Reliability-based design sensitivity by efficient simulation

• Published in: Computers & structures Vol. 83; no. 14; pp. 1048 - 1061
• Main Author: Au, S.K.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Oxford Elsevier Ltd 01.05.2005; Elsevier Science
• Subjects: Exact sciences and technology; Failure analysis; Fracture mechanics (crack, fatigue, damage...); Fundamental areas of phenomenology (including applications); Monte Carlo method; Performance-based design; Physics; Reliability; Sensitivity analysis; Solid mechanics; Structural and continuum mechanics; Subset Simulation; Performance-based design; Monte Carlo method; Subset Simulation; Sensitivity analysis; Reliability; Failure analysis; Uncertain system; Probabilistic approach; Rupture; Rehabilitation; Small parameter method; Optimization
• ISSN: 0045-7949; 1879-2243
• DOI: 10.1016/j.compstruc.2004.11.015

Reliability-based design sensitivity analysis involves studying the dependence of the failure probability on design parameters. Conventionally, this requires repeated evaluations of the failure probability for different values of the design parameters, which is a direct but computationally expensive task. An efficient simulation approach is presented to perform reliability-based design sensitivity analysis using only one simulation run. The approach is based on consideration of an ‘augmented reliability problem’ where the design parameters are artificially considered as uncertain. It is shown that the desired information about reliability sensitivity can be extracted through failure analysis of the augmented problem. The required computational effort is relatively insensitive to the number of uncertain parameters but generally grows exponentially with the number of design parameters whose sensitivity is to be studied. The latter implies that the proposed approach is applicable for studying the sensitivity of a small number of design parameters, say, less than 3, although this drawback appears unavoidable whenever multi-dimensional information is sought. Examples are presented to illustrate applications of the approach to reliability-based retrofit of structures.