Characterisation of the spatial variability of underconsolidated Singapore Marine Clay using random field theory

Publikation: Beitrag in FachzeitschriftMeinungsbeitragForschungPeer-Review

Autorschaft

  • Ze Zhou Wang
  • Xiangfeng Guo
  • Yue Hu

Externe Organisationen

  • University of Cambridge
  • South China University of Technology
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seitenumfang19
FachzeitschriftGeorisk
Frühes Online-Datum11 Nov. 2024
PublikationsstatusElektronisch veröffentlicht (E-Pub) - 11 Nov. 2024

Abstract

This paper characterised the spatial variability of Singapore Kallang Formation Marine Clays using piezocone penetration test (CPT) data from the Marina South area. Both vertical and horizontal scales of fluctuation in undrained shear strength for two distinct clay units, Upper Marine Clay (UMC) and Lower Marine Clay (LMC), are calibrated for autocorrelation and semi-variogram functions. The Marina South area was reclaimed from the sea using fills placed in three phases from 1970s to 1990s and remains underconsolidated up to date. This study identified variations in the degree of consolidation across the area, which has led to variations in the undrained shear strength in this area. However, the variations in the degree of consolidation were found to have no noticeable influence on the vertical and horizontal scales of fluctuation of either UMC or LMC unit. The vertical scales of fluctuation of UMC and LMC units are (Formula presented.) and (Formula presented.), respectively, while the horizontal scales of fluctuations are (Formula presented.) and (Formula presented.), respectively. The present study contributes to the database of the statistical and spatial variability of marine clays and can provide useful guidance for assessing reliability of excavations and foundations in Marina South as well as other areas with similar geological settings.

ASJC Scopus Sachgebiete

Ziele für nachhaltige Entwicklung

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Characterisation of the spatial variability of underconsolidated Singapore Marine Clay using random field theory. / Wang, Ze Zhou; Guo, Xiangfeng; Hu, Yue.
in: Georisk, 11.11.2024.

Publikation: Beitrag in FachzeitschriftMeinungsbeitragForschungPeer-Review

Wang ZZ, Guo X, Hu Y. Characterisation of the spatial variability of underconsolidated Singapore Marine Clay using random field theory. Georisk. 2024 Nov 11. Epub 2024 Nov 11. doi: 10.1080/17499518.2024.2422487
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T1 - Characterisation of the spatial variability of underconsolidated Singapore Marine Clay using random field theory

AU - Wang, Ze Zhou

AU - Guo, Xiangfeng

AU - Hu, Yue

N1 - Publisher Copyright: © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

PY - 2024/11/11

Y1 - 2024/11/11

N2 - This paper characterised the spatial variability of Singapore Kallang Formation Marine Clays using piezocone penetration test (CPT) data from the Marina South area. Both vertical and horizontal scales of fluctuation in undrained shear strength for two distinct clay units, Upper Marine Clay (UMC) and Lower Marine Clay (LMC), are calibrated for autocorrelation and semi-variogram functions. The Marina South area was reclaimed from the sea using fills placed in three phases from 1970s to 1990s and remains underconsolidated up to date. This study identified variations in the degree of consolidation across the area, which has led to variations in the undrained shear strength in this area. However, the variations in the degree of consolidation were found to have no noticeable influence on the vertical and horizontal scales of fluctuation of either UMC or LMC unit. The vertical scales of fluctuation of UMC and LMC units are (Formula presented.) and (Formula presented.), respectively, while the horizontal scales of fluctuations are (Formula presented.) and (Formula presented.), respectively. The present study contributes to the database of the statistical and spatial variability of marine clays and can provide useful guidance for assessing reliability of excavations and foundations in Marina South as well as other areas with similar geological settings.

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KW - spatial variability

KW - statistic analysis

KW - stochastic models

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