• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.5
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• pp.1165-1171
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• 2015

Due to the increasing trend of operation and maintenance cost (O&M cost) of infrastructure, the accurate estimation of O&M cost is crucial part to the government. Recent literatures pointed out that gradual climate changes such as average temperature changes, average precipitation changes, and etc. have significant impact on infrastructure O&M cost. This research is intended to develop a long-term O&M cost prediction model of road facilities by considering the impacts of average temperature changes. For this end, the climate change scenarios of Intergovernmental Panel on Climate Change (IPCC)'s $5^{th}$ report are adopted to structure the impact of average temperature changes by using binomial lattice model. The proposed framework is expected to regional government in supporting decisions for road O&M cost.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.6
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• pp.131-142
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• 2007

The road user cost in indirect costs as well as direct costs such as the inspection/ diagnosis cost and the repair/reinforcement cost should be considered as one of the important items in the life-cycle cost-effective design and maintenance of the bridges. To estimate the road user cost, this paper formulates the road user cost as a sum of the user delay cost and the vehicle operating cost considering the detour effect. A numerical traffic simulation and a regression analysis are performed to develop a regression model due to a time delay. The proposed regression model is applied to the generation of the maintenance strategy based on the life-cycle cost and performance, and its effectiveness and applicability is investigated. The road user cost has a great influence on establishing the maintenance strategy, and the proposed regression model could be successfully utilized to estimate the road user cost of a bridge.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.77-85
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• 2013

In this paper, we present the cost measurement metrics for the operation management and service improvement besides the general maintenance. The cost measurement metrics of the operation management and service improvement are based on the metrics that are classified and summarized precedent studies and complemented by empirical measuring indicators, and we propose the maintenance cost estimation model based on this metrics. The maintenance costs can be calculated detailedly, because the proposed metrics can be used selectively, depending on the scope of the information system maintenance. The effectiveness of the proposed maintenance cost measurement metrics and cost estimation model is verified by comparison between existing studies and our research.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.505-516
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• 2018

In order to establish an efficient bridge maintenance strategy, the future performance of a bridge must be estimated by considering the current performance, which allows more rational way of decision-making in the prediction model with higher accuracy. However, personnel-based existing maintenance may result in enormous maintenance costs since it is difficult for a bridge administrator to estimate the bridge performance exactly at a targeting management level, thereby disrupting a rational decision making for bridge maintenance. Therefore, in this work, we developed a representative performance prediction model for each bridge element considering uncertainty using domestic bridge inspection data, and proposed a bayesian updating method that can apply the developed model to actual maintenance bridge with higher accuracy. Also, the feasibility analysis based on calculation of maintenance cost for monitoring maintenance scenario case is performed to propose advantages of the Bayesian-updating-driven preventive maintenance in terms of the cost efficiency in contrast to the conventional periodic maintenance.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.6
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• pp.1-9
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• 2016

The paper aims at evaluating effects of preventive maintenance on life cycle cost(LCC) reduction of bridges. The preventive maintenance activities capable to delay bridge deteriorations can reduce overall maintenance costs and extend service life of a bridge by regularly providing maintenance activities and avoiding larger maintenance(repairs or rehabilitations) costs. Couple of prediction models were proposed in order to calculate LCC of a typical bridge: a health score model and repair rehabilitation cost model. In addition, the maintenance activities such as wash and painting were also suggested in order to consider effects of preventive maintenance in the analysis based on literature reviews. According to analysis results, new maintenance strategy(reactive maintenance + preventive maintenance) can save \0.5 billion per bridge for future life-cycle costs over 100 year analysis or \184 billion for entire HBMS(Highway Bridge Management System) inventory over 20 years. Small investments for preventive maintenance in improved bridge management can have a very significant return when considering the large bridge inventory.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.717-724
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• 2018

To prepare for the explosive increase in maintenance costs of bridges according to the aging of infrastructure, future maintenance costs of bridges should be predicted. For this purpose, the management status of bridges was investigated and modeled as the upper limit of the performance level and the target management level according to the life cycle. This paper proposes methodologies and procedures for estimating the bridge maintenance costs using two models and existing cost and performance prediction models that consist of unit repair cost model according to the safety score, performance degradation model of bridges, unit reconstruction cost, and average reconstruction time. To verify the applicability, future maintenance costs can be forecasted for specific management agency considering the number of bridges, degree of aging, and current management status. As a result, it is possible to obtain the maintenance cost and safety level of an individual bridge level for each year. In addition, by summing them up to the agency level, the average safety score, ratio of the safety level, inspection costs, repair costs, and reconstruction costs can be obtained. In a further study, the changes in maintenance costs can be analyzed according to the changes in the target management levels using the developed method. The optimal management level can be suggested by reviewing the results.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.1
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• pp.33-40
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• 2016

In this study, using the Cost Prediction Model and Performance Prediction Model have developed a way to estimate future management costs and performance for bridge and tunnel by Network Level. Studies to date have primarily focused on the single facility, it is difficult to apply to the analysis of the Network Level. This study, items used as an index of 'Special Act for the Safety Control of Public Structures' was added to Usability and Functionality to Status. Action period and annual budget for each facility can be estimated through the Basic and Advanced analysis. In addition, we verified the technical feasibility through case analysis.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.4
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• pp.87-96
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• 2017

It is important to estimate the future maintenance budget of all SOC infrastructure at the national strategic level. In this study, Based on a currently available statistics data, we predicted future maintenance investment for all SOC infrastructure in Korea. We have studied the applicable prediction models, and we developed the prediction models that can calculated the future maintenance cost by a real expenditure date. The subjects of facilities are bridges, tunnels, pavements, harbors, dams, airports, water supply, rivers and port. As a result of total estimated cost, eight types of SOC infrastructures are about 23 trillion won for the next 10years, and the most expensive facilities are road pavements and bridges.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.533-542
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• 2016

The periodic maintenance of bridges is necessary once they have been constructed and its cost depends on various factors, such as their condition, environmental conditions and so on. To make a decision support system, it is essential to establish a basic reconstruction cost model. In this study, a regression model is suggested for calculating the reconstruction cost for typical cases and influential factors, depending on the type of bridge and its components, by analyzing the basic bridge specifications based on the data of the Bridge Management System (BMS). The details for each case were estimated in consideration of the cost calculation variables. The details for each case were estimated in consideration of the cost calculation variables. The cost model for the new construction of the superstructure, substructure and foundation and the temporary bridge construction and demolition costs were drawn from the regression analysis of the estimation results of typical cases according to the cost calculation variables. The reconstruction costs for different types of bridge were obtained using the cost model and compared with those in the literature. The cost model developed herein is expected to be utilized effectively in maintenance decision making.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.802-809
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• 2021

To cope with the increasing maintenance costs due to aging, the maintenance cost was evaluated from the perspective of asset management. The maintenance cost can be predicted based on the condition of the bridge, and the life cycle cost is used as an index. In general, the condition of a bridge has a wide distribution characteristic depending on the deterioration, load, and material characteristics. In this paper, to evaluate the effect of the bridge conditions on the life cycle cost, condition prediction models were constructed considering the service life, deterioration rate, and inspection error, which are the main variables of the bridge condition and life cycle cost calculation. In addition, condition prediction models were constructed based on the distribution of the health index to estimate the upper and lower bounds of the life cycle costs that can occur in individual bridges. Life cycle cost analysis showed that the life cycle cost differed significantly according to the condition of the bridge. Accordingly, research will be needed to increase the reliability of predicting the life cycle cost of individual bridges.