ABSTRACT
ABSTRACT: This paper investigates how to incorporate in-service live load data obtained via structural health monitoring (SHM) into the calculation of the reliability index β over time. The idea is that a structure could either be overly conservative in its design, in which case one would want to take advantage of this fact in maintenance scheduling, or a structure could be subjected to greater than anticipated loading, wear, or decay, also demanding maintenance adjustments. In this analysis a very important question is uncovered. What live load is most appropriate in calculating the reliability of a structure, the initial code-driven design load, a projected anticipated future load, or a load distribution created from an on-site historical demand history? To answer this question, a model is proposed that incorporates all three elements as they change over time. An innovative approach using the statistics of extremes is introduced to update, over time, a prior assumed load distribution to reflect the actual in-service loads on site. The results are then incorporated into the calculation of the reliability index through Bayesian updating and projected forward in time.
