2010 Fiscal Year Final Research Report
System of Functional Diagnosis for Stock Management of Soil Structures Based on Integrated Measurement/Data Assimilation
| Project/Area Number |
20380136
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Irrigation, drainage and rural engineering/Rural planning
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| Research Institution | Okayama University |
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Principal Investigator |
MURAKAMI Akira Okayama University, 農学研究科, 教授 (80157742)
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| Co-Investigator(Kenkyū-buntansha) |
NISHIMURA Shinichi 岡山大学, 大学院・環境学研究科, 准教授 (30198501)
NISHIYAMA Taturou 愛媛大学, 農学部, 准教授 (30294440)
SHIBATA Toshifumi 松江工業高等専門学校, 准教授 (30342546)
FUJISAWA Kazunori 岡山大学, 大学院・環境学研究科, 講師 (30510218)
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| Co-Investigator(Renkei-kenkyūsha) |
SUZUKI Makoto 清水建設, 技術研究所, 副所長 (90416818)
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| Project Period (FY) |
2008 – 2010
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| Keywords | 土質力学 / 応用力学 |
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| Research Abstract |
This research aimed to establish the system of functional diagnosis for stock management of soil structures using integrated measurements, data assimilation, risk evaluation, and estimation of LCC. The spatial distribution of the strength parameters of decrepit earth-fill dams, and the identification methods of distribution are discussed. Generally, the strength of the earth-fill is predicted from the SPT N-values. While, in this research, the Swedish Weight Sounding Tests (SWS Tests) are conducted to obtain the spatial distribution of the N-values as the simpler method, and the statistical model of the N-values is determined based on the sounding tests. For this task, the Minimizing Akaike's Information Criteria (MAIC) method is employed, and the semi-variogram method is also used to identify the spatial correlation characteristics. The spatial distribution of the N-value is identified from the sounding tests with high resolution, since the point estimations are obtained with short in
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tervals. To interpolate the point estimate values, the indicator simulation method, which is one the geostatistical methods, is employed. In the method, the hard data (primary data) and the soft data (complementary data) can be used simultaneously. Results from the SWS and the Surface Wave Method (SWM), which is one of the geophysical exploration methods, are dealt with as hard and soft data, respectively. With synthesizing two results, the accurate spatial distribution of the N-values can be identified. A computational method, incorporating the finite element model into data assimilation using the particle filter, is presented for identifying deteriorated area within soil structures based on measured data on the settlement and the pore pressure. The effect of improving of the embankment is evaluated in relation to the safety of the embankment against the earthquake and the heavy rain within the framework of the reliability-based design. Risk and the LCC of the soil structures are evaluated from the overall considerations listed above. Less
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