A generalized surrogate response aided-subset simulation approach for efficient geotechnical reliability-based design. (April 2016)

• Record Type: Journal Article
• Authors: Li, Dian-Qing; Shao, Ke-Bo; Cao, Zi-Jun; Tang, Xiao-Song; Phoon, Kok-Kwang
• Is Part Of: Computers and geotechnics. Volume 74(2016)
• Page Start: 88
• Page End: 101
• Publication Date: 2016-04
• Subjects: Reliability-based design -- Subset simulation -- Driving variable -- Computational efficiency -- Geotechnical structures; Engineering geology -- Data processing -- Periodicals; Soil mechanics -- Data processing -- Periodicals; Rock mechanics -- Data processing -- Periodicals; 624.1510285
• DOI: 10.1016/j.compgeo.2015.12.010
• Languages: English
• ISSNs: 0266-352X

Abstract

Abstract: This paper aims to develop an efficient geotechnical reliability-based design (RBD) approach using Monte Carlo simulation (MCS). The proposed approach combines a recently developed MCS-based RBD approach, namely expanded RBD approach, with an advanced MCS method called "Subset Simulation (SS)" to improve the computation efficiency at small probability levels that are often concerned in geotechnical design practice. To facilitate the integration of SS and expanded RBD, a generalized surrogate response f is proposed to define the driving variable, which is a key parameter in SS, for expanded RBD of geotechnical structures (e.g., soil retaining structures and foundations). With the aid of the proposed surrogate response, failure probabilities of all the possible designs in a prescribed design space are calculated from a single run of SS. Equations are derived for integration of the surrogate response-aided SS and expanded RBD, and are illustrated using an embedded sheet pile wall design example and two drilled shaft design examples. Results show that the proposed approach provides reasonable estimates of failure probabilities of different designs using a single run of the surrogate response-aided SS, and significantly improves the computational efficiency at small probabilities levels in comparison with direct MCS-based expanded RBD. The surrogate response-aided SS is able to, simultaneously, approach the failure domains of all the possible designs in the design space by a single run of simulation and to generate more complete design information, which subsequently yields feasible designs with a wide range of combinations of design parameters. This is mainly attributed to the strong correlation between the surrogate response and target response (e.g., factor of safety) of different designs concerned in geotechnical RBD.