Title:
Probabilistic Service Life Modeling: Validation Case Studies
Author(s):
Abdelrahman
Publication:
Web Session
Volume:
ws_S25_Abdelraman.pdf
Issue:
Appears on pages(s):
Keywords:
DOI:
Date:
3/30/2025
Abstract:
Rehabilitation planning for reinforced concrete structures is often most effective when supported by comprehensive field evaluations and probabilistic service life modeling grounded in field data. To be useful, these service life models need to consider variability in the input parameters that are the basis for the probabilistic modeling. This presentation includes two case studies of reinforced concrete bridge decks in the Midwest United States exposed to de-icing agents. Initial assessments and material testing were conducted in the early 2010s, with follow-up evaluations approximately a decade later in the early 2020s. These studies focused on: 1) measuring as-built cover and variability across structures relative to design documents; 2) evaluating changes in chloride concentration profile from the surface to the reinforcing; and 3) comparing field observed damage to service life model predictions. The findings demonstrated the importance of probabilistic modeling in capturing the inherent variability in as-built properties, material behavior, and exposure conditions and highlight the need for expertise in interpreting and utilizing investigation results effectively.