-directional Long Short-Term Memory network, and the type of damage case is the output. Second, the feasibility of the algorithm is verified using a model test. Finally, the key links in the algorithm are discussed. The results indicate that the proposed algorithm can identify damage cases with a small number of training and test sets, and the accuracy of the test set can reach 83.33%. Through time-frequency feature extraction and normalization processing, the length of the network input sequence is reduced, the training speed is increased, and damage identification can be realized without a deep network.
Bayesian Back Analysis of Axially Loaded Pile Response Using Fibre Optic Strain Data
Authors: Wang M , Leung Y 
Published: May 2024

Abstract
The load-transfer method has been extensively used to evaluate the deformation behavior of foundation piles, with the nonlinear load-settlement behavior of a pile-soil system modeled using load-transfer curves. Although load-transfer models have a considerable impact on the pile response, the model parameters are usually estimated empirically from soil parameters using transformation models, and the associated uncertainties are often neglected. Fiber optic sensing technology provides detailed axial strain information along the entire length of a pile; however, the full potential of such utilization has not yet been realized. This paper presents a Bayesian back analysis method for statistical descriptions of load-transfer curves and pile responses based on fiber optic measurement. A pile test case study is used to illustrate the proposed method, and several candidate model configurations are compared. The results show that the predicted pile response generally matches the measured data, and the quantified uncertainty allows for a better understanding of the possible ranges of the pile response, in addition to the single best-estimate result.
Predicting base resistance of super-long piles using a random forest model: A case study from Ho Chi Minh city
Authors: Weng Kailiang , Jia Mincai 
Published: May 2024

Abstract
The prediction of the base resistance for long piles is usually challenging because of the impact of material characteristics and the influence of the nature of the surrounding soil. Artificial intelligence models have been applied in various geotechnical engineering fields, and significant results have been achieved. Based on a well-instrumented static load test dataset (1131 data points) from various projects in the soft soil area of Ho Chi Minh City, this study established a random forest (RF) model considering five input parameters, including the applied load, load point displacement, axial stiffness, standard penetration test value of the soil beneath the pile toe, and the distance from the load point to the pile toe. Twenty percent of the data was designated as the test set, which was used to make predictions using the established model. The results show that the RF model has good predictive performance in terms of prediction accuracy and reliability. A sensitivity analysis of the input factors provided a deeper understanding of the base resistance mechanism, which is important in pile foundation design practice.
Development and key technologies for architectural design and technical solutions of CIM platform: A review
Authors: Fang J , Xie X , Xu J 
Published: May 2024

Abstract
The integration of building information modeling (BIM), geographic information systems (GIS), 5G, IOT, cloud computing, big data, artificial intelligence, and other technologies in urban management has become a new and rapidly developing trend in recent years. However, most of the existing research on the construction of city information modeling (CIM) platforms based on the integration of BIM and GIS technologies focuses on integration technologies, and there is a lack of theories, methods, and standards for further data analysis and mathematical modeling. This paper analyzes and summarizes the actual situation of the application of recent research papers in the BIM field and the application of CIM platform pilot projects, reviews the application of BIM and GIS technologies in smart cities, and discusses future trends. For example, the construction of a basic platform for smart cities requires the establishment of a three-dimensional visual CIM platform with functions such as the planning review, architectural design plan review, construction drawing review, completion acceptance filing. A smart city is built by analyzing the cyber security risks faced during the construction. The technical, management, and operational measures of the security system provide guidance and reference for the secure construction of smart cities. This involves promoting the reform of the construction work system driven by data resources obtained from government information, and the establishment a new digital government construction management system through the “separation of management and transportation.” These analyses highlight the evolution of the CIM platform construction. The results indicate that the use of key technology integration in the construction of a CIM platform requires a system theory that goes beyond integration technology and mathematical modeling methods for a detailed application. It involves analyzing the deep integration of key technologies and business processes in the CIM platform.
Intelligent prediction and evaluation method of optimal frequency based on PSO-BPNN-AdaBoost model
Authors: Chen X B , Hao Z R , Xie K , Li T F , Li J S 
Published: May 2024

Abstract
To achieve rapid and accurate determination of the optimal compaction frequency for high-speed railway subgrade materials, a method based on the PSO-BPNN-AdaBoost model for intelligent frequency estimation is proposed. Firstly, the Particle Swarm Optimization (PSO) algorithm is introduced to obtain the optimal hyperparameters of the Backpropagation Neural Network (BPNN), and then the PSO-BPNN-AdaBoost model is established by integrating the AdaBoost ensemble algorithm. Secondly, taking graded gravel fill material as an example, the Grey Relational Analysis algorithm (GRA) is employed to identify the main controlling features affecting f
op as input features for the model, and the predictive performance of the model is evaluated. Finally, the model’s reliability is verified through ablation analysis. The results indicate that the PSO-BPNN-AdaBoost model demonstrates higher predictive accuracy. The main controlling features influencing f
op are revealed to be the maximum particle size (d
max), gradation parameters (b, m), coarse aggregate elongation index (EI), Los Angeles Abrasion (LAA), water absorption rates (W
ac, W
af).
How to quantify the tunnel structural resilience in longitudinal direction: a discussion on the index and its effect
Authors: Hua Y S , Huang H W , Zhang D M , Liu X M 
Published: May 2024

Abstract
Shield tunnel is prone to longitudinal differential settlement due to the characteristics such as segmental linings and unpredictable changes in multiple uncertain environments. Excessive differential settlement may deteriorate the safety and operational serviceability of the shield tunnel. Resilience has been increasingly applied in structural performance assessment given that it can evaluate the ability of structure to absorb the disruption and to restore the performance level. However, the resilience index and analysis framework for tunnels are quite vague and still in the developing phase. In this paper, a resilience analysis framework is introduced, and the detailed model to quantify the resilience of shield tunnel is presented. The cumulative settlement, maximum, and average value of differential settlement are selected as the performance indexes, because they can reflect the ability of the tunnel to ensure the structural safety and meet the waterproof requirements of the circumferential joints. Then, the effects of these indexes are analyzed using a real case in Shanghai. The results show that the resilience grades calculated using the three performance indexes are different, and the cumulative settlement is regarded as the better index.
Mechanical properties of sulfate saline soil stabilized by coal gangue-slag composite geopolymers
Authors: Yang Xiaoyun , Lin Cheng 
Published: May 2024

Abstract
Geopolymers, which are composed of solid waste, are eco-friendly binders characterized by rapid hardening and high strength. Using geopolymers to stabilize saline soils presents a sustainable solution for soil improvement. This study investigated two geopolymers, HG and SG, composed of a coal gangue-slag composite, to improve saline soils. The stabilized soils were prepared by blending geopolymers with saline soils in varying proportions of 10, 20, 30, and 40% by weight. The strength of the stabilized soils was evaluated based on the geopolymer dosage. Moreover, we examined the strength of the stabilized soils with curing time and elucidated the underlying mechanisms using microscopic analyses including XRD, FTIR, and SEM. This study revealed that: 1) the SG geopolymer outperformed the HG geopolymer in soil strength enhancement; 2) cohesion of the stabilized soil increased as the dosage and curing time increased, while the internal friction angle showed no clear trend; 3) the geopolymer stabilized soil mainly contained quartz, C-A-S-H, N-A-S-H, and C-N-A-S-H gels, and these gels were distributed on the soil particle surface and within the interstitial voids, improving the soil strength, and 4) in saline soil engineering, HG or SG geopolymer dosages should be above 30% and 20%, respectively.
Seismic response analysis and resilience study of Qingdao 2nd submarine tunnel using the finite element method
Authors: Zhang Q Y , Zhang W , Xue Y D 
Published: May 2024

Abstract
Earthquakes, as considered a highly destructive and unpredictable natural disaster that poses significant challenges for engineers designing underground structures. Incorporating seismic considerations is important to ensure the safety and stability of such structures. Therefore, it is crucial to analyze the response of tunnels to earthquakes and establish an evaluation index for their resilience, which would help guide projects toward improved safety. In this paper, we use numerical simulations to study the seismic impact on the Qingdao 2nd Submarine Tunnel according to different lining thicknesses (25-75 cm) and varying stratum conditions. Through adjustments to lining thickness and stratum conditions, a total of 30 numerical simulation experiments are conducted. These experiments contribute to the creation of the resilience evaluation index. The results of the study indicate the following trends: 1. Increasing lining thickness reduces the stress and deformation along the lining, though the effect stabilizes around 45-cm thickness. 2. Poor surrounding rock conditions lead to increased stress and deformation along the lining, especially near fault fracture zones. 3. The culmination of the study involves the creation of a resilience evaluation index, which serves as a practical guidance for tunnel construction in real-world projects.
Feasibility study of geosynthetic vegetation substrate for hard-surface ecological restoration part 2: Biodiversity and environmental effects
Authors: Chen L Y , Qin C R , Qiu T , Wu J Y , Guo J , Yan X 
Published: May 2024

Abstract
Current ecological restoration techniques often face challenges on steep and hard surfaces (e.g., concrete or rock surfaces) because of their reliance on soil as a vegetation substrate. Two geosynthetic-based ecological restoration techniques were proposed in which a geosynthetic material was used to replace the soil as a vegetation substrate on hard-surface slopes. In the first technique, vegetation is planted directly on the geosynthetic vegetation substrate (GVS), where the GVS provides water to the vegetation and room for vegetation roots. In the second technique, Hygrophila ringens is planted on the GVS. Hygrophila ringens exhibits rapid growth initially and then dies, creating a layer of humus over the GVS. A one-year vegetation growing test demonstrated that the designated vegetation thrived on the GVS and various foreign vegetation also began to grow on the GVS. The variety of vegetation indicates that the GVS not only successfully sustained the designated vegetation but also helped in the ecological restoration and improved the biodiversity on the hard-surface slopes.
Mitigation of soil frost heave with fungi
Authors: Zhang X J , Jiang Y S , Fan X D , Yu X 
Published: May 2024

Abstract
Frost heave and thaw weakening can impose engineering issues on cold region infrastructures, including pavements, slopes, pipes, foundations, and buildings. This study investigated the potential of fungi treatment to mitigate the frost susceptibility of soils. Fungi were grown with organic waste to develop fungal mycelium. Subsequently, it is introduced into the soil. A sensitivity study was conducted on the influence of fungi centration on soil behaviors. The volume change behaviors when subjected to freezing or thawing were monitored. The results indicated that both soil frost heave and thaw weakening were reduced significantly with fungi treatment. The mechanisms are investigated with the measurement of the soil water characteristic curves. The introduction of fungi treatment affected the SWCC and soil water affinity. These affect the moisture transport when soil is subjected to freezing/thawing. Subsequently, the volume changes were suppressed.
Application of PISA method for monopile design in layered soil
Authors: Wang Huan , He Ben , Nallathamby Sivasithamparam , Yang Shaoli , Huynh Khoa 
Published: May 2024

Abstract
The foundation design for offshore wind turbines (OWTs) is critical to ensuring their structural integrity and long-term stability. Large-diameter monopiles are widely used for OWTs owing to their proven effectiveness. The conventional design approach, derived from the oil and gas industry’s p-y model, has limitations when applied to monopiles for OWTs. Consequently, a novel design method based on the PISA joint industry research project was developed, which extends beyond the traditional lateral soil resistance (p-y curves) and incorporates additional soil reaction components from shaft friction, pile base shear, and base moment. Unlike the simplistic rule-based conventional approaches, the proposed method necessitates site-specific 3D finite element (FE) simulations for precise calibration of soil reaction curves. Although successfully applied in European offshore wind farms, the PISA method’s performance in regions with distinct seabed compositions, such as China, remains to be verified. Therefore, this paper presents a comprehensive case study conducted at the Xiangshan wind farm, a representative site characterized by layered soil. The study employed in-situ investigations (cone penetration test, borehole) and laboratory tests (direct simple shear, bender element) to delineate the seabed soil profile and derive essential soil parameters for accurate foundation design. To facilitate the design, an Abaqus-based design tool was developed, which automated the extraction of soil reaction curves from the 3D FE simulations, calibration of PISA springs, and execution of one-dimensional beam-spring analyses employing Timoshenko beam theory. Comparative analyses were performed on the computed responses of piles, encompassing load-deflection curves, pile deflections, and bending moment profiles. The outcomes from the 3D FE simulations, uncalibrated rule-based PISA model, and calibrated PISA model were compared to validate the PISA method for monopile design in layered soil conditions.
Anchor chain profiles in sand based on centrifuge model tests
Authors: Rui S J , Zhou Z F , Liu Z Q , Jostad H P , Wang L Z , Guo Z 
Published: May 2024

Abstract
The rapid development of floating wind turbines (FWTs) has brought new challenges to their mooring systems in shallow water of 50-200 m. The sand seabed, which is widely distributed in offshore regions, is often encountered in the service of FWTs and influences the anchor and mooring line design. The anchor chain is primarily adopted as the part interacting with the seabed, and its configuration in the seabed is vital for anchor design. However, a complete understanding of the chain configuration in sand is yet to be achieved. To address this, a group of centrifuge model tests using a model chain were conducted to simulate the chain embedment behavior in carbonate sand. During the tests, the chain position and soil deformation were captured using the Particle Image Velocimetry (PIV) method. A calculation model was adopted to predict the chain configuration in the sand, compare it with the centrifuge test results, and then analyze the differences between them. Finally, suggestions for model improvement were discussed.
Numerical simulation of offshore monopiles with reinforcement in shallow soil layer
Authors: Zhu Tao , He Rui , Guo Zhen 
Published: May 2024

Abstract
With the development of large-scale offshore wind turbines (OWTs), monopile foundations require larger diameter and greater embedded depth to satisfy the higher bearing requirements. Large-diameter monopiles for OWTs are mainly loaded horizontally, and the horizontal resistance provided by the shallow soil plays an important role in the loading of the monopile foundation. Therefore, shallow soil reinforcement (such as cement grouting and bio-grouting) is an effective method to improve the bearing capacity of the monopile. In this study, the lateral static loading mechanism of a shallow-layer reinforced monopile was investigated by finite element method (FEM). The effect of reinforcements with different stiffness values (elastic modulus), different strengths (cohesion and friction angle) and different reinforced ranges (width and depth) was analyzed on the lateral bearing capacity, deformations, soil resistances, and soil resistance per unit length to pile deflection (p-y) curves of monopiles. Based on the numerical results, an empirical formula was proposed for predicting the reinforcement coefficient of the bearing capacity. The effects of different reinforcement parameters on the distribution of soil resistance were analyzed, and the soil resistances obtained by FEM were compared with those from a theoretical formula. It was found that the resistance provided by the reinforced soil was clearly reduced at the interface with the unreinforced soil, and the resistance of the unreinforced soil was not significantly affected by the reinforced soil.
Stress stress-strain behavior of hydraulic filled coral sand subjected to internal erosion
Authors: Ding H Z , Wang X Z , Wen D S , Peng H , Liu K C 
Published: May 2024

Abstract
Coral sand foundations lose fine particles under the action of groundwater infiltration. As the soil skeleton structure deteriorates, the foundation becomes uneven and may even collapse. In this study, a triaxial drainage shear test of coral sand is used as a quantitative control method for the loss of fine particulate soil, and the effect of internal erosion on the mechanical behavior of coral sand is evaluated. An experiment is used to demonstrate that erosion leads to a decrease in the peak shear strength and residual strength of coral sand. Erosion has different effects on coral sand with different fine particle contents, and the effects on the friction angles of coral and terrestrial sand are also different. The secant modulus E50 and peak secant modulus Ep gradually decrease as the loss of fine particles increases. The effect of fine particle loss on the peak secant modulus Ep is significant at fine-particle losses exceeding 10% for a fine-particle content of 20%. The loss of fine particles creates new pore spaces in the coral sand, which, in turn, affects the stability of the original soil skeleton. Erosion has been shown to have an effect on the gradational features of coral sand, leading to the phenomenon that the dilatancy effect increases as a function of the amount of erosion that takes place. To prevent uneven foundation settlement caused by subsurface erosion in engineering designs, it is important to consider the gradation characteristics and fine particulate content of coral sand, which affect the stability of coral reef foundations.
Electric steelmaking process monitoring with optical emission spectroscopy – An in-depth review
Authors: Rautioaho Arto , Pauna Henri , Visuri Ville-Valtteri , Huttula Marko , Fabritius Timo 
Published: May 2024

Abstract
Electric steelmaking plays an important role in various scenarios for environmentally friendly steelmaking where the processes must be energetically and economically feasible. As electric furnaces’ capacities and low-grade recycled material usage can be expected to increase, optimizing the process practices and flexibility becomes paramount. The high-temperature environment of electric steelmaking sets several criteria for the implemented tools, where the equipment must withstand extreme conditions, have a low maintenance need and cost, and have the capability of real-time data acquisition and analysis. Optical emission spectroscopy (OES) has been studied in laboratory furnaces and on pilot and industrial scales to provide an in situ method for electric arc furnace and ladle furnace process control. Since OES is a method that measures the properties of emitted light, the applications focus on the electric arc plasma, burners’ flames, and heat radiation from the molten bath. The optical spectra carry information on the composition, temperature, and status of the process. This in-depth review compiles the research and usage of OES as a process monitoring tool by focusing on electric arc plasma, burner flames, and molten bath radiation. Suggestions for further development of existing applications and potential new applications are discussed.