2019 CSCE Annual Conference - Laval (Greater Montreal) Conference
Dr. Emad Elwakil, Purdue University (Presenter)
About $12.2 billion were estimated for repairs of approximately 17% of California’s bridges, at the beginning of 2018. This significant cost refers to the importance of preventive maintenance actions to reduce the deficient bridges. Deterioration models were widely used as a guide for identifying the maintenance priority and consequently reducing the cost of repairs. Prestressed concrete bridges represent about 24% of bridges in California. Thus, detecting damages and rating condition for these bridges is a contribution to the bridges maintenance system. This paper has utilized National Bridge Inventory (NBI) database for California State in order to develop four regression models for predicting the superstructure condition of four structure types (Slab ; Stringer / Multi Beam or Girder; T- Beam; and Box Beam or Girder). The developed models have investigated the significant variables on the superstructure deterioration using regression modeling. This research has come out with significant impact of eight variables with high coefficient of determination (R2=86%). The developed models have been validated using average validity percentage method (AVP) with a satisfactory result “93%”. The developed models will help infrastructure agencies to priorities the maintenance process for bridges, and support the inspected condition rating with objective opinion instead of subjective expert opinion only.