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확률론적 방법에 의한 인천송도지반 압밀침하량의 공간적 분포 평가

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dc.contributor.author김동휘-
dc.contributor.author최영민-
dc.contributor.author이우진-
dc.date.accessioned2021-09-08T08:59:01Z-
dc.date.available2021-09-08T08:59:01Z-
dc.date.issued2010-
dc.identifier.issn1229-2427-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/118233-
dc.description.abstractBecause the thickness and depth of consolidation layer vary at every location, the consolidation settlement and time have to be evaluated spatially. Also, for a rational evaluation of the uncertainty of the spatial distribution of consolidation settlement and time, it is necessary to adopt a probabilistic method. In this study, mean and standard deviation of consolidation settlement and time of whole analysis region are evaluated by using the spatial distribution of consolidation layer which is estimated from ordinary kriging and statistics of soil properties. Using these results and probabilistic method, the area that needs adopting the prefabricated vertical drain as well as raising the ground level for balancing the final design ground level is determined. It is observed that such areas are influenced by the variability of soil properties. The design procedure and method presented in this paper can be used in the decision making process for a geotechnical engineering design.-
dc.format.extent10-
dc.language한국어-
dc.language.isoKOR-
dc.publisher한국지반공학회-
dc.title확률론적 방법에 의한 인천송도지반 압밀침하량의 공간적 분포 평가-
dc.title.alternativeEvaluation of Spatial Distribution of Consolidation Settlement of Songdo Marine Clay by Probabilistic Method-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.bibliographicCitation한국지반공학회논문집, v.26, no.9, pp 15 - 24-
dc.citation.title한국지반공학회논문집-
dc.citation.volume26-
dc.citation.number9-
dc.citation.startPage15-
dc.citation.endPage24-
dc.identifier.kciidART001486508-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorConsolidation settlement-
dc.subject.keywordAuthorConsolidation rate-
dc.subject.keywordAuthorKriging-
dc.subject.keywordAuthorProbabilistic method-
dc.subject.keywordAuthorVariogram-
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