Random Field Reliability Analysis for Time-Dependent Behaviour of Soft Soils Considering Spatial Variability of Elastic Visco-Plastic Parameters

可靠性(半导体) 土壤水分 领域(数学) 随机场 岩土工程 可靠性工程 统计 数学 环境科学 工程类 土壤科学 物理 量子力学 功率(物理) 纯数学
作者
Mehrnaz Alibeikloo,Hadi Khabbaz,Behzad Fatahi
出处
期刊:Reliability Engineering & System Safety [Elsevier]
卷期号:219: 108254-108254 被引量:15
标识
DOI:10.1016/j.ress.2021.108254
摘要

• K-L expansion method was adopted to generate random field with different spatial correlation lengths • A critical spatial correlation length existed for predicting time-dependent settlement of soft soils • A single random variable analysis is not always the most conservative analysis in predicting settlement of soft soils • It is essential to perform random field analysis to reduce the risk of the design to be applied in construction. Low embankment strategy is one of the effective methods to control time-dependent settlement of soft soils in infrastructure construction projects. Spatial variability of soil characteristics is a crucial factor, affecting the reliability of predictions of the long-term settlement in soft soils. In this paper, the time-dependent behaviour of soft soils is analysed incorporating spatial variability of elastic visco-plastic model parameters. Standard Gaussian random fields for correlated elastic-plastic model parameter ( λ / V ) and the initial creep coefficient ( ψ 0 / V ) are generated adopting Karhunen-Loeve expansion method based on the spectral decomposition of correlation function into eigenvalues and eigenfunctions. Then the generated random fields are incorporated in the proposed non-linear elastic visco-plastic (EVP) creep model. The impacts of spatially variable elastic visco-plastic model parameters (i.e. ψ 0 / V and λ / V ) on long-term settlement predictions are evaluated through random field analysis (RF) with different spatial correlation lengths, and results are then compared to a single random variable (SRV) analysis. The probability of failure (PF) is calculated adopting RF and SRV analysis to determine the critical spatial correlation length, resulted in a maximum probability of failure. This study can be employed by design engineers to determine the critical spatial correlation length for safe design in the absence of adequate data to determine the exact spatial correlation length. The results also confirm that SRV analysis is not always the most conservative analysis in predicting time-dependent settlement of soft soils; and it is essential to perform RF analysis considering the spatial correlation length to reduce the risk and increase the reliability of the design to be applied in construction.
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