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http://dx.doi.org/10.7843/kgs.2010.26.7.161

Reliability Updates of Driven Piles Based on Bayesian Theory Using Proof Pile Load Test Results  

Park, Jae-Hyun (Dept. of Geotech. Research Eng'g Div., KICT)
Kim, Dong-Wook (Dept. of Geotech. Research Eng'g Div., KICT)
Kwak, Ki-Seok (Dept. of Geotech. Research Eng'g Div., KICT)
Chung, Moon-Kyung (Dept. of Geotech. Research Eng'g Div., KICT)
Kim, Jun-Young (Dept. of Civil and Environmental Eng'g, Seoul National Univ.)
Chung, Choong-Ki (Dept. of Civil and Environmental Eng'g, Seoul National Univ.)
Publication Information
Journal of the Korean Geotechnical Society / v.26, no.7, 2010 , pp. 161-170 More about this Journal
Abstract
For the development of load and resistance factor design, reliability analysis is required to calibrate resistance factors in the framework of reliability theory. The distribution of measured-to-predicted pile resistance ratio was obrained based on only the results of load tests conducted to failure for the assessment of uncertainty regarding pile resistance and used in the conventional reliability analysis. In other words, successful pile load test (piles resisted twice their design loads without failure) results were discarded, and therefore, were not reflected in the reliability analysis. In this paper, a new systematic method based on Bayesian theory is used to update reliability indices of driven steel pipe piles by adding more proof pile load test results, even not conducted to failure, to the prior distribution of pile resistance ratio. Fifty seven static pile load tests performed to failure in Korea were compiled for the construction of prior distribution of pile resistance ratio. The empirical method proposed by Meyerhof is used to calculate the predicted pile resistance. Reliability analyses were performed using the updated distribution of pile resistance ratio. The challenge of this study is that the distribution updates of pile resistance ratio are possible using the load test results even not conducted to failure, and that Bayesian updates are most effective when limited data are available for reliability analysis.
Keywords
Bayesian theory; Driven steel pipe pile; FORM; Reliability analysis; Reliability index; Static pile load test;
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