Importance sampling for system reliability analysis of soil slopes based on shear strength reduction

ABSTRACT

Probabilistic methods are increasingly used to quantify the effect of uncertainties on slope stability assessment. The shear strength reduction method can be used for slope stability analysis without prior assumption on the shape of the failure surfaces, and hence is an attractive method for slope stability analysis. Since it is computationally more demanding than limit equilibrium methods, reliability analysis based on the shear strength reduction method is often considered as computationally challenging. In this paper, an importance sampling method is suggested to conduct system reliability analysis of soil slopes based on the shear strength reduction method. In the suggested method, the design points are first identified using a response surface method. Then, a sampling function is constructed centred at the design points. An efficient method is used to identify the failure samples based on the shear strength reduction method. Results from two illustrative examples show that the suggested importance sampling method is an effective and robust tool for system reliability analysis of soil slopes.

KEYWORDS:

• System reliability
• importance sampling
• shear strength reduction method

Acknowledgements

This work was substantially supported by the Research Funding from Yunnan Provincial Communication Department (Project No. 2018-26), Shuguang Program from Shanghai Education Development Foundation and Shanghai Municipal Education Commission (19SG19), National Key R&D Programmes of China (2018YFC0809600, 2018YFC0809601), National Natural Science Foundation of China (51538009, 41672276), Key Innovation Team Program of MOST of China (2016RA4059) and Fundamental Research Funds for the Central Universities.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 41672276, 51538009]; Key Innovation Team Program of MOST of China [grant number 2016RA4059]; Fundamental Research Funds for the Central Universities; Research Funding from Yunnan Provincial Communication Department [grant number 2018-26]; National Key R&D Programmes of China [grant numbers 2018YFC0809600, 2018YFC0809601].