Prep rint Vers ion

4 Real behavior of existing structures is usually associated with large uncertainty that is often 5 covered by the use of conservative models and code practices for the evaluation of remaining fa6 tigue lives. In order to make better decisions related to retrofit and replacement of existing bridges, 7 new techniques that are able to quantify fatigue reserve capacity are required. This paper presents 8 a population-based prognosis methodology that takes advantage of in-service behavior measure9 ments using model-based data interpretation. This approach is combined with advanced traffic 10 and fatigue models to refine remaining-fatigue-life predictions. The study of a full-scale bridge 11 demonstrates that this methodology provides less conservative estimations of remaining fatigue 12 lives. In addition, this approach propagates uncertainties associated with finite-element, traffic and 13 fatigue-damage models to quantify their effects on fatigue-damage assessments and shows that 14 traffic models and structural model parameters are the most influential sources of uncertainty. 15