The next-generation constitutive correlations for simulation of cyclic stress-strain behaviour of sand

This paper presents an innovate approach to simulate the stress-strain behaviour of sands subjected to large amplitude regular cyclic loading. New prediction correlations were derived for damping ratio (D) and shear modulus (G) of sand utilizing linear genetic programming (LGP) methodology. The cor...

Full description

Bibliographic Details
Main Authors: Habib Shahnazari, Yasser Dehnavi, Amir H. Alavi
Format: Article
Language:English
Published: Vilnius Gediminas Technical University 2014-12-01
Series:Journal of Civil Engineering and Management
Subjects:
Online Access:http://journals.vgtu.lt/index.php/JCEM/article/view/2996
id doaj-1bfb8d65be124073a99bbab6523f2625
record_format Article
spelling doaj-1bfb8d65be124073a99bbab6523f26252021-07-02T01:49:35ZengVilnius Gediminas Technical UniversityJournal of Civil Engineering and Management1392-37301822-36052014-12-0121110.3846/13923730.2013.802726The next-generation constitutive correlations for simulation of cyclic stress-strain behaviour of sandHabib Shahnazari0Yasser Dehnavi1Amir H. Alavi2School of Civil Engineering, Iran University of Science and Technology, Tehran, IranDepartment of Civil Engineering, University of Bojnord, Bojnord, IranDepartment of Civil and Environmental Engineering, Michigan State University, East Lansing, MI, 48824, USA This paper presents an innovate approach to simulate the stress-strain behaviour of sands subjected to large amplitude regular cyclic loading. New prediction correlations were derived for damping ratio (D) and shear modulus (G) of sand utilizing linear genetic programming (LGP) methodology. The correlations were developed using several cyclic torsional simple shear test results. In order to formulate D and G, new equations were developed to simulate hysteresis strain–stress curves and maximum shear stress (τmax) at different loading cycles. A genetic algorithm analysis was per­formed to optimize the parameters of the proposed formulation for stress-strain relationship. A total of 746 records were extracted from the simple shear test results to develop the τmax predictive model. Sensitivity and parametric analyses were conducted to verify the results. To investigate the applicability of the models, they were employed to simulate the stress-strain curves of portions of test results that were not included in the analysis. The LGP method precisely charac­terizes the complex hysteresis behaviour of sandy soils resulting in a very good prediction performance. The proposed design equations may be used by designers as efficient tools to determine D and G, specifically when laboratory testing is not possible. http://journals.vgtu.lt/index.php/JCEM/article/view/2996cyclic stress-strain relationshiplinear genetic programmingdamping ratioshear modulushardening
collection DOAJ
language English
format Article
sources DOAJ
author Habib Shahnazari
Yasser Dehnavi
Amir H. Alavi
spellingShingle Habib Shahnazari
Yasser Dehnavi
Amir H. Alavi
The next-generation constitutive correlations for simulation of cyclic stress-strain behaviour of sand
Journal of Civil Engineering and Management
cyclic stress-strain relationship
linear genetic programming
damping ratio
shear modulus
hardening
author_facet Habib Shahnazari
Yasser Dehnavi
Amir H. Alavi
author_sort Habib Shahnazari
title The next-generation constitutive correlations for simulation of cyclic stress-strain behaviour of sand
title_short The next-generation constitutive correlations for simulation of cyclic stress-strain behaviour of sand
title_full The next-generation constitutive correlations for simulation of cyclic stress-strain behaviour of sand
title_fullStr The next-generation constitutive correlations for simulation of cyclic stress-strain behaviour of sand
title_full_unstemmed The next-generation constitutive correlations for simulation of cyclic stress-strain behaviour of sand
title_sort next-generation constitutive correlations for simulation of cyclic stress-strain behaviour of sand
publisher Vilnius Gediminas Technical University
series Journal of Civil Engineering and Management
issn 1392-3730
1822-3605
publishDate 2014-12-01
description This paper presents an innovate approach to simulate the stress-strain behaviour of sands subjected to large amplitude regular cyclic loading. New prediction correlations were derived for damping ratio (D) and shear modulus (G) of sand utilizing linear genetic programming (LGP) methodology. The correlations were developed using several cyclic torsional simple shear test results. In order to formulate D and G, new equations were developed to simulate hysteresis strain–stress curves and maximum shear stress (τmax) at different loading cycles. A genetic algorithm analysis was per­formed to optimize the parameters of the proposed formulation for stress-strain relationship. A total of 746 records were extracted from the simple shear test results to develop the τmax predictive model. Sensitivity and parametric analyses were conducted to verify the results. To investigate the applicability of the models, they were employed to simulate the stress-strain curves of portions of test results that were not included in the analysis. The LGP method precisely charac­terizes the complex hysteresis behaviour of sandy soils resulting in a very good prediction performance. The proposed design equations may be used by designers as efficient tools to determine D and G, specifically when laboratory testing is not possible.
topic cyclic stress-strain relationship
linear genetic programming
damping ratio
shear modulus
hardening
url http://journals.vgtu.lt/index.php/JCEM/article/view/2996
work_keys_str_mv AT habibshahnazari thenextgenerationconstitutivecorrelationsforsimulationofcyclicstressstrainbehaviourofsand
AT yasserdehnavi thenextgenerationconstitutivecorrelationsforsimulationofcyclicstressstrainbehaviourofsand
AT amirhalavi thenextgenerationconstitutivecorrelationsforsimulationofcyclicstressstrainbehaviourofsand
AT habibshahnazari nextgenerationconstitutivecorrelationsforsimulationofcyclicstressstrainbehaviourofsand
AT yasserdehnavi nextgenerationconstitutivecorrelationsforsimulationofcyclicstressstrainbehaviourofsand
AT amirhalavi nextgenerationconstitutivecorrelationsforsimulationofcyclicstressstrainbehaviourofsand
_version_ 1721344239069036544