Technical Papers
Aug 4, 2021

Probabilistic Predictive Model for Liquefaction Triggering in Layered Sites Improved with Dense Granular Columns

Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 147, Issue 10

Abstract

This paper presents a probabilistic model for evaluating the liquefaction-triggering hazard in level, layered, and saturated granular soil profiles improved with dense granular columns (DGCs). The model is developed using the results of a comprehensive numerical parametric study, validated with a dynamic centrifuge test, and subsequently tested with the available case histories involving DGCs as a liquefaction countermeasure. The numerical database includes a total of 30,000, three-dimensional (3D), fully coupled, nonlinear, dynamic finite-element simulations with a statistically determined range of layer-, profile-, DGC-, and ground motion–specific input parameters. The criteria for the predicted degree of liquefaction (i.e., full, marginal, and no liquefaction) are based on the peak values of excess pore pressure ratio and shear strain anticipated within each soil layer. A machine learning approach that performs multinomial logistic regression along with variable selection and regularization is used to develop a set of functional forms for estimating the probabilities of full-, marginal-, and no-liquefaction in sites improved with DGCs. The proposed probabilistic model is the first of its kind that explicitly considers variations in the area replacement ratio (Ar), stiffness, and drainage capacity of the DGC; the thickness, depth, relative density, and hydraulic conductivity range of each layer; the evolutionary characteristics of ground motions; and the underlying uncertainty in the prediction of pore pressures and shear strains within each layer.

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Data Availability Statement

All data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors would like to acknowledge the Chilean National Commission for Science and Technology (Grant No. CONICYT-PCHA/Doctorado Nacional/2015-21150231) as well as the Department of Civil, Environmental, and Architectural Engineering at University of Colorado at Boulder (CU) for the financial support given to the first author. This work utilized the Summit supercomputer, which is supported by the National Science Foundation (Award No. CNS-0821794) and CU. The Summit supercomputer is a joint effort of the CU, the University of Colorado at Denver, and the National Center for Atmospheric Research.

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Journal of Geotechnical and Geoenvironmental Engineering
Volume 147Issue 10October 2021

History

Received: Aug 18, 2020
Accepted: May 14, 2021
Published online: Aug 4, 2021
Published in print: Oct 1, 2021
Discussion open until: Jan 4, 2022

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Juan Carlos Tiznado, A.M.ASCE [email protected]
Assistant Professor, Dept. of Structural and Geotechnical Engineering, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860, Macul, Santiago 7820436, Chile. Email: [email protected]
Associate Professor, Dept. of Civil, Environmental and Architectural Engineering, Univ. of Colorado Boulder, Boulder, CO 80309 (corresponding author). ORCID: https://orcid.org/0000-0002-7188-4208. Email: [email protected]
Associate Professor, Dept. of Structural and Geotechnical Engineering, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860, Macul, Santiago 7820436, Chile. ORCID: https://orcid.org/0000-0003-3821-6264. Email: [email protected]

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