Assessing temporal requirements for SHM campaigns Available to Purchase

In the context of limited funds, continuous long-term monitoring may turn out not to be cost-effective to assess structural assets and estimate their service life. Motivated by this, the authors discuss how much data in terms of strain, pavement temperatures and traffic intensities are required to provide estimates of fatigue lives of an orthotropic steel deck. This is done by quantifying the uncertainty reduction due to increasing monitoring training data sets being available. First, several options for monitoring campaigns are defined in terms of the number, the time and the duration of the different monitoring phases associated with each monitoring option. The monitoring outcomes corresponding to each of the different monitoring options are then used to regress the statistical models for fatigue loading prediction based on daily averaged pavement temperatures and daily aggregated heavy-traffic counts. Fatigue reliability profiles are then calculated following a probabilistic methodology to estimate the remaining fatigue life for each location monitored. Finally, the error in determining the fatigue life of a structure detail is calculated for different monitoring options to determine the optimum duration for short-term monitoring campaigns. The proposed approach is illustrated by considering the field data from the Great Belt Bridge (Denmark).