Methods for approximate reliability analysis

Abstract Approximate solutions are developed for reliability problems involving constant-in-time and time-dependent random parameters. They are based on estimates of the distribution of scalar control variables obtained from approximations of the safety condition (control variable approach) or on a transformation of the input space of parameters into a space in which the safety condition is nearly linear (linearization approach). The distribution of the control variable or of the random parameters in the transformed space can be estimated from moments of these variables. The control variable approach is most effective when the random parameters are constant in time while the linearization approach is useful for time-dependent reliability studies since it permits application of various rules (e.g., Turkstra's rule) for approximate load combination analysis.