TY - JOUR
T1 - Uncertainty quantification and propagation in the modeling of liquefiable sands.
AU - Mercado, Vicente
AU - Ochoa-Cornejo, Felipe
AU - Astroza, Rodrigo
AU - El-Sekelly, Waleed
AU - Abdoun, Tarek
AU - Pastén, Cesar
AU - Hernández, Francisco
N1 - Funding Information:
This study was partially funded by the Department of Civil Engineering of the Universidad de Chile, making possible the leave of professor V. Mercado to the Universidad de Chile. R. Astroza acknowledges the financial support from the Chilean National Commission for Scientific and Technological Research (CONICYT), through FONDECYT-Iniciación research grant No. 11160009. F. Ochoa-Cornejo acknowledges the financial support of CONICYT, Project FONDECYT-Iniciación No. 11181252, and from Universidad de Chile, Project U-Inicia Code N° UI 24/2018.
Funding Information:
This study was partially funded by the Department of Civil Engineering of the Universidad de Chile , making possible the leave of professor V. Mercado to the Universidad de Chile. R. Astroza acknowledges the financial support from the Chilean National Commission for Scientific and Technological Research (CONICYT) , through FONDECYT -Iniciación research grant No. 11160009 . F. Ochoa-Cornejo acknowledges the financial support of CONICYT, Project FONDECYT-Iniciación No. 11181252 , and from Universidad de Chile , Project U-Inicia Code N° UI 24/2018 .
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/8
Y1 - 2019/8
N2 - This paper combines data from laboratory, centrifuge testing, and numerical tools to highlight the predictive capabilities of the Bayesian method for uncertainty quantification and propagation. The Bayesian approach is employed to estimate uncertain parameters of a multi-yield constitutive model using data from cyclic-triaxial testing. Then, predictive capabilities of a finite element model in reproducing the dynamic response of a saturated sand deposit are investigated by drawing samples from the estimated posterior probability distributions of the constitutive model parameters. Variability of the predicted responses due to estimation uncertainty is evaluated. The response of centrifuge tests is used to assess the simulated responses.
AB - This paper combines data from laboratory, centrifuge testing, and numerical tools to highlight the predictive capabilities of the Bayesian method for uncertainty quantification and propagation. The Bayesian approach is employed to estimate uncertain parameters of a multi-yield constitutive model using data from cyclic-triaxial testing. Then, predictive capabilities of a finite element model in reproducing the dynamic response of a saturated sand deposit are investigated by drawing samples from the estimated posterior probability distributions of the constitutive model parameters. Variability of the predicted responses due to estimation uncertainty is evaluated. The response of centrifuge tests is used to assess the simulated responses.
UR - http://www.scopus.com/inward/record.url?scp=85065436908&partnerID=8YFLogxK
U2 - 10.1016/j.soildyn.2019.04.016
DO - 10.1016/j.soildyn.2019.04.016
M3 - Article
AN - SCOPUS:85065436908
SN - 0267-7261
VL - 123
SP - 217
EP - 229
JO - Soil Dynamics and Earthquake Engineering
JF - Soil Dynamics and Earthquake Engineering
ER -