Design charts for reliability assessment of rock bedding slopes stability against bi-planar sliding: SRLEM and BPNN approaches. Issue 2 (3rd April 2022)

• Record Type: Journal Article
• Authors: Chen, Longlong; Zhang, Wengang; Gao, Xuecheng; Wang, Lin; Li, Zheng; Böhlke, Thomas; Perego, Umberto
• Is Part Of: Georisk. Volume 16:Issue 2(2022)
• Page Start: 360
• Page End: 375
• Publication Date: 2022-04-03
• Subjects: Rock bedding slope -- bi-planar sliding -- reliability assessment -- back-propagation neural network -- First-Order reliability method -- safety factor; Environmental risk assessment -- Periodicals; Hazardous geographic environments -- Risk assessment -- Periodicals; Reliability (Engineering) -- Periodicals; Risk management -- Periodicals; 624.151
• DOI: 10.1080/17499518.2020.1815215
• Languages: English
• ISSNs: 1749-9518

Abstract

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.