Limitations of Surface Liquefaction Manifestation Severity Index Models Used in Conjunction with Simplified Stress-Based Triggering Models
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 148, Issue 3
Abstract
The severity of surface manifestation of liquefaction is commonly used as a proxy for liquefaction damage potential. As a result, manifestation severity index (MSI) models are more commonly being used in conjunction with simplified stress-based triggering models to predict liquefaction damage potential. This paper assesses the limitations of three existing MSI models and a fourth MSI model that is developed herein. The different models have differing attributes that account for factors influencing the severity of surficial liquefaction manifestations, with the newly proposed model accounting more factors than the others. The efficacies of these MSI models are evaluated using well-documented liquefaction case histories from Canterbury, New Zealand, with the deposits primarily comprising clean to nonplastic silty sands. It is found that the MSI models that explicitly account for the contractive/dilative tendencies of soil did not perform as well as the models that do not account for this tendency, opposite of what would be expected based on the mechanics of liquefaction manifestation. The likely reason for this is the double-counting of the dilative tendencies of medium-dense to dense soils by these MSI models because the liquefaction triggering model, to some extent, inherently accounts for such effects. This implies that development of mechanistically more rigorous MSI models that are used in conjunction with simplified triggering models will not necessarily result in improved liquefaction damage potential predictions and may result in less accurate predictions. This provides the impetus for the development of a new framework that clearly and distinctly separates triggering and manifestation.
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Data Availability Statement
The Canterbury data set is available in digital format through the NEHRI DesignSafe Data Depot at https://doi.org/10.17603/ds2-tygh-ht91. Alternatively, the subsurface data and aerial photographs are publically available through the New Zealand Geotechnical Database (NZGD 2020) website.
Acknowledgments
This research was funded by National Science Foundation (NSF) Grant Nos. CMMI-1751216, CMMI-1825189, and CMMI-1937984, as well as Pacific Earthquake Engineering Research Center (PEER) Grant No. 1132-NCTRBM and US Geological Survey award G18AP-00006. This support is gratefully acknowledged, as well as access to the NZGD. 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, PEER, USGS, or the NZGD.
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Journal of Geotechnical and Geoenvironmental Engineering
Volume 148 • Issue 3 • March 2022
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© 2021 American Society of Civil Engineers.
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Received: Apr 13, 2021
Accepted: Sep 28, 2021
Published online: Dec 22, 2021
Published in print: Mar 1, 2022
Discussion open until: May 22, 2022
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