Soil liquefaction assessment using soft computing approaches based on capacity energy concept

Soil liquefaction is one of the most complicated phenomena to assess in geotechnical earthquake engineering. The conventional procedures developed to determine the liquefaction potential of sandy soil deposits can be categorized into three main groups: Stress-based, strain-based, and energy-based pr...

Full description

Saved in:
Bibliographic Details
Main Authors: Chen, Zhixiong, Li, Hongrui, Goh, Anthony Teck Chee, Wu, Chongzhi, Zhang, Wengang
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2021
Subjects:
Online Access:https://hdl.handle.net/10356/146244
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-146244
record_format dspace
spelling sg-ntu-dr.10356-1462442021-02-04T01:48:29Z Soil liquefaction assessment using soft computing approaches based on capacity energy concept Chen, Zhixiong Li, Hongrui Goh, Anthony Teck Chee Wu, Chongzhi Zhang, Wengang School of Civil and Environmental Engineering Engineering::Civil engineering Soil Liquefaction Capacity Energy Soil liquefaction is one of the most complicated phenomena to assess in geotechnical earthquake engineering. The conventional procedures developed to determine the liquefaction potential of sandy soil deposits can be categorized into three main groups: Stress-based, strain-based, and energy-based procedures. The main advantage of the energy-based approach over the remaining two methods is the fact that it considers the effects of strain and stress concurrently unlike the stress or strain-based methods. Several liquefaction evaluation procedures and approaches have been developed relating the capacity energy to the initial soil parameters, such as the relative density, initial effective confining pressure, fine contents, and soil textural properties. In this study, based on the capacity energy database by Baziar et al. (2011), analyses have been carried out on a total of 405 previously published tests using soft computing approaches, including Ridge, Lasso & LassoCV, Random Forest, eXtreme Gradient Boost (XGBoost), and Multivariate Adaptive Regression Splines (MARS) approaches, to assess the capacity energy required to trigger liquefaction in sand and silty sands. The results clearly prove the capability of the proposed models and the capacity energy concept to assess liquefaction resistance of soils. It is also proposed that these approaches should be used as cross-validation against each other. The result shows that the capacity energy is most sensitive to the relative density. Published version 2021-02-04T01:48:28Z 2021-02-04T01:48:28Z 2020 Journal Article Chen, Z., Li, H., Goh, A. T. C., Wu, C., & Zhang, W. (2020). Soil Liquefaction Assessment Using Soft Computing Approaches Based on Capacity Energy Concept. Geosciences, 10(9), 330-. doi:10.3390/geosciences10090330 2076-3263 https://hdl.handle.net/10356/146244 10.3390/geosciences10090330 2-s2.0-85090540918 9 10 en Geosciences © 2020 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Civil engineering
Soil Liquefaction
Capacity Energy
spellingShingle Engineering::Civil engineering
Soil Liquefaction
Capacity Energy
Chen, Zhixiong
Li, Hongrui
Goh, Anthony Teck Chee
Wu, Chongzhi
Zhang, Wengang
Soil liquefaction assessment using soft computing approaches based on capacity energy concept
description Soil liquefaction is one of the most complicated phenomena to assess in geotechnical earthquake engineering. The conventional procedures developed to determine the liquefaction potential of sandy soil deposits can be categorized into three main groups: Stress-based, strain-based, and energy-based procedures. The main advantage of the energy-based approach over the remaining two methods is the fact that it considers the effects of strain and stress concurrently unlike the stress or strain-based methods. Several liquefaction evaluation procedures and approaches have been developed relating the capacity energy to the initial soil parameters, such as the relative density, initial effective confining pressure, fine contents, and soil textural properties. In this study, based on the capacity energy database by Baziar et al. (2011), analyses have been carried out on a total of 405 previously published tests using soft computing approaches, including Ridge, Lasso & LassoCV, Random Forest, eXtreme Gradient Boost (XGBoost), and Multivariate Adaptive Regression Splines (MARS) approaches, to assess the capacity energy required to trigger liquefaction in sand and silty sands. The results clearly prove the capability of the proposed models and the capacity energy concept to assess liquefaction resistance of soils. It is also proposed that these approaches should be used as cross-validation against each other. The result shows that the capacity energy is most sensitive to the relative density.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Chen, Zhixiong
Li, Hongrui
Goh, Anthony Teck Chee
Wu, Chongzhi
Zhang, Wengang
format Article
author Chen, Zhixiong
Li, Hongrui
Goh, Anthony Teck Chee
Wu, Chongzhi
Zhang, Wengang
author_sort Chen, Zhixiong
title Soil liquefaction assessment using soft computing approaches based on capacity energy concept
title_short Soil liquefaction assessment using soft computing approaches based on capacity energy concept
title_full Soil liquefaction assessment using soft computing approaches based on capacity energy concept
title_fullStr Soil liquefaction assessment using soft computing approaches based on capacity energy concept
title_full_unstemmed Soil liquefaction assessment using soft computing approaches based on capacity energy concept
title_sort soil liquefaction assessment using soft computing approaches based on capacity energy concept
publishDate 2021
url https://hdl.handle.net/10356/146244
_version_ 1692012996625170432