• KSCE Journal of Civil and Environmental Engineering Research
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• 제28권4A호
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• pp.581-590
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• 2008

The panels are used as a composite part of the completed deck. They replace the main bottom transverse deck reinforcement and also serve as a form surface for the cast-in-place concrete upper layer that contains the top of deck reinforcement. In this paper, three types of the detail for joints was selected and their structural performance in terms of strength and crack contral was investigated through static tests on composite beams. Form the results, the validity of loop joints for continuity of half-depth precast deck was observed and especially an overlapping length of loop joint and transverse reinforcement were checked. The results suggest that increasing the loop overlapping length increases the flexural strength of half-depth precast deck with loop joints. In terms of crack contral, the loop joint with transverse reinforcement showed better performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제26권4A호
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• pp.659-675
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• 2006

Recently, significant progress has been made in performance-based engineering methods that rely mainly on nonlinear static seismic analysis procedures. The Capacity Spectrum Method (CSM) and the Displacement Coefficient Method (DCM) are the representative nonlinear static seismic analysis procedures. In order to evaluate the applicability of the procedures to the seismic evaluation and design process of new and existing structures, the accuracy of both CSM and DCM should be evaluated in advance. The accuracy of seismic responses by the nonlinear static procedures is evaluated in comparison with the shaking table test results for the structural wall specimen subjected to the far field and near field earthquakes. Also conducted are comparative studies where the shaking table test results are compared with those from nonlinear dynamic analysis procedures, i.e., Single-Degree-of-Freedom (SDOF), equivalent SDOF and Multi-Degree-of-Freedom (MDOF) systems.

• Journal of Korean Tunnelling and Underground Space Association
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• 제12권3호
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• pp.223-237
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• 2010

The initial heating rate is well known as one of the most influencing factors on the occurrence of spalling and the loss of strength in concrete after fire initiation. In this study, a series of fire tests were carried out at different initial heating rates to find out its effects on the deterioration of tunnel structural members. Heat transfer analyses combined with an element elimination model were also carried out to verify its applicability in the same conditions as the fire tests. Moreover, the convection heat transfer coefficients compatible with fire test results were derived from parametric studies. In this course, their time-dependent variations were also analyzed at different initial heating rates. Finally, a numerical formula to estimate the heat transfer coefficients at the various initial heating rates was proposed by the interpolation of the results of numerical analyses.

• Journal of Korean Tunnelling and Underground Space Association
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• 제12권6호
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• pp.451-461
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• 2010

Utilization of the fiber reinforced polymer (FRP) material has been enlarged as a substitution material to the general construction materials having certain long-term problems such as corrosion, etc. However, it could be difficult to apply the FRP material, which has a linear shape generally, to an arch-shaped tunnel structure. Therefore, an attempt has been made in this study to develop a device to form a designed cross section of FRP material by pulling out with a curvature. A sample of the circled FRP product was successfully produced and then the sample has been tested to identify its physical characteristics. Then, intensive feasibility studies on the circled FRP panel to be used for a tunnel lining structure have been carried out by numerical analyses. As a result, it appears that the new circled FRP-concrete composite panel has a high capability to be used for a tunnel lining material without any structural problem.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제30권1A호
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• pp.35-43
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• 2010

The panels are used as a composite part of the completed deck. They replace the main bottom transverse deck reinforcement and also serve as a form surface for the cast-in-place concrete upper layer that contains the top of deck reinforcement. However, in order to apply the precast panels to bridges properly, it is necessary to fully understand the structural characteristics of joint in precast panels. Particularly, since the bridge deck is under repeated loads such as traffic loads, fatigue behavior and characteristics of joint should be investigated. In this paper, fatigue tests of composite deck with shear ties and loop joints were conducted. The fatigue tests were conducted with an application of repeated loading and wheel loading. Test results were analyzed to examine the current design code for fatigue of reinforcement bar and serviceability under repeated loading.

• Structural Engineering and Mechanics
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• 제84권3호
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• pp.345-360
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• 2022

In this paper, the impact on seismic performance of an economical effective technique for retrofitting reinforced concrete (RC) columns using high-strength steel strips under high axial compression ratios was presented. The experimental program included a series of cyclic loading tests on one nonretrofitted control specimen and three retrofitted specimens. The effects of the axial compression ratio and spacing of the steel strips on the cyclic behavior of the specimens were studied. Based on the test results, the failure modes, hysteretic characteristics, strength and stiffness degradation, displacement ductility, and energy dissipation capacity of the specimens were analyzed in-depth. The analysis showed that the transverse confinement provided by the high-strength steel strips could effectively delay and restrain diagonal crack development and improve the failure mode, which was flexural-shear failure controlled by flexural failure with better ductility. The specimens retrofitted using high-strength steel strips showed more satisfactory seismic performance than the control specimen. The seismic performance and deformation capacity of the retrofitted RC columns increased with decreasing axial compression ratio and steel strip spacing. Based on the test results, a hysteretic model for RC columns that considers the transverse confinement of high-strength steel strips was then established. The hysteretic model showed good agreement with the experimental results, which verified the effectiveness of the proposed hysteretic model. Therefore, the aforementioned analysis can be used for the design of retrofitted RC columns.

• Smart Structures and Systems
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• 제32권5호
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• International Journal of Internet, Broadcasting and Communication
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• 제16권2호
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• pp.237-246
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• 2024

In recent years, the frequent occurrence of fire accidents in university libraries has posed significant threats to the safety of students' lives and property, alongside negative social impacts. Accurately analyzing the factors affecting evacuation during library fires and proposing optimized measures for safe evacuation is thus crucial. This paper utilizes a specific university library as a case study, simulating fire evacuation scenarios using the Pathfinder software, to assess and validate evacuation strategies and propose relevant optimizations. Pathfinder, developed by Thunderhead Engineering in the United States, is an intuitive and straightforward personnel emergency evacuation assessment system, offering advanced visualization interfaces and 3D animation effects. This study aims to construct evacuation models and perform simulation analysis for the selected university library using Pathfinder. The library's structural layout, people flow characteristics, and the nature of fire and smoke spread are considered in the analysis. Additionally, evacuation scenarios involving different fire outbreak locations and the status of emergency exits are examined. The findings underscore the importance of effective evacuation in fire situations, highlighting how environmental conditions, individual characteristics, and behavioral patterns significantly influence evacuation efficiency. Through these investigations, the study enhances understanding and optimization of evacuation strategies in fire scenarios, thereby improving safety and efficiency. The research not only provides concrete and practical guidelines for building design, management, and emergency response planning in libraries but also offers valuable insights for the design and management of effective evacuation systems in buildings, crucial for ensuring occupant safety and minimizing loss of life in potential hazard situations

• Steel and Composite Structures
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• 제51권5호
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• pp.509-527
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• 2024

Bonding carbon fiber-reinforced polymer (CFRP) laminates have been extensively employed in the restoration of steel constructions. In addition to the mechanical properties of the CFRP, the bond strength (P_U) between the CFRP and steel is often important in the eventual strengthened performance. Nonetheless, the bond behavior of the CFRP-steel (CS) interface is exceedingly complicated, with multiple failure causes, giving the P_U challenging to forecast, and the CFRP-enhanced steel structure is unsteady. In just this case, appropriate methods were established by hybridized Random Forests (RF) and support vector regression (SVR) approaches on assembled CS single-shear experiment data to foresee the P_U of CS, in which a recently established optimization algorithm named Aquila optimizer (AO) was used to tune the RF and SVR hyperparameters. In summary, the practical novelty of the article lies in its development of a reliable and efficient method for predicting bond strength at the CS interface, which has significant implications for structural rehabilitation, design optimization, risk mitigation, cost savings, and decision support in engineering practice. Moreover, the Fourier Amplitude Sensitivity Test was performed to depict each parameter's impact on the target. The order of parameter importance was t_c> L_c > E_A > t_A > E_c > b_c > f_c > f_A from largest to smallest by 0.9345 > 0.8562 > 0.79354 > 0.7289 > 0.6531 > 0.5718 > 0.4307 > 0.3657. In three training, testing, and all data phases, the superiority of AO - RF with respect to AO - SVR and MARS was obvious. In the training stage, the values of R² and VAF were slightly similar with a tiny superiority of AO - RF compared to AO - SVR with R² equal to 0.9977 and VAF equal to 99.772, but large differences with results of MARS.

• Journal of Korean Association for Spatial Structures
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• 제24권3호
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• pp.43-51
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• 2024

Dynamic responses of nuclear power plant structure subjected to earthquake loads should be carefully investigated for safety. Because nuclear power plant structure are usually constructed by material of reinforced concrete, the aging deterioration of R.C. have no small effect on structural behavior of nuclear power plant structure. Therefore, aging deterioration of R.C. nuclear power plant structure should be considered for exact prediction of seismic responses of the structure. In this study, a machine learning model for seismic response prediction of nuclear power plant structure was developed by considering aging deterioration. The OPR-1000 was selected as an example structure for numerical simulation. The OPR-1000 was originally designated as the Korean Standard Nuclear Power Plant (KSNP), and was re-designated as the OPR-1000 in 2005 for foreign sales. 500 artificial ground motions were generated based on site characteristics of Korea. Elastic modulus, damping ratio, poisson's ratio and density were selected to consider material property variation due to aging deterioration. Six machine learning algorithms such as, Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost), were used t o construct seispic response prediction model. 13 intensity measures and 4 material properties were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks present good prediction performance considering aging deterioration.