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dc.contributor.authorStephen K. Suryasentana
dc.contributor.authorBrendan F. O’Boyle
dc.contributor.authorJohn Davidson
dc.contributor.authorSarunas Bartkus
dc.contributor.authorFelix Schroeder
dc.contributor.authorZefeng Zhou
dc.date.accessioned2025-08-17T22:46:57Z
dc.date.available2025-08-17T22:46:57Z
dc.date.copyright7/1/2025 12:00:00 AM
dc.date.issued2025
dc.identifier.otherJGGEFK.GTENG-13304.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4307439
dc.description.abstractThis paper presents a detailed back-analysis of large-scale field data from suction caisson installations in complex, layered soil conditions, enhancing the understanding of caisson installation interaction through a refined assessment of the parameters for cone penetration test (CPT)-based installation calculation methods. Leveraging CPT and suction caisson installation data from a large database, this paper proposes a more nuanced CPT-based design approach tailored for such complex soil conditions. The findings highlight notable parameter differences between dilative and contractive soils, suggesting the necessity of treating these two groups distinctively. Through a comparative analysis with existing CPT-based methods, this research highlights areas where current practices align well with field realities and identifies areas where crucial adjustments are needed to enhance design accuracy. The paper also proposes a quantile-based approach for high estimate installation calculations, which demonstrates an effective balance between safety and excessive conservatism.
dc.publisherAmerican Society of Civil Engineers
dc.titleEnhancing CPT-Based Suction Caisson Penetration Design: Insights from Back-Analysis of Large-Scale Field Installation Data
dc.typeJournal Article
dc.journal.volume151
dc.journal.issue7
dc.journal.titleJournal of Geotechnical and Geoenvironmental Engineering
dc.identifier.doi10.1061/JGGEFK.GTENG-13304
dc.journal.fristpage04025053-1
dc.journal.lastpage04025053-15
dc.page15
dc.treeJournal of Geotechnical and Geoenvironmental Engineering:;2025:;Volume ( 151 ):;issue: 007
dc.contenttypeFulltext


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