Condition Factor Calibration for Load and Resistance Factor Rating of Steel Girder Bridges

The Load and Resistance Factor Rating (LRFR) is a reliability-based rating procedure complementary to the Load and Resistance Factor Design (LRFD). The intent of LRFR is to provide consistent reliability for all bridges regardless of in-situ condition. The primary difference between design and rating is the uncertain severity and location of deterioration, including the potential future loss of strength for an element already evidencing deterioration. Ostensibly, these uncertainties are accounted for by applying an additional strength reduction factor: the condition factor, ϕc. Currently, condition factors are nominally correlated to the condition of the member, which can be Good, Fair, or Poor. However, definitions of these condition categories are deferred to inspection documents, which themselves lack clear, objective definitions. Furthermore, lack of guidance to account for the location and extent of deterioration exacerbates confusion in the methodology to appropriately assign condition factors. These ambiguities cause incoherence between inspection and rating processes by introducing additional uncertainty. The additional uncertainty skews load ratings, sometimes producing ratings with unintended conservativism, and sometimes overestimating the safe load-carrying capacity of a bridge. This study presents a calibration of ϕc to be used with steel girder bridges, accounting for uncertainty due to non-uniform deterioration throughout transverse sections, lack of knowledge of the longitudinal location(s) of the deterioration, and the likelihood of further deterioration over the next inspection cycle for ranges of section loss for each condition. Section loss rangers are proposed to define each condition state for potential implementation by inspectors. The proposed condition state definitions and implementation methodology can improve uniformity in the inspection process and produce bridge load ratings that are more consistent with the target reliability intended by the rating procedure. Advisor: Joshua Steelma