Structural reliability reformulation

Abstract When the general accuracy of a reliability method is not mathematically proven, the correctness of its yielded results may be in doubt. This study emphasizes this observation and proposes a reality-oriented concept for improved structural reliability analysis. The failure probability integral is reformulated based on this insight and two general approaches are presented for probability estimation, namely, probability expectation and control variates. The former is a general interpretation of the Monte Carlo simulation (MCS) based on which the formulation of the existing reliability methods can be used as an indicator function of the MCS, while the latter can remove errors of a reliability method by considering the assumptions employed in it. Using the suggested CV approach and considering the subset simulation as a method of interest, a general sequential framework is proposed for a robust reliability evaluation. Using the presented reality-oriented concept, some popular simulation methods are re-derived and it is shown that the proposed idea can be easily used to derive novel robust reliability methods.

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