Probabilistic risk assessment of earth dams with spatially variable soil properties using random adaptive finite element limit analysis



Liao, Kang, Wu, Yiping, Miao, Fasheng, Pan, Yutao and Beer, Michael ORCID: 0000-0002-0611-0345
(2023) Probabilistic risk assessment of earth dams with spatially variable soil properties using random adaptive finite element limit analysis. Engineering with Computers, 39 (5). pp. 3313-3326.

[img] Text
Manuscript.pdf - Author Accepted Manuscript

Download (1MB) | Preview

Abstract

Risk assessment of earth dams is concerned not only with the probability of failure but also with the corresponding consequence, which can be more difficult to quantify when the spatial variability of soil properties is involved. This study presents a risk assessment for an earth dam in spatially variable soils using the random adaptive finite element limit analysis. The random field theory, adaptive finite element limit analysis, and Monte Carlo simulation are employed to implement the entire process. Among these methods, the random field theory is first introduced to describe the soil spatial variability. Then the adaptive finite element limit analysis is adopted to obtain the bound solution and consequence. Finally, the failure probability and risk assessment are counted via the Monte Carlo simulation. In contrary to the deterministic analysis that only a factor of safety is given, the stochastic analysis considering the spatial variability can provide statistical characteristics of the stability and assess the risk of the earth dam failure comprehensively, which can be further used for guiding decision-making and mitigation. Besides, the effects of the correlation structure of strength parameters on the stochastic response and risk assessment of the earth dam are investigated through parametric analysis.

Item Type: Article
Uncontrolled Keywords: Risk assessment, Spatial variability, Random adaptive finite element limit analysis, Random field theory, Monte Carlo simulation
Divisions: Faculty of Science and Engineering > School of Engineering
Depositing User: Symplectic Admin
Date Deposited: 08 Mar 2023 11:06
Last Modified: 07 Nov 2023 02:30
DOI: 10.1007/s00366-022-01752-0
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3168839