Bayesian identification of uncertainties in chloride ingress modeling into reinforced concrete structures

Emilio Bastidas-Arteaga (1) , Franck Schoefs (1) , Stéphanie Bonnet (1) , Alan O'Connor (2)

1 GeM - Institut de Recherche en Génie Civil et Mécanique
2 Trinity College Dublin

Chloride penetration is one of the major causes leading to the degradation of reinforced concrete structures by reinforcement corrosion. Therefore, its modeling is a major component in planning and quantifying maintenance operations of the structure. Modeling needs relevant material and environmental parameters determined from experimental measurements. The main objective of this paper is to develop a method for identifying the model parameters of chloride penetration into concrete from measurements using an inverse analysis model based on probabilistic principles. The results of the identification indicate that the Bayesian approach may be useful to identify the model parameters from real data.

Domaines: Mécanique [physics.med-ph]; Matériaux

Emilio Bastidas-Arteaga, Franck Schoefs, Stéphanie Bonnet, Alan O'Connor. Bayesian identification of uncertainties in chloride ingress modeling into reinforced concrete structures. Third International Symposium on Life-Cycle Civil Engineering, 2012, Vienna, Austria. ⟨hal-01007932⟩