Adaptive sampling strategy for characterizing spatial distribution of soil liquefaction potential using cone penetration test

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)1221-1231
Journal / PublicationJournal of Rock Mechanics and Geotechnical Engineering
Volume14
Issue number4
Online published18 Mar 2022
Publication statusPublished - Aug 2022

Abstract

Characterizing spatial distribution of soil liquefaction potential is critical for assessing liquefaction-related hazards (e.g. building damages caused by liquefaction-induced differential settlement). However, in engineering practice, soil liquefaction potential is usually measured at limited locations in a specific site using in situ tests, e.g. cone penetration tests (CPTs), due to the restrictions of time, cost and access to subsurface space. In these cases, liquefaction potential of soil at untested locations requires to be interpreted from limited measured data points using proper interpolation method, leading to remarkable statistical uncertainty in liquefaction assessment. This underlines an important question of how to optimize the locations of CPT soundings and determine the minimum number of CPTs for achieving a target reliability level of liquefaction assessment. To tackle this issue, this study proposes a smart sampling strategy for determining the minimum number of CPTs and their optimal locations in a self-adaptive and data-driven manner. The proposed sampling strategy leverages on information entropy and Bayesian compressive sampling (BCS). Both simulated and real CPT data are used to demonstrate the proposed method. Illustrative examples indicate that the proposed method can adaptively and sequentially select the required number and optimal locations of CPTs.

Research Area(s)

  • Compressive sampling, Cone penetration test (CPT), Information entropy, Liquefaction potential, Site characterization

Citation Format(s)

Adaptive sampling strategy for characterizing spatial distribution of soil liquefaction potential using cone penetration test. / Guan, Zheng; Wang, Yu; Zhao, Tengyuan.

In: Journal of Rock Mechanics and Geotechnical Engineering, Vol. 14, No. 4, 08.2022, p. 1221-1231.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review