Article

Reliability assessment of deteriorating reinforced concrete structures by representing the coupled effect of corrosion initiation and progression by Bayesian networks

Reliability assessment of deteriorating reinforced concrete structures by representing the coupled effect of corrosion initiation and progression by Bayesian networks

  • Hackl, J., and Köhler, J. (2016). Reliability assessment of deteriorating reinforced concrete structures by representing the coupled effect of corrosion initiation and progression by Bayesian networks. Structural Safety, 62, 12–23. doi: 10.1016/j.strusafe.2016.05.005

Abstract

Reinforced concrete structures constitute an essential part of the building infrastructure. This infrastructure is aging, and a large number of structures will exceed the prescribed service period in the near future. The aging of concrete structures is often accompanied by corresponding deterioration mechanisms. One of the major deterioration mechanisms is the corrosion of the reinforcing steel, caused by chloride ions and carbon dioxide exposure. Here, a generic framework for the stochastic modeling of reinforced concrete deterioration caused by corrosion is presented. This framework couples existing probabilistic models for chloride and carbonation initiation with models for the propagation and consequences of corrosion. For this purpose, a combination of structural reliability analysis and Bayesian networks is used to estimate the probability of failure of a reinforced concrete structure. This approach allows the calculation of probabilities of rare events for simple structures in an efficient and consistent way to update the model with new information from measurements, monitoring and inspection results. The generic framework enables a holistic view of the current service life models. Corresponding sensitivity studies, finding optimal decisions for treating deteriorated reinforced concrete structures and temporal changes of structures can also be represented and analyzed within this framework.

Jürgen Hackl Written by:

Dr. Jürgen Hackl is an Assistant Professor at the University of Liverpool. His research interests lie in complex urban systems and span both computational modelling and network science.