• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.1
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• pp.131-140
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• 2001

In general, the deterioration induced by the freezing and thawing cyclic in concrete structures often leads to the reduction in concrete durability by the cracking or surface spalling. If it can prediction of concrete deterioration subjected to cyclic freezing and thawing, we can rationally do the design of mix proportion in view of concrete durability and the maintenance management of concrete structures. Therefore in this study a prediction method of deterioration for concrete structures subjected to the irregular freezing and thawing is proposed from the results of accelerated laboratory freezing and thawing test using the constant temperature condition and the in-situ weathering data. Furthermore, to accurately predict the concrete deterioration, a method of modification for the effect of hydration increasing during rapid freezing and thawing test is investigated.

• Journal of Korea Water Resources Association
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• v.36 no.1
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• pp.61-74
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• 2003

This study(II) apply to the A city by using the optimal rehabilitation model based on the deterioration prediction of the water distribution system proposed the study(I). The deterioration prediction model divides factors into 14 factors with digging and experiment and 9 factor without digging and experiment and calculate the deterioration degree. The application results of the deterioration prediction model show that a difference of the deterioration degree according to factor numbers is within 1~2%. Also, the model can predict the deterioration degree of each pipe without digging and experiment. The optimal rehabilitation model is divided into the optimal residual durability of each deterioration factor and budget constraint or not. The application result is as follow: the rehabilitation time and cost increase according to the increasing of the optimal residual durability. When compared the model with budget constraint and model without budget constraint, the former model increase the cost of total contents. In case of budget constraint, the increasing tendency is concluded that the pipe rehabilitation is executed in same budget every year in condition that every rehabilitation cost do not exceed the every year budget within the optimal residual durability.

• Journal of Korean Society of Water and Wastewater
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• v.30 no.2
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• pp.155-165
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• 2016

Pipe Deterioration Prediction (PDP) and Pipe Failure Risk Prediction (PFRP) models were developed in an attempt to predict the deterioration and failure risk in water mains using fuzzy technique and the markov process. These two models were used to determine the priority in repair and replacement, by predicting the deterioration degree, deterioration rate, failure possibility and remaining life in a study sample comprising 32 water mains. From an analysis approach based on conservative risk with a medium policy risk, the remaining life for 30 of the 32 water mains was less than 5 years for 2 mains (7%), 5-10 years for 8 (27%), 10-15 years for 7 (23%), 15-20 years for 5 (17%), 20-25 years for 5 (17%), and 25 years or more for 2 (7%).

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.261-267
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• 2010

Present maintenance of a high speed railway is after the fack maintenance that executes a task when measured value goes over threshold value except some planned maintenance. It is difficult from efficient management of maintenance human resource and equipment commitment because it is difficult to predict quantity of maintenance targets. Corrective maintenance is pushed back on the repair priority of other target to need repair and it is exceeded repair cost potentially. For safety and dependable track management because track deterioration prediction is linked directly with track's life and safety of train service, it is very important that track management be based on preventive maintenance. In this study, we propose statistics model of track quality to use track inspection data and forecast model for track deterioration prediction.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.700-706
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• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.

• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.685-691
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• 2011

Developing accurate prediction models for deterioration behavior represents a challenging but essential task in comprehensive Infrastructure Management Systems. The challenge may be a result of the lack of historical data, impact of unforeseen parameters, and/or the past repair/maintenance practices. These realities contribute heavily to the noticeable variability in deterioration behavior even among similar components. This paper introduces a novel approach to predict the deterioration of any infrastructure component. The approach is general as it fits any component, however the prediction is custom for a specific item to consider the inherent impacts of expected and unexpected parameters that affect its unique deterioration behavior.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.10a
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• pp.795-798
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• 1999

Deterioration induced by the freezing and thawing in concrete often leads to the reduction in concrete durability by the cracking or surface spalling. In this paper, the deterioration prediction model for concrete structures subjected to the irregular freeze-thaw was proposed from the results of accelerated laboratory test using the constant temperature condition and acceleration factor from the in-situ weather data.

• Journal of the Korean Society of Safety
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• v.23 no.4
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• pp.59-66
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• 2008

Recently, the deterioration of reinforced concrete structures, primarily due to corrosion of steel reinforcement, has become a major concern. Chloride-induced deterioration is the most important deterioration phenomenon in reinforced concrete structures in harsh environments. For the realistic prediction of chloride penetration into concrete, a mathematical model was developed in which the effects of diffusion, chloride binding and convection due to water movement can be taken into account. The aim of this research was to reach a better understanding on the physical mechanisms underlying the deterioration process of reinforced concrete associated with chloride-induced corrosion and to propose a reliable method for estimating these effects. Chloride concentrations coming from de-icing salts are significantly influenced by the exposure conditions such as salt usage, ambient temperature and repeated wet-dry cycles.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3A
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• pp.341-347
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• 2008

Among coating systems used for steel bridge coatings on highway such as red lead-pigmented alkyd, chlorinated rubber, waterborne inorganic zinc, inorganic zinc/epoxy/urethane and inorganic zinc/epoxy/fluororesin, evaluation of deterioration degree and prediction of lifetime through regression analysis were carried out for coating systems widely used and grossly degraded. For evaluation of deterioration degree, 75 bridges on highway were selected, and evaluations were carried out according to point offering method regulated by Guideline of maintenance coating for steel bridges used in Korea Expressway Corporation. Lifetime prediction results showed 13.0~13.3 years for the whole nation, 11.8 years for urban and industrial region in the metropolitan area, 13.2 years for rural region except the metropolitan area, 13.5~13.7 years for chlorinated rubber coating systems, and 12.86 years for red lead-pigmented alkyd systems. For prediction of the rest life of coating, we tried to execute parallel translations of standard deterioration curve to current life and deterioration degree for both x and y axes, and it was thought that parallel translation for x axis corresponded to deterioration aspects in actual environment. Maximum and minimum equations were derived from standard deterioration equation by adding and subtracting error values deduced in regression analysis to/from each coefficient in order to establish maintenance coating criteria for overall steel bridges on highway. Whole domain was divided into 8 parts in order to predict the rest life of coating and optimum time of maintenance coating, and maintenance coating criteria for each 8 domains were presented.

• Journal of the Korea Concrete Institute
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• v.15 no.4
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• pp.574-584
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• 2003

The most common deterioration cause of concrete structures in urban environment is carbonation. Recently, the $CO_2$ concentration and temperature at atmosphere is sharply increased with time due to global warming phenomena. In this study, the climate scenario IS92a, which was suggested by the IPCC, is used to consider temperature and atmospheric $CO_2$ concentration change in the model of service life prediction. The modified mathematical solution, which was based on the Fick's 1st law of diffusion, was used to reflect concrete materials properties such as the degree of hydration of concrete with elapsed time, and important parameters, which associated with deterioration rate. The techniques of service life prediction are developed introducing the method of reliability and stochastic concept to consider microclimatic condition in Seoul, South Korea. From the result of service life prediction, concrete containing high W/C ratio is shown fast carbonation rate due to $CO_2$ concentration increase. It is concluded that the deterioration of concrete structures due to carbonation is insignificant problem on the conditions that below W/C 55%, well curing concrete.