• Smart Structures and Systems
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• v.15 no.3
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• pp.543-553
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• 2015

The condition of the vehicular bridge network in New York City, as represented by ratings obtained during biennial inspections is reviewed over a period of three decades. Concurrently, the bridges comprising the network are considered as networks of structural elements whose condition defines the overall bridge condition according to New York State assumptions. A knowledge-based matrix of assessments is used in order to determine each element's vulnerability and impact within the network of an individual structure and the network of City bridges. In both networks expansion deck joints emerge as the weak link. Typical joint failures are illustrated. Bridge management options for maintenance, preservation, rehabilitation and replacement are examined in the context of joint performance.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.557-564
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• 2006

Life-cycle performance and maintaining cost predictions are required for the effective management for bridges. In Korea, the importance of management of bridges has been recognized over the past two decades, resulting in the development of databases and various bridge management support tools by both government and private sectors. However, none of these tools has truly included the expected features of the bridge management system (EMS) for the next generation such as the quantification of the effects of maintenance interventions on bridge condition and safety. In this paper, a novel quantification process to simulate the life-cycle performance of steel box bridges has been developed. The process is based on the Response Surface method. Various performance-related variables aloe investigated to identify a set of significant design variables to construct the response surfaces.

• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.3-11
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• 2012

The most of domestic bridge has an used life under 30 years, Future maintenance budgets can be expected to increase. However, because of bridge maintenance budgets are limited, demand for asset management being performed to achieve required performance within available budget is increasing. To perform effective asset management of bridges should be made the best use of information to occur in all phase of construction project. Therefore, the development of system and DB is required to support asset management by effective information management. The objective of this study is the development of the BIM-based bridge asset management model. Through previous research survey, BIM capabilities and asset management components were established and mutual linkages were examined. Bridge asset management model was composed of alternate assessment model. In addition, BIM-based asset management model was performed case studies to verify feasibility and applicability. The proposed model can be applied to a current bridge maintenance procedures and supported to perform effective bridge maintenance tasks within a limited budget.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.493-496
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• 2008

In case of collapsed or damaged Servicing infrastructure, such as a bridge, tunnel, dam, a severe loss may have to be incurred. Therefore, infrastructure should not be designed and constructed properly but also maintained impeccably. This paper tried to build an intelligent bridge maintenance system that warn the people on bridge and control traffic in the danger. For the purpose, diverse wireless sensor fields are composed and structure's database is established. Also the paper develops a bridge maintenance program. Developed programme is regarded as a good tool to provide the utmost bridge management scenario, which is exactly correspondent with the demand and restraint by improving the present bridge management strategy.

• 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.

• Steel and Composite Structures
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• v.12 no.5
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• pp.379-393
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• 2012

Many steel bridge infrastructures in the world are getting older, and a large number of these structures are in need of maintenance, rehabilitation or replacement. Most of them are subjected to corrosion due to exposure to aggressive environmental conditions and inadequate maintenance, causing reduction of their carrying capacities. In order to have an adequate bridge management, it is of paramount importance to develop an efficient, accurate and rapid condition assessment method which can be used to make reliable decisions affecting the cost and safety. Therefore, a simple and accurate method of calculating remaining yield and tensile strength by using a concept of representative effective thickness with correlation of initial thickness and maximum corroded depth is proposed in this study, based on the results of many tensile coupon tests of corroded plates obtained from a steel plate girder with severe corrosion, used for about 100 years. Furthermore, a strength reduction diagram which will be very useful for bridge inspection engineers to make rational decisions about the maintenance management of aged steel bridge infrastructures is presented.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.389-394
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• 2019

In case of damaged timber sleepers, maintenance is carried out according to the track inspection standard. However, it is difficult to detect the extent of damage on the bridge, and maintenance is depended on inspector's judgment. In this study, we propose to improve the evaluation criterion of timber sleepers for the ballast-less tracks on serviced urban railway bridge. The timber sleepers on railway bridge was classified according to degree of damage, and damage scores were calculated for each damage grade. Also we have improved the maintenance system of the timber sleepers through the history management system of the individual timber sleepers on railway bridge. As a results, it was judged that systematic management of timber sleepers could be possible during maintenance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.128-134
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• 2016

Estimating the repair and reinforcement (R&R) costs for each bridge member is essential for managing the life cycle of a bridge using a bridge management system (BMS). Representative members of a bridge were defined in this study, and detailed and representative R&R methods for each one were drawn in order to develop a systematic maintenance cost model that is applicable to the BMS. The unit cost for each detailed R&R method was established using the standard of estimate and historical cost data, and a systematic procedure is presented using an integration program to enable easy renewal of the R&R unit cost. Also, the average unit cost of the representative R&R methods was calculated in the form of a weighted average by considering the unit cost and application frequency of each detained R&R method. The appropriateness of the drawn average unit cost was reviewed by comparing and verifying it with the previous historical unit cost. The suggested average R&R unit cost can be used to review the validity of the required budget or the appropriateness of the R&R performance cost in the stage to establish the bridge maintenance plan. The results of this study are expected to improve the reliability of maintenance cost information and the rationality of decision making.

• Smart Structures and Systems
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• v.30 no.6
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• pp.571-582
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• 2022

Optimal life-cycle management is a challenging issue for deteriorating regional bridges. Due to the complexity of regional bridge structural conditions and a large number of inspection and maintenance actions, decision-makers generally choose traditional passive management strategies. They are less efficiency and cost-effectiveness. This paper suggests a deep reinforcement learning framework employing double-deep Q-networks (DDQNs) to improve the life-cycle management of deteriorating regional bridges to tackle these problems. It could produce optimal maintenance plans considering restrictions to maximize maintenance cost-effectiveness to the greatest extent possible. DDQNs method could handle the problem of the overestimation of Q-values in the Nature DQNs. This study also identifies regional bridge deterioration characteristics and the consequence of scheduled maintenance from years of inspection data. To validate the proposed method, a case study containing hundreds of bridges is used to develop optimal life-cycle management strategies. The optimization solutions recommend fewer replacement actions and prefer preventative repair actions when bridges are damaged or are expected to be damaged. By employing the optimal life-cycle regional maintenance strategies, the conditions of bridges can be controlled to a good level. Compared to the nature DQNs, DDQNs offer an optimized scheme containing fewer low-condition bridges and a more costeffective life-cycle management plan.

• Korean Journal of Construction Engineering and Management
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• v.12 no.2
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• pp.64-71
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• 2011

Construction projects are becoming larger in size and higher in complexity. Operation and maintenance, therefore, is an important part in providing the serviceability of the built facility from the perspective of life-cycle. This paper presents a 3D graphic model-integrated data extraction for bridge maintenance. The 3D graphic model environment assigns attributes to the member blocks in CAD, and link the attributes to the data stored in a database. Then, the user can click the member block to extract the data associated with the attributes. A prototype has been developed to test the applicability of the 3D graphic model environment using CAD and web. Application of the system in an actual bridge construction showed that the 3D graphic model environment can help the user find necessary data at a shorter time, thereby increasing the effectiveness of operation and maintenance in bridge structures.