Fragility Functions for Liquefaction-Induced Ground Failure
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 146, Issue 12
Abstract
The predicted severity of liquefaction manifested at the ground surface is a popular and pragmatic proxy of damage potential for infrastructure. Toward this end, the liquefaction potential index () and similar models are commonly used, and often codified, to predict surface manifestations on level ground. These predictions typically use deterministic thresholds from the literature—obtained via calibration on case-history data—to classify the expected manifestation. While widely adopted, such thresholds obscure the uncertainty of expected outcomes and are incompatible with probabilistic frameworks. Proposed thresholds are also intimately tied to the liquefaction analytics used to compute them and to the methodology used to select them, each of which can conflict with forward applications, leading to erroneous predictions. Accordingly, using 15,223 case histories from 24 earthquakes, this study develops fragility functions that probabilistically predict surficial manifestations of liquefaction using triggering and manifestation models popular in practice. Deterministic workflows are easily extended by selecting appropriate fragility coefficients; options are provided for six cone penetration test (CPT)–based triggering models, one CPT-inversion filter, three manifestation models, and three manifestation severities. The model application is demonstrated by predicting (1) liquefaction manifestations in Christchurch, New Zealand, resulting from an Alpine Fault earthquake, wherein a logic-tree is used to ensemble predictions from 18 models, and (2) the return period of liquefaction manifestations in the South-of-Downtown (SODO) district of Seattle, wherein predictions are compared to historical observations.
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Data Availability Statement
Some or all data, models, or code generated during the study are available from the corresponding author, including Tables 4 and 5 as well as all data associated with the Canterbury case-history dataset. In addition, all calculations demonstrated in this study, including CPT processing, may be performed using Horizon (Geyin and Maurer 2020), a freely available open-source program developed by the authors.
Acknowledgments
The presented study is based upon work supported by the National Science Foundation (NSF) (Grant No. CMMI-1751216), USGS (Grant No. G18AP-00006), and Pacific Earthquake Engineering Research Center (PEER) (Grant No. 1132-NCTRBM). However, any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of NSF, USGS, or PEER.
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Journal of Geotechnical and Geoenvironmental Engineering
Volume 146 • Issue 12 • December 2020
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© 2020 American Society of Civil Engineers.
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Received: Sep 27, 2019
Accepted: Jul 27, 2020
Published online: Oct 8, 2020
Published in print: Dec 1, 2020
Discussion open until: Mar 8, 2021
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