• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.2
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• pp.75-83
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• 2019

In this study, to propose the deterioration curves of urethane, ceramic, polysiloxane and fluorocarbon coating for the steel bridge, an accelerated corrosion tests were carried out. The each coating system wes applied on the top of the specimens, and circular initial defects were introduced with different diameters with 0.5, 1.0, 3.0, 5.0 mm. An accelerated corrosion test condition was used to simulate severe corrosive environment depending on ISO 20340. The deterioration curve of each coating type was evaluated based on deteriorated area from the circular defects. In order to evaluate the coating service life of installed steel bridge using deterioration curve, the acceleration coefficient was calculated at correlation between ISO 20340 and corrosivity categories by ISO 9223 based on field corrosion rate. From test results, the propagation rate of coating deterioration area was different to diameter of circular defects. In case of urethane coating, the coating service lifes of 3% deterioration area was evaluated in 31.8, 15.8, 9.9 and 3.9 years with C2, C3, C4 and C5 category.

• Interaction and multiscale mechanics
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• v.5 no.1
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• pp.41-56
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• 2012

This study is focused on evaluation of the tensile properties of concrete exposed to acid rain environment. Acid rain environment was simulated by the mixture of sulfate and nitric acid in the laboratory. The dumbell-shaped concrete specimens were submerged in pure water and acid solution for accelerated conditioning. Weighing, tensile test, CT, SEM/EDS test and microanalysis were performed on the specimens. Tensile characteristics of the damaged concrete are obtained quantitatively. Evolution characteristics of the voids, micro cracks, chemical compounds, elemental distribution and contents in the concrete are examined. The deterioration mechanisms of concrete exposed to acid rain are well elucidated.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2005.11a
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• pp.280-284
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• 2005

Existing construction materials such as concrete and steel have chronic problems; deterioration and corrosion. Owing to its special features of light weight ‘ high durability, anti-corrosion, composite material used in civil infrastructure can not only solve fundamental problems of deterioration and corrosion, but also reduce both construction and maintenance cost significantly. After the fabrication of deck panel with snap-fit connection by pultrusion through composite design according to stacking sequence of composite laminates and structural analysis, performance of decks will be verified and evaluated by structural tests.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.4
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• pp.185-193
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• 2004

Reasonable prediction of bridge deterioration is the most important factor in the determination of repair time or optimized maintenance policy for bridges. To accomplish these purposes, the proposed method is composed of quantitative condition assessment, Markov chains and Bayesian estimates. Example predictions of concrete slab bridges in Korea were illustrated with higher reasonability than those of existing methods such as expert opinion and visual inspection only.

• Journal of the Korean Society for Railway
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• v.13 no.1
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• pp.71-77
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• 2010

It is increasing annually that the cost for bridge Maintenance Repair & Rehabilitation (MR&R) in developed countries. Based on Intelligent Technology, Bridge Management System (BMS) is developed for optimization of Life Cycle Cost (LCC) and reliability to predict long-term bridge deteriorations. However, such data are very limited amongst all the known bridge agencies, making it difficult to reliably predict future structural performances. To alleviate this problem, an Artificial Neural Network (ANN) based Backward Prediction Model (BPM) for generating missing historical condition ratings has been developed. Its reliability has been verified using existing condition ratings from the Maryland Department of Transportation, USA. The function of the BPM is to establish the correlations between the known condition ratings and such non-bridge factors as climate and traffic volumes, which can then be used to obtain the bridge condition ratings of the missing years. Since the non-bridge factors used in the BPM can influence the variation of the bridge condition ratings, well-selected non-bridge factors are critical for the BPM to function effectively based on the minimized discrepancy rate between the BPM prediction result and existing data (deck; 6.68%, superstructure; 6.61%, substructure; 7.52%). This research is on the generation of usable historical data using Artificial Intelligence techniques to reliably predict future bridge deterioration. The outcomes (Long-term Bridge deterioration Prediction) will help bridge authorities to effectively plan maintenance strategies for obtaining the maximum benefit with limited funds.

• Structural Engineering and Mechanics
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• v.52 no.1
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• pp.35-49
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• 2014

This paper studies the behaviour of deteriorated reinforced concrete (RC) beams attacked by various forms of simulated acid rain. An artificial rainfall simulator was firstly designed and evaluated. Eleven RC beams ($120mm{\times}200mm{\times}1800mm$) were then constructed in the laboratory. Among them, one was acting as a reference beam and the others were subjected to three accelerated corrosion methods, including immersion, wetting-drying, and artificial rainfall methods, to simulate the attack of real acid rain. Acid solutions with pH levels of 1.5 and 2.5 were considered. Next, ultrasonic, scanning electron microscopy (SEM), dynamic, and three-point bending tests were performed to investigate the mechanical properties of concrete and flexural behaviour of the RC beams. It can be concluded that the designed artificial simulator can be effectively used to simulate the real acid rainfall. Both the immersion and wetting-drying methods magnify the effects of the real acid rainfall on the RC beams.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1158-1164
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• 2007

Recently, the demand on the practical application of life-cycle cost effectiveness for design and rehabilitation of civil infrastructure is rapidly growing unprecedentedly in civil engineering practice. Accordingly, it is expected that the life-cycle cost in the 21st century will become a new paradigm for all engineering decision problems in practice. However, in spite of impressive progress in the researches on the LCC, so far, most researches in Koreahave only focused on roadway bridges, which are not applicable to railway bridges. Thus, this paper presents the formulation models and methods for uncertainty-based LCCA for railroad bridges consideringboth objective statistical data available in the agency database of railroad bridges management and subjective data obtained form interviews with experts of the railway agency, which are used to anew uncertainty-based expected maintenance/repair costs including lifetime indirect costs. For reliable assessment of the life-cycle maintenance/repair costs, statistical analysis considering maintenance history data and survey data including the subjective judgments of railway experts on maintenance/management of railroad bridges, are performed to categorize critical maintenance items and associated expected costs and uncertainty-based deterioration models are developed. Finally, the formulation for simulation-based LCC analysis of railway bridges with uncertainty-based deterioration models are applied to the design-decision problem, which is to select an optimal bridge type having minimum Life-Cycle cost among various railway bridges types such as steel plate girder bridge, and prestressed concrete girder bridge in the basic design phase.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.1
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• pp.267-277
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• 2003

The purpose of this study makes a retrofit and rehabilitation practice trough the analysis and the improvement for the underlying problem of current retrofit and rehabilitation methods. Therefore, the deterioration process, the damage cause, the condition classification, the fatigue mechanism and the applied quantity of strengthening methods for slab bridge decks were analysed. Artificial neural networks are efficient computing techniqures that are widely used to solve complex problems in many fields. In this study, a back-propagation neural network model for estimating a management on existing slab bridge decks from damage cause, damage type, and integrity assessment at the initial stsge is need. The training and testing of the network were based on a database of 36. Four different network models werw used to study the ability of the neural network to predict the desirable output of increasing degree of accuracy. The neural networks is trained by modifying the weights of the neurons in response to the errors between the actual output values and the target output value. Training was done iteratively until the average sum squared errors over all the training patterms were minimized. This generally occurred after about 5,000 cycles of training.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.3
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• pp.235-242
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• 2004

Bridge Management System (BMS) requires a more objective condition assessment over the lifespan of a given bridge. Thus, a quantitative assessment model of resistance capacity was developed here to meet the requirement for deteriorated concrete bridges. The model focuses on damage mechanisms of concrete bridges deteriorated by traffic loads and environment factors such as chloride and carbonation attacks. Also, it was applied to a typical concrete slab bridge which was severely damaged due to both load and environmental conditions. It was shown that the proposed quantitative model simulates well the deterioration level considering the two damage criteria.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.476-479
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• 2010

In recent years, the deterioration of infrastructures is especially considered. In prestress concrete bridges, one of the important mechanisms of deterioration is the corrosion of the post-tensioned tendon due to environmental agents. In this study, the reliability analysis is performed for a prestress concrete box girder bridge under the pitting corrosion attack with considering the inspection and failure cost. The variation of life-time performance depending on inspection methods have to be quantified. The inspection methods with different accuracy of corrosion detection are presented and applied for model of reliability analysis. The computer program for analysis reliability index of the structure as well as updating process is obtained. An existing bridge is applied for illustrating the influence of inspection cost on the behaviors of structure. Subsequently, the benefit of inspection has shown to predict the time to failure of structure.