Practical Method of Reliability-based Assessment and Lifecycle Management of Deteriorating Existing Structures

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The continued use of existing structures is one of the most important factors for achieving sustainable society. In order to assess such structures for continued future service, simple and practical tools need to be developed for evaluating the time-dependent reliability and performance of the structures.The investigator has introduced the concept of a resistance reduction factor in order to take the impact of degradation of a structural component on its performance level into account in a scalar value. With the factor a time-dependent reliability problem can be approximated as a time-independent one and existing simple methods such as AFOSM can be used for reliability assessment. In this research, a practical formula for a resistance reduction factor is proposed classifying the cumulative distribution functions according to the classification of parent distributions of extreme value distributions. Numerical examples show that the method provides an estimate with relatively large error … More when the variability in the principal load is small and/or the variability in the resistance is large. Yet the error level is comparable with the error due to AFOSM and would not cause a problem in practice.Periodic in-service inspection followed by suitable maintenance may restore a degraded structural component to near-original condition. Since inspection and maintenance are costly, there are tradeoffs between the extent and accuracy of inspection, required level of reliability, and cost. To design an optimum inspection/maintenance strategy with minimum expected total lifecycle cost, generally non-linear optimization problem must be solved. The practical method can be applied to estimate a resistance reduction factor including the cases when the strength of a component changes discontinuously in time due to, such as, restoration. Using the proposed method, the time-dependent reliability analysis can be avoided in the optimization and the computational time can be reduced about a fiftieth. Less