| Project/Area Number |
13650636
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Building structures/materials
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| Research Institution | University of the Ryukyus |
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Principal Investigator |
YAMADA Yoshitomo University of the Ryukyus, Faculty of Eng., Associate Professor, 工学部, 助教授 (80220416)
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| Project Period (FY) |
2001 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥2,500,000 (Direct Cost: ¥2,500,000)
Fiscal Year 2002: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 2001: ¥1,900,000 (Direct Cost: ¥1,900,000)
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| Keywords | Chloride Ions / Air Born chlorides / Penetrating Process of Chloride Ions / Durability / Finite Element Method / Neural-Network / 劣化予測 / 鉄筋腐食状態 / 腐食限界塩化物イオン量 / 飛来塩分量 / HSMAC法 / 鉄筋コンクリート構造物 |
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| Research Abstract |
In order to perform rational durability design and proper diagnosis of reinforced concrete structures under chloride contaminated environment, it is necessary to understand the characteristics of air born chlorides and clarify the penetrating process of chloride ions into concrete. Also, it becomes important to evaluate the amount of chloride ions around steel reinforcement quantitatively relating with time. Therefore, this research presents experimental and analytical studies on the characteristics of air born chlorides and the penetrating process of chloride ions into concrete.
The outline of the discussion about research result is as following;
The background of this research and wide survey of related researchers are presented in order to show the purpose of this research.
1. The advection and diffusion equation of air born chlorides proposed here takes account of the surface roughness and the shielding effect due to barriers. The analytical results of the proposed equation are obtained by using the finite element method (F.E.M.), and the results are compared to the field data. It is confirmed that they are closely related each other qualitatively and quantitatively.
2. This paper proposes an evaluating method of chloride ion content in concrete by the Neural-Network. Output data from the Neural-Network are confirmed to present proper values which are closely related to the measured data.
Recently, premature deterioration of existing reinforced concrete structures has become a public concern and future reinforced concrete structures are required to have durability. Therefore, the results from this research are believed to give valuable information for durability design and diagnosis of reinforced concrete structures under chloride contaminated environment.
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