Abstract : In corrosive environments, cover depth is one of the dominant parameters that controls time to corrosion initiation. Consequently, probabilistic modeling of this variable is essential to determine the performance of structures during the time. In this work, we study the influence of cover depth on probability of corrosion initiation. Towards this aim, we compare the effect of the models commonly used in probabilistic modeling with models determined from image analysis. Preliminary results illustrate the importance of accurate characterization of this random variable for a realistic assessment of structural lifetime.
https://hal.archives-ouvertes.fr/hal-01009094
Contributor : Gilles Marckmann <>
Submitted on : Friday, October 9, 2020 - 7:40:34 AM Last modification on : Wednesday, December 16, 2020 - 4:22:03 PM Long-term archiving on: : Sunday, January 10, 2021 - 6:08:09 PM
Emilio Bastidas-Arteaga, E. Leonel, Franck Schoefs, C. Attard, Michel Roche. Use of image processing for structural computation updating during repair works of concrete structures. Structural Faults and Repair, 2010, Edinburgh, United Kingdom. ⟨hal-01009094⟩