| Project/Area Number |
16K18170
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Civil engineering project/Traffic engineering
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| Research Institution | Ehime University |
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Principal Investigator |
Chun Pang-jo 愛媛大学, 理工学研究科(工学系), 准教授 (60605955)
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| Co-Investigator(Renkei-kenkyūsha) |
Yoshii Toshio 愛媛大学, 理工学研究科(工学系), 教授 (90262120)
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| Research Collaborator |
Kusumoto Masahiro
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| Project Period (FY) |
2016-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2017: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2016: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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| Keywords | リスク評価 / 地域都市計画 / 橋梁工学 / アセットマネジメント / 劣化予測 |
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| Outline of Final Research Achievements |
This research aims to improve the degradation prediction method required for bridge asset management. First, we investigated which parameters affect bridge degradation. As a result, it is found that the bridge deterioration is affected by the difference in the management organization. It is said that the distance from the coastal line affects very much, however, it is only a certain degree of influence according to the analysis of inspection data. Rather, it was suggested that initial defects may have a large effect on degradation.
To evaluate the tail risk of the bridge deterioraton, it is required to derive the detailed tail of the predicion distribution. We realize it by using hierarchical Bayesian model. As a result, it became possible to evaluate the tail risk as mentioned in the research plan, as well as to present the optimal inspection interval for each individual bridge.
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