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Resistance deterioration which is purely a time function such as typified by simple corrosion problems is considered herein for structural systems subjected to one or more stochastic load processes. The resistances are modelled as Gaussian random variables and the loads as Gaussian random processes. Deterioration is considered by either of two simple models -exponential or parabolic functions of time. Both an upcrossing and an outcrossing formulation is used to estimate the up (out) crossing rate through linear domain boundaries. Numerical integration is employed to evaluate the resulting integrals, although significant simplifications are occasioned through the use of Gaussian random variables and processes. Results are given for two simple structural examples and compared to purely simulation results both for the outcrossing rate and for various sensitivity results. Good agreements is found. The results suggest that results for failure probability based on mean values of the deterioration models may be satisfactory in some cases.
The next section outlines the recent development of an appropriate model for fn(t, E) based on actual and very detailed observations of steels exposed to natural seawater. The model has been shown to be applicable to immersion, tidal and coastal atmospheric corrosion environments (Melchers 2003a, 2007b). Next is described how the model may be slightly simplified for practical application under longer-term exposure conditions. Field data is then used to estimate the variability in maximum pit depth at a given exposure location, derived from the application of extreme value statistics. Some comments are made also about the application of the simplified model.