This paper investigates the settlement in a pavement due to soil liquefaction. Four 1-g shaking table tests were performed on saturated sand bed-pavement model to understand the factors affecting the liquefaction-induced settlements and their relation to the pavement thickness and width. All the tests were performed with a base acceleration of 320 gal in a laminar box. The shaking table tests revealed that the total settlement reduced with the increase in the pavement thickness. The pavement with the same thickness but different width showed that the total settlement reduced with the increase in the pavement width. The co-seismic settlement and post-seismic settlement depend upon the thickness and width of the pavement, and the maximum contribution of the sand ejecta is around 7.7% in the total settlement.
Data assimilation methods have been implemented on a slope stability problem, and the performance of different constitutive models and data assimilation schemes has been investigated. In the first part, a data assimilation scheme called the ensemble Kalman filter (EnKF) is implemented using a finite element model (FEM) and its performance with different constitutive models (the Mohr-Coulomb (MC) and Hardening Soil (HS) material models) is investigated to study their effect on the parameter and the factor of safety (FoS) estimation. Measurements of horizontal displacement are assimilated. The results from a synthetic example show that the HS model can generally be used to get reliable results for parameter and FoS estimation. However, using the MC model does not always output reliable parameter and FoS estimation. In the second part, the performance of different data assimilation schemes, i.e., the EnKF and ensemble smoother with multiple data assimilation (ESMDA), is studied with the preferred constitutive material model (the HS model). The results of a synthetic case show that the EnKF results in a narrower distribution for the FoS than the ESMDA method, while the latter results in FoS estimation which is closer to the 'truth'.
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