• Journal of Korean Society of Steel Construction
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• v.16 no.2 s.69
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• pp.235-245
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• 2004

The advantages of composite construction are now well understood in terms of structural economy, good performance in service, and ease of construction. However, these conventional composite construction systems have some problems in application to steel framed buildings due to their large depth. So, in this study we executed an experimental test with the "Slim Floor"system which could reduce the overall depth of composite beam. Slim Floor system is a method of steel frame multi-story building construction in which the structural depth of each floor is minimized by incorporating the steel floor beams within the depth of the concrete floor slab. Presented herein is an experimental study that focuses on the flexural behaviour of the partially connected slim floor system with asymmetric steel beams encased in composite concrete slabs. Eight full-scale specimens were constructed and tested in this study with different steel beam height, slab width, with or without shear connection and concrete topping thickness. Observations from experiments indicated that the degree of shear connection without additional shear connection was $0.53{\sim}0.95$ times that of the full shear connection due to inherent mechnical and chemical bond stress.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.303-310
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• 2021

Cracks in bridges are important factors that indicate the condition of bridges and should be monitored periodically. However, a visual inspection conducted by a human expert has problems in cost, time, and reliability. Therefore, in recent years, researches to apply a deep learning model are started to be conducted. Deep learning requires sufficient data on the situations to be predicted, but bridge crack data is relatively difficult to obtain. In particular, it is difficult to collect a large amount of crack data in a specific situation because the shape of bridge cracks may vary depending on the bridge's design, location, and construction method. This study developed a crack detection model that generates and trains insufficient crack data through a Generative Adversarial Network. GAN successfully generated data statistically similar to the given crack data, and accordingly, crack detection was possible with about 3% higher accuracy when using the generated image than when the generated image was not used. This approach is expected to effectively improve the performance of the detection model as it is applied when crack detection on bridges is required, though there is not enough data, also when there is relatively little or much data f or one class.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.375-380
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• 2022

High-speed railway bridges carry a risk of dynamic response amplification due to resonance caused by train loads, and running safety and riding comfort must therefore be reviewed through dynamic analysis in accordance with design codes. The running safety and ride comfort calculation procedure, however, is time consuming and expensive because dynamic analyses must be performed for every 10 km/h interval up to 110% of the design speed, including the critical speed for each train type. In this paper, a deep-learning-based prediction system that can predict the running safety and ride comfort in advance is proposed. The system does not use dynamic analysis but employs a deep learning algorithm. The proposed system is based on a neural network trained on the dynamic analysis results of each train and speed of the railway bridge and can predict the running safety and ride comfort according to input parameters such as train speed and bridge characteristics. To confirm the performance of the proposed system, running safety and riding comfort are predicted for a single span, straight simple beam bridge. Our results confirm that the deck vertical displacement and deck vertical acceleration for calculating running safety and riding comfort can be predicted with high accuracy.

• Wind and Structures
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• v.6 no.1
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• pp.53-70
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• 2003

Tsing Ma Bridge in Hong Kong is the longest suspension bridge in the world carrying both highway and railway. It has two H-shape concrete towers, each of which is composed of two reinforced concrete legs and four deep transverse prestressed concrete beams. A series of wind tunnel tests have been performed to measure the aerodynamic coefficients of the tower legs and transverse beams in various arrangements. A 1:100 scaled 3D rigid model of the full bridge tower assembled from various tower components has been constructed for different test cases. The aerodynamic coefficients of the lower and upper segments of the windward and leeward tower legs and those of the transverse beams at different levels, with and without the dummy bridge deck model, were measured as a function of yaw wind angle. The effects of wind interference among the tower components and the influence of the bridge deck on the tower aerodynamic coefficients were also investigated. The results achieved can be used as the pertinent data for the comparison of the computed and field-measured fully coupled buffeting responses of the entire bridge under yaw winds.

• Fire Science and Engineering
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• v.31 no.6
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• pp.40-46
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• 2017

As one of the solutions to deal with economic loss caused by traffic congestion in metropolitan area, a deep underground road has been planned and implemented at home and abroad. The part of them has been pushed ahead with a double-deck scheme which has an advantage in constructability and cost efficiency comparing to traditional road tunnel. However, the double-deck tunnel has a lower floor height than the general road tunnel due to the special structure used as the upper and lower lines by installing the middle slab on one excavation section. Therefore, it is relatively weak against fire accidents and ventilation problems occurring in tunnels. Thus study to develop the life safety system optimized to a double-deck tunnel has been systematically carried out in order to overcome their weak point. In this study, automatic monitoring fire extinguisher (AMFE) is developed to suppress a fire and prevent its spread at early stage of tunnel fire, conducting the performance test through vehicle fire tests as verification. The tests were conducted with AMFE being 30 m apart from the vehicle and 10 m apart from engine room. As a results, it was confirmed that AMFE enables to suppress a fire and prevent its spread in both cases.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.2
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• pp.171-183
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• 2020

The purpose of this study is to analyze in advance the problems and improvements that may occur during the construction of intermediate slabs and the loading of intermediate slabs through the preliminary structural safety evaluation of intermediate slabs for Test bed structures in deep depth tunnels. The Test bed construction can verify and confirm the results of the design and construction technology development of large depth double deck tunnel through the process, and can also be used as a learning site for engineers and the general public to speed up the time of underground space development. There will be an opportunity to do this. In particular, the design load of middle slab built inside the circular deep-depth double-sided tunnel cross-section varies depending on the construction method and the construction equipment load used. Class 3 truck load of KL-510 assumed to be common load to upper and middle slab during loading and installation is loaded on upper and lower slab with different working position for each load combination Analyzed.

• Smart Structures and Systems
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• v.23 no.5
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• pp.507-520
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• 2019

In the structural health monitoring field, damage detection has been commonly carried out based on the structural model and the engineering features related to the model. However, the extracted features are often subjected to various errors, which makes the pattern recognition for damage detection still challenging. In this study, an automated damage identification method is presented for hanger cables in a tied-arch bridge using a convolutional neural network (CNN). Raw measurement data for Fourier amplitude spectra (FAS) of acceleration responses are used without a complex data pre-processing for modal identification. A CNN is a kind of deep neural network that typically consists of convolution, pooling, and fully-connected layers. A numerical simulation study was performed for multiple damage detection in the hangers using ambient wind vibration data on the bridge deck. The results show that the current CNN using FAS data performs better under various damage states than the CNN using time-history data and the traditional neural network using FAS. Robustness of the present CNN has been proven under various observational noise levels and wind speeds.

• Journal of the Korean Society for Railway
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• v.9 no.4 s.35
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• pp.467-472
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• 2006

This paper deals with the applicability of long-gauge deformation fiber optic sensors (FOS) to prestressed concrete structures. A main motivation is the desire to monitor the deflection of the railway bridges without intervenes of the signal intensity fluctuations. A 25 m long, 1.8 m deep PSC girder was fabricated compositely with 22 cm thick reinforced concrete deck. Two pairs of 3 m long-gauge sensors are attached to the prestressed concrete girder with parallel topology. Using the relationship between curvature and vortical deflection and the quadratic regression of curvatures at the discrete point, it is possible to extrapolate the deflection curve of the girder. The estimated deflection based on the developed method is compared with the results using conventional strain gauges and LVDTS. It has been demonstrated that the proposed instrumentation technique is capable of estimating the vertical deflection and neutral axis position of the prestressed concrete girder up to weak nonlinear region.

• Steel and Composite Structures
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• v.16 no.1
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• pp.21-44
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• 2014

The aim of this study is to determine the dynamic characteristics of long reinforced concrete highway bridges with post-tension tendons using analytical and experimental methods. It is known that the deck length and height of bridges are affected the dynamic characteristics considerably. For this purpose, Berta Bridge constructed in deep valley, in Artvin, Turkey, is selected as an application. The Bridge has two piers with height of 109.245 m and 85.193 m, and the total length of deck is 340.0 m. Analytical and experimental studies are carried out on Berta Bridge which was built in accordance with the balanced cantilever method. Finite Element Method (FEM) and Operational Modal Analysis (OMA) which considers ambient vibration data were used in analytical and experimental studies, respectively. Finite element model of the bridge is created by using SAP2000 program to obtain analytical dynamic characteristics such as the natural frequencies and mode shapes. The ambient vibration tests are performed using Operational Modal Analysis under wind and human loads. Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (SSI) methods are used to obtain experimental dynamic characteristics like natural frequencies, mode shapes and damping ratios. At the end of the study, analytical and experimental dynamic characteristic are compared with each other and the finite element model of the bridge was updated considering the material properties and boundary conditions. It is emphasized that Operational Modal Analysis method based on the ambient vibrations can be used safely to determine the dynamic characteristics, to update the finite element models, and to monitor the structural health of long reinforced concrete highway bridges constructed with the balanced cantilever method.

• Journal of Korean Tunnelling and Underground Space Association
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• v.15 no.2
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• pp.135-148
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• 2013

Recently, road tunnels have become longer and the plans for long and deep road tunnel have been underway in urban areas. These long and deep tunnel excavations include NATM and TBM. Shield TBM is applied to around 80% of traffic tunnels in Europe, and approximately 30% of them in other developed countries. However, as much of equipment is imported from foreign countries at high prices and distribution rate of TBM tunnel is considerably low in Korea, NATM excavation method is commonly used. To increase TBM tunnel, it is necessary to do assure economic feasibility with the supply-demand of TBM equipment. For this, the selection of standardized TBM diameter is urgently needed. Therefore, the study aims to estimate the standardized optimum section properties of TBM by examining TBM excavation cross section utilization depending on the volume of traffic, the number of lane and its cross-section type(single or double deck), and ventilation system.