Energy-based numerical models for assessment of soil liquefaction

This study presents promising variants of genetic programming (GP), namely linear genetic programming (LGP) and multi expression programming (MEP) to evaluate the liquefaction resistance of sandy soils. Generalized LGP and MEP-based relationships were developed between the strain energy density requ...

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Main Authors: Amir Hossein Alavi, Amir Hossein Gandomi
Format: Article
Language:English
Published: Elsevier 2012-07-01
Series:Geoscience Frontiers
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S167498711100137X
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spelling doaj-079de003e3fe4aff8c61523affcf9e162020-11-24T21:42:08ZengElsevierGeoscience Frontiers1674-98712012-07-013454155510.1016/j.gsf.2011.12.008Energy-based numerical models for assessment of soil liquefactionAmir Hossein Alavi0Amir Hossein Gandomi1School of Civil Engineering, Iran University of Science and Technology, Tehran, IranCollege of Civil Engineering, Tafresh University, Tafresh, IranThis study presents promising variants of genetic programming (GP), namely linear genetic programming (LGP) and multi expression programming (MEP) to evaluate the liquefaction resistance of sandy soils. Generalized LGP and MEP-based relationships were developed between the strain energy density required to trigger liquefaction (capacity energy) and the factors affecting the liquefaction characteristics of sands. The correlations were established based on well established and widely dispersed experimental results obtained from the literature. To verify the applicability of the derived models, they were employed to estimate the capacity energy values of parts of the test results that were not included in the analysis. The external validation of the models was verified using statistical criteria recommended by researchers. Sensitivity and parametric analyses were performed for further verification of the correlations. The results indicate that the proposed correlations are effectively capable of capturing the liquefaction resistance of a number of sandy soils. The developed correlations provide a significantly better prediction performance than the models found in the literature. Furthermore, the best LGP and MEP models perform superior than the optimal traditional GP model. The verification phases confirm the efficiency of the derived correlations for their general application to the assessment of the strain energy at the onset of liquefaction.http://www.sciencedirect.com/science/article/pii/S167498711100137XSoil liquefactionCapacity energyLinear genetic programmingMulti expression programmingSandFormulation
collection DOAJ
language English
format Article
sources DOAJ
author Amir Hossein Alavi
Amir Hossein Gandomi
spellingShingle Amir Hossein Alavi
Amir Hossein Gandomi
Energy-based numerical models for assessment of soil liquefaction
Geoscience Frontiers
Soil liquefaction
Capacity energy
Linear genetic programming
Multi expression programming
Sand
Formulation
author_facet Amir Hossein Alavi
Amir Hossein Gandomi
author_sort Amir Hossein Alavi
title Energy-based numerical models for assessment of soil liquefaction
title_short Energy-based numerical models for assessment of soil liquefaction
title_full Energy-based numerical models for assessment of soil liquefaction
title_fullStr Energy-based numerical models for assessment of soil liquefaction
title_full_unstemmed Energy-based numerical models for assessment of soil liquefaction
title_sort energy-based numerical models for assessment of soil liquefaction
publisher Elsevier
series Geoscience Frontiers
issn 1674-9871
publishDate 2012-07-01
description This study presents promising variants of genetic programming (GP), namely linear genetic programming (LGP) and multi expression programming (MEP) to evaluate the liquefaction resistance of sandy soils. Generalized LGP and MEP-based relationships were developed between the strain energy density required to trigger liquefaction (capacity energy) and the factors affecting the liquefaction characteristics of sands. The correlations were established based on well established and widely dispersed experimental results obtained from the literature. To verify the applicability of the derived models, they were employed to estimate the capacity energy values of parts of the test results that were not included in the analysis. The external validation of the models was verified using statistical criteria recommended by researchers. Sensitivity and parametric analyses were performed for further verification of the correlations. The results indicate that the proposed correlations are effectively capable of capturing the liquefaction resistance of a number of sandy soils. The developed correlations provide a significantly better prediction performance than the models found in the literature. Furthermore, the best LGP and MEP models perform superior than the optimal traditional GP model. The verification phases confirm the efficiency of the derived correlations for their general application to the assessment of the strain energy at the onset of liquefaction.
topic Soil liquefaction
Capacity energy
Linear genetic programming
Multi expression programming
Sand
Formulation
url http://www.sciencedirect.com/science/article/pii/S167498711100137X
work_keys_str_mv AT amirhosseinalavi energybasednumericalmodelsforassessmentofsoilliquefaction
AT amirhosseingandomi energybasednumericalmodelsforassessmentofsoilliquefaction
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