• Steel and Composite Structures
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• v.51 no.2
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• pp.117-126
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• 2024

There are many challenges in the construction of large-section tunnels, such as extremely soft rock and fractured zones. In order to solve these problems, the confined concrete support technology is proposed to control the surrounding rocks. The large-scale laboratory test is carried out to clarify mechanical behaviours of the combined confined concrete and traditional I-steel arches. The test results show that the bearing capacity of combined confined concrete arch is 3217.5 kN, which is 3.12 times that of the combined I-steel arch. The optimum design method is proposed to select reasonable design parameters for confined concrete arch. The parametric finite element (FE) analysis is carried out to study the effect of the design factors via optimum design method. The steel pipe wall thickness and the longitudinal connection ring spacing have a significant effect on the bearing capacity of the combined confined concrete arch. Based on the above research, the confined concrete support technology is applied on site. The field monitoring results shows that the arch has an excellent control effect on the surrounding rock deformation. The results of this research provide a reference for the support design of surrounding rocks in large-section tunnels.

• Steel and Composite Structures
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• v.51 no.2
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• pp.185-202
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• 2024

In this research paper, and for the first time, wave propagations in sigmoidal imperfect functionally graded material plates are investigated using a simplified quasi-three-dimensionally higher shear deformation theory (Quasi-3D HSDTs). By employing an indeterminate integral for the transverse displacement in the shear components, the number of unknowns and governing equations in the current theory is reduced, thereby simplifying its application. Consequently, the present theories exhibit five fewer unknown variables compared to other Quasi-3D theories documented in the literature, eliminating the need for any correction coefficients as seen in the first shear deformation theory. The material properties of the functionally graded plates smoothly vary across the cross-section according to a sigmoid power law. The plates are considered imperfect, indicating a pore distribution throughout their thickness. The distribution of porosities is categorized into two types: even or uneven, with linear (L)-Type, exponential (E)-Type, logarithmic (Log)-Type, and Sinus (S)-Type distributions. The current quasi-3D shear deformation theories are applied to formulate governing equations for determining wave frequencies, and phase velocities are derived using Hamilton's principle. Dispersion relations are assumed as an analytical solution, and they are applied to obtain wave frequencies and phase velocities. A comprehensive parametric study is conducted to elucidate the influences of wavenumber, volume fraction, thickness ratio, and types of porosity distributions on wave propagation and phase velocities of the S-FGM plate. The findings of this investigation hold potential utility for studying and designing techniques for ultrasonic inspection and structural health monitoring.

• Steel and Composite Structures
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• v.51 no.2
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• pp.153-172
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• 2024

Due to the fast development of constructions in recent years, there has been a rapid consumption of fresh water and river sand. In the production of concrete, alternatives such as sea water and sea sand are available. The near surface mounted (NSM) technique is one of the most important methods of strengthening. Aluminum alloy (AA) bars are non-rusting and suitable for usage with sea water and sand concrete (SSC). The goal of this study was to enhance the shear behaviour of SSC-beams strengthened with NSM AA bars. Twenty-four RC beams were cast from fresh water river sand concrete (FRC) and SSC before being tested in four-point flexure. All beams are the same size and have the same internal reinforcement. The major factors are the concrete type (FRC or SSC), the concrete degree (C25 or C50 with compressive strength = 25 and 50 MPa, respectively), the presence of AA bars for strengthening, the direction of AA bar reinforcement (vertical or diagonal), and the AA bar ratio (0, 0.5, 1, 1.25 and 2 %). The beams' failure mechanism, load-displacement response, ultimate capacity, and ductility were investigated. Maximum load and ductility of C25-FRC-specimens with vertical and diagonal AA bar ratios (1%) were 100,174 % and 140, 205.5 % greater, respectively, than a matching control specimen. The ultimate load and ductility of all SSC-beams were 16-28 % and 11.3-87 % greater, respectively, for different AA bar methods than that of FRC-beams. The ultimate load and ductility of C25-SSC-beams vertically strengthened with AA bar ratios were 66.7-172.7 % and 89.6-267.9 % higher than the unstrengthened beam, respectively. When compared to unstrengthened beams, the ultimate load and ductility of C50-SSC-beams vertically reinforced with AA bar ratios rose by 50-120 % and 45.4-336.1 %, respectively. National code proposed formulae were utilized to determine the theoretical load of tested beams and compared to matching experimental results. The predicted theoretical loads were found to be close to the experimental values.

• Korean Journal of Occupational Health Nursing
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• v.33 no.1
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• pp.12-25
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• 2024

Purpose: This quasi-experimental study used a non-equivalent control group pretest-posttest design with clinical nurses to develop a compassion improvement program and verify its effects on compassion competence and empathic communication. Methods: The Triandis Interpersonal Behavior model (Triandis, 1980) was used as a theoretical framework, and a compassion improvement program was developed based on the ADDIE model. The experimental treatment in the program was conducted for 120 minutes per session, once a week, for a total of six sessions. The data collection and research period ranged from September 7 to November 16. It involved a pre-survey of measured variables, six sessions of experimental treatment, a post-survey, and a follow-up survey in sequence. The collected data were analyzed using the statistical program SPSS/WIN 25.0 and then based on a t-test and repeated measures ANOVA to verify the effectiveness of the program. Results: Clinical nurses participating in the compassion improvement program showed improved compassion competence (F=8.00, p=.001) due to the cultivation of insight, sensitivity, and communication skills. In addition, the improvement in attentive listening (F=3.32, p=.024) indicated that the program was partially effective in empathic communication. Conclusion: The compassion improvement program for clinical nurses, which was developed in this study, is expected to be useful in nursing practice. In other words, the compassion improvement program may contribute to creating a positive atmosphere in the workplace for nurses and an empathic relationship between nurses and healthcare recipients through improvement in the compassion competence of nurses. If the compassion improvement program is continuously implemented as a facilitating condition, it will greatly help prevent the turnover of clinical nurses, assist them in adapting to hospital life, and enhance the quality of nursing care.

• Earthquakes and Structures
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• v.26 no.4
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• pp.311-326
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• 2024

Transmission tower structures are particularly susceptible to damage and even collapse under strong seismic ground motions. Conventional seismic analyses of transmission towers are usually performed by considering only ground motion uncertainty while ignoring structural uncertainty; consequently, the performance evaluation and failure prediction may be inaccurate. In this context, the present study numerically investigates the seismic responses and failure mechanism of transmission towers by considering multiple sources of uncertainty. To this end, an existing transmission tower is chosen, and the corresponding three-dimensional finite element model is created in ABAQUS software. Sensitivity analysis is carried out to identify the relative importance of the uncertain parameters in the seismic responses of transmission towers. The numerical results indicate that the impacts of the structural damping ratio, elastic modulus and yield strength on the seismic responses of the transmission tower are relatively large. Subsequently, a set of 20 uncertainty models are established based on random samples of various parameter combinations generated by the Latin hypercube sampling (LHS) method. An uncertainty analysis is performed for these uncertainty models to clarify the impacts of uncertain structural factors on the seismic responses and failure mechanism (ultimate bearing capacity and failure path). The numerical results show that structural uncertainty has a significant influence on the seismic responses and failure mechanism of transmission towers; different possible failure paths exist for the uncertainty models, whereas only one exists for the deterministic model, and the ultimate bearing capacity of transmission towers is more sensitive to the variation in material parameters than that in geometrical parameters. This research is expected to provide an in-depth understanding of the influence of structural uncertainty on the seismic demand assessment of transmission towers.

• Earthquakes and Structures
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• v.26 no.4
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• pp.261-267
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• 2024

With the increase in the exploitation depth of offshore oil and gas, it is possible to control the global buckling of deep-sea pipelines by the snake lay method. Previous studies mainly focused on the analysis of critical buckling force and critical temperature of pipelines under the snake-like laying method, and pipelines often suffer structural failure due to seismic disasters during operation. Therefore, seismic action is a necessary factor in the design and analysis of submarine pipelines. In this paper, the seismic action of steel pipes in the operation stage after global buckling has occurred under the active control method is analyzed. Firstly, we have established a simplified finite element model for the entire process cycle and found that this modeling method is accurate and efficient, solving the problem of difficult convergence of seismic wave and soil coupling in previous solid analysis, and improving the efficiency of calculations. Secondly, through parameter analysis, it was found that under seismic action, the pipe diameter mainly affects the stress amplitude of the pipeline. When the pipe wall thickness increases from 0.05 m to 0.09 m, the critical buckling force increases by 150%, and the maximum axial stress decreases by 56%. In the pipe soil interaction, the greater the soil viscosity, the greater the pipe soil interaction force, the greater the soil constraint on the pipeline, and the safer the pipeline. Finally, the pipeline failure determination formula was obtained through dimensionless analysis and verified, and it was found that the formula was accurate.

• Computers and Concrete
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• v.33 no.4
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• pp.399-407
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• 2024

This study nondestructively examined the evolution of crack density in ultra-high performance concrete (UHPC) upon cyclic loading. Uniaxial compression was repeatedly applied to the cylindrical specimens at levels corresponding to 32% and 53% of the maximum load-bearing capacity, each at a steady strain rate. At each stage, both P-wave and S-wave velocities were measured in the absence of the applied load. In particular, the continuous monitoring of P-wave velocity from the first loading prior to the second loading allowed real-time observation of the strengthening effect during loading and the recovery effect afterwards. Increasing the number of cycles resulted in the reduction of both elastic wave velocities and Young's modulus, along with a slight rise in Poisson's ratio in both tested cases. The computed crack density showed a monotonically increasing trend with repeated loading, more significant at 53% than at 32% loading. Furthermore, the spatial distribution of the crack density along the height was achieved, validating the directional dependency of microcracking development. This study demonstrated the capability of the crack density to capture the evolution of microcracks in UHPC under cyclic loading condition, as an early-stage damage indicator.

• Computers and Concrete
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• v.33 no.4
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• pp.341-348
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• 2024

Ultra-high-performance concrete (UHPC) has received remarkable attentions in civil infrastructure due to its unique mechanical characteristics and durability. UHPC gains increasingly dominant in essential structural elements, while its unique properties pose challenges for traditional inspection methods, as damage may not always manifest visibly on the surface. As such, the need for robust inspection techniques for detecting cracks in UHPC members has become imperative as traditional methods often fall short in providing comprehensive and timely evaluations. In the era of artificial intelligence, computer vision has gained considerable interest as a powerful tool to enhance infrastructure condition assessment with image and video data collected from sensors, cameras, and unmanned aerial vehicles. This paper presents a computer vision-based approach employing deep learning to detect cracks in UHPC beams, with the aim of addressing the inherent limitations of traditional inspection methods. This work leverages computer vision to discern intricate patterns and anomalies. Particularly, a convolutional neural network architecture employing transfer learning is adopted to identify the presence of cracks in the beams. The proposed approach is evaluated with image data collected from full-scale experiments conducted on UHPC beams subjected to flexural and shear loadings. The results of this study indicate the applicability of computer vision and deep learning as intelligent methods to detect major and minor cracks and recognize various damage mechanisms in UHPC members with better efficiency compared to conventional monitoring methods. Findings from this work pave the way for the development of autonomous infrastructure health monitoring and condition assessment, ensuring early detection in response to evolving structural challenges. By leveraging computer vision, this paper contributes to usher in a new era of effectiveness in autonomous crack detection, enhancing the resilience and sustainability of UHPC civil infrastructure.

• Computers and Concrete
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• v.33 no.4
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• pp.425-443
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• 2024

Floods are among the most common natural hazards in urban areas. To mitigate the problems caused by flooding, unstructured data such as images and videos collected from closed circuit televisions (CCTVs) or unmanned aerial vehicles (UAVs) have been examined for flood management (FM). Many computer vision (CV) techniques have been widely adopted to analyze imagery data. Although some papers have reviewed recent CV approaches that utilize UAV images or remote sensing data, less effort has been devoted to studies that have focused on CCTV data. In addition, few studies have distinguished between the main research objectives of CV techniques (e.g., flood depth and flooded area) for a comprehensive understanding of the current status and trends of CV applications for each FM research topic. Thus, this paper provides a comprehensive review of the literature that proposes CV techniques for aspects of FM using ground camera (e.g., CCTV) data. Research topics are classified into four categories: flood depth, flood detection, flooded area, and surface water velocity. These application areas are subdivided into three types: urban, river and stream, and experimental. The adopted CV techniques are summarized for each research topic and application area. The primary goal of this review is to provide guidance for researchers who plan to design a CV model for specific purposes such as flood-depth estimation. Researchers should be able to draw on this review to construct an appropriate CV model for any FM purpose.

• Ocean Systems Engineering
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• v.14 no.1
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• pp.85-99
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• 2024

Ocean surface currents have an essential role in the Earth's climate system and significantly impact the marine ecosystem, weather patterns, and human activities. However, predicting ocean surface currents remains challenging due to the complexity and variability of the oceanic processes involved. This review article provides an overview of the current research status, challenges, and opportunities in the prediction of ocean surface currents. We discuss the various observational and modelling approaches used to study ocean surface currents, including satellite remote sensing, in situ measurements, and numerical models. We also highlight the major challenges facing the prediction of ocean surface currents, such as data assimilation, model-observation integration, and the representation of sub-grid scale processes. In this article, we suggest that future research should focus on developing advanced modeling techniques, such as machine learning, and the integration of multiple observational platforms to improve the accuracy and skill of ocean surface current predictions. We also emphasize the need to address the limitations of observing instruments, such as delays in receiving data, versioning errors, missing data, and undocumented data processing techniques. Improving data availability and quality will be essential for enhancing the accuracy of predictions. The future research should focus on developing methods for effective bias correction, a series of data preprocessing procedures, and utilizing combined models and xAI models to incorporate data from various sources. Advancements in predicting ocean surface currents will benefit various applications such as maritime operations, climate studies, and ecosystem management.