KSCE Journal of Civil Engineering最新文献

In order to calculate the fatigue deflection of prestressed concrete (PC) beams, a fatigue variable stiffness distribution (VSD) model based on crack development pattern extracted from fatigue test is presented in this study. Firstly, a linear strain distribution model along the transfer length of concrete and steel bar was established. And the stress analysis of different cross-sections along the transfer length was performed in order to calculate the average moment of inertia in the fatigue crack zone of PC beam. Then, combined with the characterization model of concrete fatigue modulus, a fatigue VSD model for PC beams was established. The model validation shows that the calculated deflections are in good agreement with the measured deflections, and the deviation does not exceed ±10%. Furthermore, the quantitative reverse deduction of fatigue damage based on stiffness index was carried out. And the multi-stage development laws of stiffness degradation and damage evolution under fatigue loading were summarized. Finally, combined with the setting of fatigue failure threshold, the critical point of the PC beam entering the failure state can be reasonably determined. which provides a reference for the assessment of structural service status. The stiffness threshold of the fatigue failure criterion is about 70%, and the damage threshold is about 0.6 for this study. The research results can provide a theoretical basis for the structural performance analysis and failure assessment for PC beams.

Artificial Ground Freezing (AGF) is a promising method for controlling seepage in permeable strata. However, AGF faces challenges, including difficulties in achieving a frozen barrier in high-flow conditions and concerns about cost-effectiveness. This study optimizes freezing pipe placement in AGF using a simulated annealing algorithm and a coupled hydrothermal finite element model, focusing on AGF system responses under varying seepage velocities. The optimized layout significantly reduces freeze-ring formation time (by 2.5 days) and the overall freezing duration (by 12.5 days). Moreover, it substantially decreases the required frozen soil volume, facilitating drilling and excavation. Across different seepage velocities, the difference in freeze-ring formation time between the optimized and uniform layouts gradually increases with higher seepage velocity, reaching a maximum difference of 5.9 days. Finally, the relationship between freezing time and seepage velocity was quantitatively described using exponential functions. This study underscores the critical role of optimizing freezing pipe placement in AGF, providing a foundation for efficient and cost-effective geotechnical engineering practices.

This paper analyzes the influence of different factors on the train-induced vibration response of newly-built underpass. These factors include the train operation mode (T), train speed (V), the thickness ratio of the underpass roof slab to the upper station floor slab (R_RF), the thickness ratio of the middle wall to the side wall of the underpass (R_MS), and the void defect between the underpass roof and the upper station floor (V_RF). On this basis, the sensitivity of the above factors to the underpass vibration response induced by existing trains is discussed. The results demonstrate that all the above factors have a great effect on the peak acceleration and peak amplitude of the underpass roof. The calculation results of T show no significant differences. Both peak acceleration and amplitude increase rapidly and non-linearly with increasing V. The acceleration response and peak amplitude of the underpass can be significantly reduced by R_RF and R_MS but aggravated by V_RF. The acceleration response distribution of the underpass is always symmetrical, and these factors have little influence on this symmetrical. Based on preliminary design parameters, the sensitivity of these factors on the acceleration response of underpass is ranked as V > R_RF > V_RF > R_MS > T.

In-situ lateral load tests were conducted on rectangular piles in gravelly soil before and after grouting to investigate the impact of combined side and end grouting on lateral bearing capacity and the failure mode of pile-soil interaction. The results indicate that this combined grouting technique significantly enhanced the lateral bearing capacity of the pile, achieving a 30% increase compared to before grouting. After grouting, the bonding state between the pile and the soil improved, resulting in the formation of tension-shear cracks within the soil on the side of the pile under lateral load. The load-displacement curve of the rectangular pile exhibited nonlinearity, with the deflection deformation showing the load characteristics of an elastic long pile. The bilinear model can accurately assess the actual bearing capacity of the rectangular pile. Comparing the theoretical model predictions with the experimental data, the prediction errors were −3.5% and 1.8% before and after grouting, respectively.

This study aimed to examine corrosion-resistance performance of epoxy-coated reinforcements and galvanized reinforcements, among the most widely used anti-corrosion reinforcements. Five types of specimens were used, as follows: (a) Black bar, (b) Black bar coated with epoxy, (c) Black bar galvanized, (d) Black bar coated with epoxy with surface damage, and (e) Black bar galvanized with surface damage. Epoxy-coated bar specimen showed excellent corrosion resistance performance. In the presence of a surface damage, however, corrosion was intensively concentrated near the damage. In the galvanized bar specimen, a trace of light corrosion was observed throughout the surface. This meant that its corrosion resistance performance was rather inferior compared to the epoxy-coated bar specimen. However, the performance remained almost the same with or without a surface damage due to the sacrificial anode effect of zinc. The relative corrosion current density of the galvanized bar specimen was about 1/7 that of the epoxy-coated bar specimen on average. Galvanized reinforcements were capable of continuously providing excellent anti-corrosion performance even in the presence of surface damage formed at the construction field. The suspension concentration density of corrosion products in the cell solution showed a high correlation with other corrosion data.

To examine the impact of inner lining defects on the mechanical behavior of double-shell structures and validate the efficacy of the shield tunnel support system, similar model tests were employed to analyze the deformation characteristics, internal force distribution, damage progression, and interaction strength of double-shell lining structures with inner lining defects in three typical locations (crown, shoulder and waist) under ultimate loads. This study discloses how inner lining defects affect the load-bearing capacity of the double-shell structure and makes recommendations. The results show that (1) The existence of defects in the inner lining makes the deformation of the double-shell lining structure under the action of external loads uncoordinated. The overall load-bearing capacity of the structure decreases by 33% to 50%. (2) Local stress concentrations and increased eccentricity lead to a significant increase in the internal force proportion and failure of the defective inner lining, thus failing to limit the deformation of the segments and the early damage of the double-shell lining structure. (3) Of the three locations studied, the impact of inner lining defect position on the mechanical behavior of the double-shell structure follows this ranking: arch waist most impactful, crown weaker than arch waist, least impactful at shoulder.

In the present study, a zinc phosphate coating was deposited on steel fiber surface and the morphology and corrosion resistance of the coating were investigated. An accelerated corrosion method was utilized to corrode steel bars embedded in concrete, and the impact of adding fibers on the performance of reinforced concrete structures after the accelerated corrosion test was examined. The results revealed that the coating primarily consisted of hopeite phase, exhibiting a dense and uniform structure. The corrosion resistance of the coated steel fibers was significantly enhanced compared to uncoated fibers. Furthermore, the fiber-reinforced specimens exhibited lower levels of corrosion and improved bond performance in comparison to reinforced plain concrete specimens. The bond strength between the reinforcement and concrete in the fiber-reinforced specimens with zinc phosphate coated steel fibers increased by 28.1% (before corrosion) and 112.9% (after corrosion) compared to plain concrete. The reduced porosity and high impermeability of the concrete matrix containing zinc phosphate coated steel fibers contributed to the delayed migration of chloride ions and protection of the reinforcement against corrosion. These findings suggest that zinc phosphate coated steel fibers have great potential for large-scale production of reinforced concrete structures.

Global warming worldwide is the reason for the increasing number of meteorological disasters causing severe property damage and human casualties. Railways are a key social infrastructure; however, quantitative and empirical research into the impact of weather changes due to global warming has not been done adequately. Thus, this study aims to develop a predictive model using a deep learning algorithm to quantify the relationship between fatal rail accidents and weather conditions. The proposed framework utilizes the Deep Neural Network (DNN) technique trained with past rail accidents and weather data. The model performance was evaluated using error metrics (mean absolute error (MAE) and root-mean-square error (RMSE)) and compared with widely used regression techniques. The findings showed that the DNN model achieved lower RMSE and MAE compared to the multi-regression, random forest and support vector machine models, with a reduction in prediction error ranging from 1.04% to 20.78% in RMSE and 5.0% to 15.3% in MAE. This exhibits the DNN model’s effectiveness in capturing complex relationships within the data and delivering more accurate predictions compared to the other models. The approach and outcomes of this study provide essential guidelines for the efficient and safe maintenance and optimized safety management of railway services.

A set of finite element investigations are performed to examine the maximum bearing strength of strip footings positioned on the crest of a cohesive-frictional marginal soil hillslope. In this regard, the influence of contributing geometrical and geotechnical parameters on the maximum bearing strength of the footing are illustrated. It is revealed that the nearness of slope face has negligible influence on the bearing strength of footing if it is located at a setback distance beyond six times the footing width. Further, using multi-gene genetic programming technique, a predictive relationship between the maximum bearing strength and the contributory factors is established and validated through relevant experimental findings. The hyper-parameters of the MGGP model are suitably optimized, as indicated by the coefficient of correlation attaining high magnitudes. A sensitivity analysis based on local perturbation is conducted to recognize the importance ranking of the contributory parameters. It is revealed that the friction angle of slope material predominantly influences the evaluation of maximum bearing strength for strip footing on slopes, followed by other contributing factors.

Addressing the challenge of large deformation in soft rock tunnels is an urgent imperative. The conventional support method is mainly passive or low-stress compensation support, which proves inadequate in effectively managing the large deformation disaster of soft rock under complex geological conditions. This paper focuses on three representative soft rock tunnel scenarios characterized by slate, schist, and metamorphic rock lithologies. The primary objective is to conduct a comprehensive comparative analysis of the efficacy of the NPR (negative Poisson’s ratio effect) anchor cable high preload support system based on the excavation compensation method. The results indicate that the NPR high preload support method adeptly controls large deformation disasters in soft rock, maintaining tunnel surrounding rock deformation within 300 mm (<3%). To achieve efficient high-stress compensation through high preload, supporting technologies should be designed for different geological conditions, exemplified by the implementation of double-gradient grouting technology in the Tabaiyi tunnel. This paper comprehensively validates the effectiveness of the NPR high preload support method in mitigating large deformations in soft rock and establishes a foundation for future engineering endeavors.