Development of corrosion monitoring system using inverse analysis framework for integrating various type of a priori information
Project/Area Number |
26420455
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Structural engineering/Earthquake engineering/Maintenance management engineering
|
Research Institution | Tokyo Institute of Technology |
Principal Investigator |
Amaya Kenji 東京工業大学, 工学院, 教授 (70251642)
|
Project Period (FY) |
2014-04-01 – 2017-03-31
|
Project Status |
Completed (Fiscal Year 2016)
|
Budget Amount *help |
¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
|
Keywords | 維持管理工学 / 逆問題 / 数値解析 / 腐食モニタリング / 腐食量推定 / 数値シミュレーション / 犠牲陽極 / 電流量推定 |
Outline of Final Research Achievements |
In this research, corrosion monitoring system which identifies corrosion currents on seawater structures from small number of potential measurements using numerical inverse analysis was developed. The new inverse analysis framework was proposed based on the following 4 approaches. 1) Virtual boundary condition is applied when the geometrical information of structures is unknown. 2) Useful ambiguous information based on experience and intuition are taken account with fuzzy reasoning. 3) Bayesian estimation is employed to integrating various type of a priori information. 4) In order to increase the measurement data, currents are impressed actively and potential change is measured. In order to demonstrate the effectiveness of the developed analysis method, numerical simulation and practical experiment has been performed.
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Report
(4 results)
Research Products
(2 results)