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Effect of soil variability on nonlinear site response predictions: Application to the Lotung site

Lookup NU author(s): Yusuf Guzel, Dr Mohamed Rouainia, Dr Gaetano Elia

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

© 2020 Elsevier LtdThe shear wave velocity profile and dynamic soil properties are known to be affected by aleatory uncertainty. This paper aims to investigate the effect of a statistical variation in the initial stiffness profile, stiffness degradation and damping curves on ground response predictions by conducting stochastic analysis. The Large Scale Seismic Test site in Lotung, Taiwan, is back-analysed with a fully-coupled finite element procedure using an advanced kinematic hardening soil model. Two ground motions recorded at the site, one strong and one weak, are applied at bedrock level. The results reveal that the site response prediction is sensitive to the seismic intensity of the input motion. When the level of induced shear strain is higher, i.e. in the case of the stronger motion, the spatial variability of the stiffness degradation and damping curves has a pronounced effect on the predicted site response. In contrast, when the weaker motion is considered the prediction is particularly sensitive to the statistical variation in the initial stiffness profile. This is mainly due to the stiffness degradation at very small strains shown by the laboratory data on LSST soils, which is captured in the paper by assuming an appropriate elastic domain in the constitutive model calibration.


Publication metadata

Author(s): Guzel Y, Rouainia M, Elia G

Publication type: Article

Publication status: Published

Journal: Computers and Geotechnics

Year: 2020

Volume: 121

Print publication date: 01/05/2020

Online publication date: 29/02/2020

Acceptance date: 05/01/2020

Date deposited: 14/03/2020

ISSN (print): 0266-352X

ISSN (electronic): 1873-7633

Publisher: Elsevier Ltd

URL: https://doi.org/10.1016/j.compgeo.2020.103444

DOI: 10.1016/j.compgeo.2020.103444


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