Verification of random field-based liquefaction mapping using a synthetic digital soil field

Qiushi Chen, Mengfen Shen, Chaofeng Wang, C. Hsein Juang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

In this paper, a classical CPT-based liquefaction model is integrated with geostatistical tools and random field models to evaluate and map liquefaction potentials over an extended area. Verification of random field-based liquefaction prediction is challenging and rarely addressed in current literature due to limitation of soil data and liquefaction observations. To this end, a three-dimensional synthetic digital soil field is generated through novel numerical models, providing extreme detailed soil properties and corresponding liquefaction hazard information quantified in terms of the liquefaction potential index (LPI). Different virtual field testing plans are designed to investigate the effect of data inference on the model performance. Three ranking criteria are used to evaluate model performance. Knowledge gained through the model verification process can be used to guide the inference of model parameters and understanding the performance of random field-based liquefaction hazard mapping.

Original languageEnglish
Title of host publicationGeotechnical Special Publication
EditorsThomas L. Brandon, Richard J. Valentine
PublisherAmerican Society of Civil Engineers (ASCE)
Pages236-245
Number of pages10
EditionGSP 281
ISBN (Electronic)9780784480489
DOIs
StatePublished - 2017
EventGeotechnical Frontiers 2017 - Orlando, United States
Duration: 12 Mar 201715 Mar 2017

Publication series

NameGeotechnical Special Publication
NumberGSP 281
Volume0
ISSN (Print)0895-0563

Conference

ConferenceGeotechnical Frontiers 2017
Country/TerritoryUnited States
CityOrlando
Period12/03/1715/03/17

Fingerprint

Dive into the research topics of 'Verification of random field-based liquefaction mapping using a synthetic digital soil field'. Together they form a unique fingerprint.

Cite this