Reliability analysis of static liquefaction of loose sand using the random finite element method

Abstract

Purpose – Liquefaction of soils is defined as significant reduction in shear strength and stiffness due to increase in pore water pressure. This phenomenon can occur in static (monotonic) or dynamic loading patterns. However, in each pattern, the inherent variability of the soil parameters indicates that this problem is of a probabilistic nature rather than being deterministic. The purpose of this paper is to present a method, based on random finite element method, for reliability assessment of static liquefaction of saturated loose sand under monotonic loading. Design/methodology/approach – The random finite element analysis is used for reliability assessment of static liquefaction of saturated loose sand under monotonic loading. The soil behavior is modeled by an elasto-plastic effective stress constitutive model. Independent soil parameters including saturated unit weight, peak friction angle and initial plastic shear modulus are selected as stochastic parameters which are modeled using a truncated normal probability density function (pdf). Findings – The probability of liquefaction is assessed by pdf of modified pore pressure ratio at each depth. For this purpose pore pressure ratio is modified for monotonic loading of soil. It is shown that the saturated unit weight is the most effective parameter, within the selected stochastic parameters, influencing the static soil liquefaction. Originality/value – This research focuses on the reliability analysis of static liquefaction potential of sandy soils. Three independent soil parameters including saturated unit weight, peak friction angle and initial plastic shear modulus are considered as stochastic input parameters. A computer model, coded in MATLAB, is developed for the random finite element analysis. For modeling of the soil behavior, a specific elasto-plastic effective stress constitutive model (UBCSAND) was used.

Probabilistic Analysis of Local Liquefaction Potential Based on Spatial Variability of SPT Data

“…Several methods have been proposed in the literature to predict the occurrence of liquefaction. Johari et al [15] had research based on reliability assessment of liquefaction potential using the jointly distributed random variables method and aslo Johari et al [16] investigated the reliability analysis of static liquefaction of loose sand using the random Finite Element Method (FEM). Hanna et al [17] proposed a method for developing the liquefaction potential based on General Regression Neural Network model (GRNN) analysis of field liquefaction performance records.…”

Advances in Gaussian random field generation: a review

“…Johari et al (2015) [59] proposed a RFEM-based approach to assess the reliability of static liquefaction of saturated loose sand under monotonic loading. Soil parameters, e.g., saturated unit weight, peak friction angle, and initial plastic shear modulus, were modeled by a 2-D Gaussian random field generated using Cholesky decomposition.…”

Relative density influence on the liquefaction potential of sand with fines

“…The most used current methods for site stabilization act on the relative density and drainage conditions of the soil, but lately other soil stabilization technics have been used by improving the resistance to liquefaction by including geotextile layers and increasing the permeability of the soil. New methods for analytical reliability of the liquefaction potential evaluation have been introduced such as those leading to the results of cone penetration tests (Johari & Khodaparast, 2014), using the random finite element method (Johari et al, 2015) or based on shear wave velocity (Johari et al, 2019). Such methods need more research in order to set a consensus on liquefaction conditions of soil, as well such methods have to be subjected to validation via experimental methods.…”