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Concrete bridges -- Floors -- Deterioration, Bridges -- Floors -- Deterioration, Concrete bridges -- Design and construction -- Statistical analysis, Concrete bridges -- United States -- Maintenance and repair -- Testing


Concrete highway bridge deck repairs represent the highest expense associated with bridge maintenance cost. In order to optimize such activities and use the available monies effectively, a solid understanding of the parameters that affect the performance of concrete bridge decks is critical. The National Bridge Inventory (NBI), perhaps the single-most comprehensive source of bridge information, gathers data on more than 600,000 bridges in all fifty states, the District of Columbia, and the Commonwealth of Puerto Rico. Focusing on concrete highway bridge deck performance, this research developed a nationwide database based on NBI data and other critical parameters that were computed by the authors, referred to as the Nationwide Concrete Highway Bridge Deck Performance Inventory (NCBDPI) database. Additionally, two performance parameters were computed from the available concrete bridge deck condition ratings (CR): Time-in-condition rating (TICR) and deterioration rate (DR). Following the aggregation of all these parameters in the NCBDPI database, filtering, and processing were performed. In addition to a basic prescriptive analysis, two types of advanced analysis were applied to the new dataset. First, binary logistic regression was applied to a subset of the data consisting of the highest and lowest DR. Second, a Bayesian survival analysis was performed on the TICR considering censored data. Through the analyses it was possible to show which parameters influence deck performance and create tools that can help agencies and bridge owners make better decisions regarding concrete bridge deck preservation.


At head of title: FHWA Collaborative Project.

Chapter 4 has been published in revised form under: Ghonima, O., Anderson, J. C., Schumacher, T., and Unnikrishnan, A. (2020). Performance of US Concrete Highway Bridge Decks Characterized by Random Parameters Binary Logistic Regression. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. Vol. 6(1). DOI:

Chapter 5 has been published in revised form under: Fleischhacker, A., Ghonima, O., and Schumacher, T. (2020). Bayesian Survival Analysis for US Concrete Highway Bridge Decks. ASCE Journal of Infrastructure Systems. Vol. 26(1). DOI:

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