Prediction of Liquefaction Susceptibility of Clean Sandy Soils Using Artificial Intelligence Techniques
By: Sabbar, Ayad Salih
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Contributor(s): Chegenizadeh, Amin.
Publisher: Germany Springer 2019Edition: Vol.49(1), February.Description: 58-69p.Subject(s): Civil EngineeringOnline resources: Click here
In:
Indian geotechnical journalSummary: The liquefaction susceptibility of sandy soil is generally characterised by some parameters in the static liquefaction potential evaluation. These parameters are usually measured by static laboratory tests on distributed and undistributed samples under different test conditions. This study performs the ANN and genetic programming to estimate the static liquefaction susceptibility of clean sand soils based on experimental results to predict and develop an equation for the ratio of qmin/qpeak which is considered as the static liquefaction criterion. The qmin/qpeak model is a function of the minimum and maximum void ratios, relative density, initial effective confining pressure, and some other parameters. The findings of this study demonstrated that a good agreement between ANN and symbolic regression in predicting the ratio of qmin/qpeak based on laboratory tests. The possible application of the proposed qmin/qpeak equation is restricted by some limitations. The outcomes of the present work can be used in the preliminary liquefaction assessment of clean sandy soils prior to the complementary experimental studies.
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Articles Abstract Database
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School of Engineering & Technology (PG) Archieval Section | Not for loan | 2021-2022257 |
The liquefaction susceptibility of sandy soil is generally characterised by some parameters in the static liquefaction potential evaluation. These parameters are usually measured by static laboratory tests on distributed and undistributed samples under different test conditions. This study performs the ANN and genetic programming to estimate the static liquefaction susceptibility of clean sand soils based on experimental results to predict and develop an equation for the ratio of qmin/qpeak which is considered as the static liquefaction criterion. The qmin/qpeak model is a function of the minimum and maximum void ratios, relative density, initial effective confining pressure, and some other parameters. The findings of this study demonstrated that a good agreement between ANN and symbolic regression in predicting the ratio of qmin/qpeak based on laboratory tests. The possible application of the proposed qmin/qpeak equation is restricted by some limitations. The outcomes of the present work can be used in the preliminary liquefaction assessment of clean sandy soils prior to the complementary experimental studies.
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