Geoscience Frontiers

Geoscience Frontiers

Volume 3, Issue 4, July 2012, Pages 541-555
Geoscience Frontiers

Research Paper
Energy-based numerical models for assessment of soil liquefaction

https://doi.org/10.1016/j.gsf.2011.12.008Get rights and content
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open access

Abstract

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.

Highlights

► The LGP and MEP methodologies were used to evaluate the liquefaction resistance of sandy soils. ► The capacity energy was formulated in terms of several factors affecting the liquefaction potential. ► The external validation of the models was successfully verified using different statistical criteria. ► The best LGP and MEP models perform superior than several models found in the literature.

Keywords

Soil liquefaction
Capacity energy
Linear genetic programming
Multi expression programming
Sand
Formulation

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