• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7893-7901
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• 2015

It is important to the periodic collection and analysis of the maintenance and management information of bridges for a more safe and efficient management of the bridges. To enhance the reliability and ease of acquisition of the bridge inspection information that is the basis for a strategy for safe and economic management using the bridge management system (BMS), this study develops a smart phone application for bridge inspection and ensures the actual applicability of the application. The developed application that is linked with the BMS for life-cycle management of bridges is possible to real-time query, modify and transmit of the maintenance-related information, and the application is able to greatly relieve the time and cost for the bridge inspection through the automatic creation of site inspection reports. The proposed method using the application is directly or indirectly expected to be very high effects of value improvement, such as ease of use, improved accuracy, sustainability of information, and future utilization, compared to conventional inspection method.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.386-397
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• 2007

One major development in bridge life cycle cost analysis (LCCA) in recent years is to develop deterioration model for bridge components so that the times of repair/replacement throughout a component's life span can be properly determined. Taiwan also developed her own bridge LCCA model in 2003, integrating with the bridge inspection database in the local bridge management system (T-BMS). Under the framework of the local LCCA model, this study employs the reliability method in developing a deterioration model of bridge components. A component deteriorates through time in its reliability, which represents the probability of a component's condition index exceeds a user specified threshold. Model assumptions and rationale are described in the paper. The steps for applying the developed model are explained in detail. Results and findings are reported.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.405-412
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• 2023

With the development of drone and ICT convergence technology, the use of underwater drones such as leisure underwater drones such as underwater exploration for fishing and industrial drones such as bridge piers is increasing. Existing motor controllers are suitable for aerial drones and these can increase the completeness of underwater drones and their reliability in motor control by developing BLDC motor controllers dedicated to underwater drones. By developing a battery management system (BMS) exclusively for underwater drones, battery stability was ensured by checking the state of charge, checking the state of discharge, adjusting cell balancing, and implementing high/voltage protection functions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5B
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• pp.824-832
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• 2010

In construction structure management, the effects of investigation by the professional manager is dependent on the cost, the inspection periods and methods. Therefore, effective and automated maintenance system for the target structure is required. Although some bridge monitoring systems are operating using wire based networks, the performance is not good enough to show sufficient ability as integrated bridge management system. In this paper, we design and implement an integrated bridge management system based on sensor networks. Two expert modules for bridge management and the integrated system management are provided. Moreover, web-based monitoring system is also designed for users at anywhere. The results show that the system is effective and readily available.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.765-778
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• 2008

Performance Profiles are essential to predict the performance variation over time for the bridge management system (BMS) based on risk management. In general, condition profiles based on experts opinion and/or visual inspection records have been used widely because obtaining profiles based on real performance is not easy. However, those condition profiles usually don't give a good consistency to the safety of bridges, causing practical problems for the effective bridge management. The accuracy of performance evaluation is directly related to the accuracy of BMS. The reliability of the evaluation is important to produce the optimal solution for distributing maintenance budget reasonably. However, conventional methods of bridge assessment are not suitable for a more sophisticated decision making procedure. In this study, a method to compute quantitative performance profiles has been proposed to overcome the limitations of those conventional models. In Bridge Management Systems, the main role of performance profiles is to compute and predict the performance of bridges subject to lifetime activities with uncertainty. Therefore, the computation time for obtaining an optimal maintenance scenario is closely related to the efficiency of the performance profile. In this study, the Response Surface Method (RSM) based on independent and important design variables is developed for the rapid computation. Steel box bridges have been investigated because the number of independent design variables can be reduced significantly due to the high dependency between design variables.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.3
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• pp.251-262
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• 2003

LCP(Life Cycle Profiles) of bridge structures are indispensable for the LCC(Life Cycle Cost) evaluations of bridge system. The bridge under considerations may be newly-designed one or one in service. Thus, a systematic study of LCP is essential for both reliable LCC evaluation and strategic bridge management. LCP is mainly influenced by the structural environment in nature. However, in Korea, LCC evaluation has been performed with the LCP of foreign research results or only with the pieces of professional engineers' opinion. Therefore, to alleviate the drawbacks of foreign LCP and to enhance the reliability of current LCP, LCP should be established using the available data in bridge management system(BMS). In this study, LCP along with a subset of the BMS data was investigated and several mathematical expressions were proposed and evaluated. The condition ratings of a bridge were trasformed into the numerical indices through fuzzy logics with real field data. From the numerical results, it is concluded that the mathematical LCP model of $y=\sqrt{y^2_0-at}$ is shown to be the fittest one (R=0.815) to express the condition rating varied with the age. This has been drawn from the case study of slab bridges under the similar conditions.

• 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.

• 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 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.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.105-115
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• 2017

PURPOSES : The occurrence of unexpected disasters, including fire events, increases as the road network becomes complicated and traffic volume increases. When a fire event occurs on and under bridges, the damage extensively influences direct damage to structures, vehicles, and human life and secondary socioeconomic issues owing to traffic blockage. This study investigated potential fire-hazard risks on bridges of the Korean national route road. METHODS : The investigation was conducted using field investigation and analysis with satellite pictures and road views from commercial websites and the Bridge Management System (BMS). From the filed investigation, various potential fire resources were identified. The satellite pictures and road views were helpful in measuring and recognizing conditions underneath bridges, stowage areas, etc. RESULTS : There are various potential fire resources underneath bridges such as piled agricultural products, parked petroleum tanks, construction equipment, and attached high-voltage cables. A total of 94.6% of bridges have underneath clearances of less than 15 m. A bridge underneath volume that can stow a potential fire hazard resource was $7,332m^3$ on average, and most bridges have about $4,000m^3$ of space. Based on the BMS data, the amounts of PSC and steel girders were 29% and 25%, respectively. CONCLUSIONS : It was found that the amount of stowed potential fire hazard resources was proportional to the underneath space of bridges. Most bridges have less than 15 m of vertical clearance that can be considered as a critical value for a bridge fire. The fire risk investigation results should be helpful for developing bridge fire-protection tools.