Technical Papers
Sep 4, 2020

Accounting for Spatial Variability in Nonlinear Dynamic Analyses of Embankment Dams on Liquefiable Deposits

Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 146, Issue 11

Abstract

Nonlinear dynamic analyses (NDAs) of embankment dams of different heights founded on a spatially variable, liquefiable alluvial layer are used to examine factors influencing embankment deformations and develop guidance on selecting representative properties for uniform analysis models. Simulations are presented for embankments ranging from 5 to 45  m high on stochastic and uniform alluvial layers subjected to a range of input motions, with sensitivity cases including the effects of various parameters describing the alluvium and embankments. Crest settlements and slope displacements obtained from the analyses with stochastic and uniform alluvial layers are compared to obtain equivalent uniform or representative percentile properties for which a uniform model produces the same deformation as a stochastic model. The representative percentile properties to estimate median deformations from a set of stochastic realizations are generally between the 40th and 60th percentile, whereas the representative percentile properties to estimate deformations conservatively (i.e., exceeded in less than 16% of the analysis cases) are generally closer to the 30th percentile. The variability in deformation patterns obtained with the stochastic models increases as the alluvium’s scale of fluctuation in the horizontal direction increases relative to the embankment base width. Recommendations regarding factors to consider in selecting representative properties for spatially variable alluvial foundations in NDAs of embankment dams and the corresponding variability in deformations are presented.

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Data Availability Statement

Data that support the findings of this study available from the corresponding author upon reasonable request.

Acknowledgments

The work described herein progressed under projects for the California Department of Water Resources under Contract No. 4600009751 and the National Science Foundation under grant CMMI-1635398. Any opinions, findings, conclusions, or recommendations expressed herein are those of the authors and do not necessarily represent the views of these organizations. Professor Jack Montgomery provided assistance with the initial stochastic modeling. The anonymous reviewers provided valuable comments that improved the manuscript. The authors appreciate the above support and assistance.

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Go to Journal of Geotechnical and Geoenvironmental Engineering
Journal of Geotechnical and Geoenvironmental Engineering
Volume 146Issue 11November 2020

History

Received: Dec 9, 2019
Accepted: Jun 10, 2020
Published online: Sep 4, 2020
Published in print: Nov 1, 2020
Discussion open until: Feb 4, 2021

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Authors

Affiliations

Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of California, Davis, CA 95616 (corresponding author). ORCID: https://orcid.org/0000-0003-3591-9749. Email: [email protected]
Ross W. Boulanger, Ph.D., F.ASCE [email protected]
P.E.
Professor, Dept. of Civil and Environmental Engineering, Univ. of California, Davis, CA 95616. Email: [email protected]
Professor, Dept. of Civil and Environmental Engineering, Univ. of California, Davis, CA 95616. ORCID: https://orcid.org/0000-0002-9809-955X. Email: [email protected]

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