A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Representative slip surface identification and reliability analysis of slope systems in spatially variable soils
A slope system is a series system with numerous potential slip surfaces (PSSs), and its failure probability is commonly evaluated by several significant failure surfaces, or representative slip surfaces (RSSs). Previous efforts have mainly identified the RSSs in spatially variable soils from the perspective of the correlations between different PSSs, the effects of the failure probabilities of the PSSs were rarely considered. With the goal of identifying RSSs from the perspective of the system failure probability, a method adopting the second-order reliability method (SORM) and the multimodal optimisation is proposed. In this method, the spatial variability of soil properties along the slip surface is characterised by local averaging to reduce the number of variables in SORM. Equations for calculating the correlation coefficient between different PSSs with correlated variables are derived. The task of RSS identification is transformed as a multimodal optimisation problem, and the PSSs that make great contributions to the system failure probability are determined as RSSs. The proposed method and the derived equations are demonstrated using two slope examples. The results show that the proposed method is capable of identifying RSSs with significant contributions, and it provides a proper estimate of the system failure probability.
Representative slip surface identification and reliability analysis of slope systems in spatially variable soils
A slope system is a series system with numerous potential slip surfaces (PSSs), and its failure probability is commonly evaluated by several significant failure surfaces, or representative slip surfaces (RSSs). Previous efforts have mainly identified the RSSs in spatially variable soils from the perspective of the correlations between different PSSs, the effects of the failure probabilities of the PSSs were rarely considered. With the goal of identifying RSSs from the perspective of the system failure probability, a method adopting the second-order reliability method (SORM) and the multimodal optimisation is proposed. In this method, the spatial variability of soil properties along the slip surface is characterised by local averaging to reduce the number of variables in SORM. Equations for calculating the correlation coefficient between different PSSs with correlated variables are derived. The task of RSS identification is transformed as a multimodal optimisation problem, and the PSSs that make great contributions to the system failure probability are determined as RSSs. The proposed method and the derived equations are demonstrated using two slope examples. The results show that the proposed method is capable of identifying RSSs with significant contributions, and it provides a proper estimate of the system failure probability.
Representative slip surface identification and reliability analysis of slope systems in spatially variable soils
Liu, Hui (author) / Zheng, Junjie (author) / Zhang, Rongjun (author) / Yang, Wenyu (author) / Guo, Yifan (author)
2023-07-03
18 pages
Article (Journal)
Electronic Resource
Unknown
Efficient slope reliability analysis at low-probability levels in spatially variable soils
| British Library Online Contents | 2016
Efficient slope reliability analysis at low-probability levels in spatially variable soils
| Online Contents | 2016
Efficient slope reliability analysis at low-probability levels in spatially variable soils
| British Library Online Contents | 2016
Efficient slope reliability analysis at low-probability levels in spatially variable soils
| British Library Online Contents | 2016
Bayesian updating of slope reliability in spatially variable soils with in-situ measurements
| British Library Online Contents | 2018