Updating Life-Cycle Performance Model of Bridge based on Inspection Data
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Bibliographic Details
| Author(s): |
Jin Hyuk Lee
(School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, KOREA)
Kyung Hwa Cha (School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, KOREA) Sang Mi Ahn (School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, KOREA) Jung Sik Kong (School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, KOREA) |
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| Medium: | conference paper | ||||
| Language(s): | English | ||||
| Conference: | IABSE Symposium: Engineering the Future, Vancouver, Canada, 21-23 September 2017 | ||||
| Published in: | IABSE Symposium Vancouver 2017 | ||||
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| Page(s): | 300-303 | ||||
| Total no. of pages: | 4 | ||||
| Year: | 2017 | ||||
| DOI: | 10.2749/vancouver.2017.0300 | ||||
| Abstract: |
For the bridge maintenance strategy and planning, prediction of future performance based on the current performance must be required and it is possible more rational decision-making through the higher accuracy of the prediction model. While performing a detailed inspection of the entire bridge can reduce a significant part of the uncertainty, it is impossible to reduce the uncertainty of inspection result and it is always evaluated by probability. In this study, to solve this problem, a Bayesian update method is applied to the optimal maintenance strategy in Bridge Management System (BMS) considering the uncertainty of inspection data. Also, examples of application are presented, showing the effects of inspection and updating on the bridge maintenance strategies. In this study, application possibility and availability of domestic bridge management system are evaluated by referring to the proposed method in the existing trends. |
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| Keywords: |
bridge uncertainty maintenance inspection Updating decision-making bayesian
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