CPT-Based Probabilistic Assessment of Seismic Soil Liquefaction Triggering Relationships

dc.contributor.authorCan, Gizem
dc.contributor.authorCetin, Kemal O.
dc.contributor.authorMoss, Robb E.S.
dc.contributor.authorKayen, Robert E.
dc.contributor.authorIlgac, Makbule
dc.contributor.authorUmut Ayhan, B.
dc.date.accessioned2026-07-02T12:42:43Z
dc.date.available2026-07-02T12:42:43Z
dc.date.issued2026
dc.departmentİstanbul Bilgi Üniversitesi
dc.descriptionGeo-Congress 2026: Earthquake Engineering and Soil Dynamics -- 9 March 2026 through 12 March 2026 -- Salt Lake City -- 219852
dc.description.abstractWithin the confines of this manuscript, updated CPT-based liquefaction triggering relationships are introduced. In the literature, there exist a number of CPT-based liquefaction triggering case histories, on the basis of which triggering relationships were developed. In this study, the prior database of Moss et al. is revisited and extended with additional case histories compiled from relatively recent events of 2001 Nisqually-Seattle, 2003 San Simeon, 2003 Bachu, 2008 Achaia-Elia, 2009 Padang, 2010 Jiasian, 2011 Tohoku, 2010 El Mayor Cucapah, 2010–2011 New Zealand-Canterbury, 2012 Emilia-Romagna, 2020 Samos-Aegean Sea, and 2023 Kahramanmaras earthquakes. The updated database, along with a discussion on the probabilistic case history processing methodology, is discussed. An illustrative case history is presented, along with a discussion on the probabilistic data procession scheme. After complying with the entire database, it is processed to develop improved CPT-based correlations for predicting the initiation of soil liquefaction during earthquakes; then, the database is evaluated by overall uncertainty using higher-order regression tools, with parameters represented by the mean and standard deviation. Maximum likelihood assessment is employed as the probabilistic framework for developing liquefaction triggering boundary curves and relationships. The resulting relationships provide an enhanced understanding of the effects of fines content, overburden stress, the geological and depositional setting on observed surface manifestations, and the presence of a crust layer. Finally, the updated model is compared with existing CPT-based seismic soil liquefaction triggering models in the literature. © ASCE.
dc.description.sponsorshipThe Geo-Institute of the American Society of Civil Engineers
dc.identifier.doi10.1061/9780784486702.012
dc.identifier.endpage126
dc.identifier.isbn978-078448670-2
dc.identifier.scopus2-s2.0-105035608123
dc.identifier.scopusqualityN/A
dc.identifier.startpage116
dc.identifier.urihttps://doi.org/10.1061/9780784486702.012
dc.identifier.urihttps://hdl.handle.net/11411/10954
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherAmerican Society of Civil Engineers (ASCE)
dc.relation.ispartofGeo-Congress 2026: Earthquake Engineering and Soil Dynamics - Selected papers from Geo-Congress 2026
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250701
dc.subjectDatabase systems; Earthquakes; Engineering geology; Geotechnical engineering; Logistic regression; Maximum likelihood; Soils; Structural geology; Uncertainty analysis; Aegean sea; Case history; High-order; Higher-order; New zealand; Probabilistic assessments; Probabilistic data; Probabilistics; Seattle; Uncertainty; Soil liquefaction
dc.titleCPT-Based Probabilistic Assessment of Seismic Soil Liquefaction Triggering Relationships
dc.typeConference Object

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