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ABSTRACT
Bi-planar sliding is one of main instabilities for bedding rock slope and is mainly dominated by the geometrical and strength properties of the weak structural plane. Traditional stability evaluation combines limit equilibrium method (LEM) with shear strength reduction (SSR) to derive the deterministic safety factor against slope stability. However, considering the uncertainties inherent in the geometrical and strength properties of the weak structural plane, as well as the variations of rock mass properties, the safety factor of rock bedding slopes against bi-planar sliding cannot be deterministically calculated. This study proposes a framework for probabilistic assessment on rock bedding slope stability against bi-planar sliding. Surrogate model for factor of safety against bi-planar sliding from LEM and SSR is developed based on back-propagation neural network (BPNN). The BPNN model, together with the design variables is implemented into the Excel Spreadsheet First-Order Reliability Method for the reliability assessment.
Acknowledgments
This work was supported by the National Key R&D Program of China (Project No. 2019YFC1509600), High-end Foreign Expert Introduction program (No. G20190022002) and Financial support from Chongqing City Construction Investment (Group) Co., Ltd. (Grant ID 2019-04). The financial supports are gratefully acknowledged.
Disclosure statement
No potential conflict of interest was reported by the author(s).