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International audience; This article is within the context of decision models aimed for maintenance of structures and infrastructures in civil engineering. The contribution relies on the construction of a degradation model oriented toward risk analysis. The proposed model can be defined as a meta-model in the sense that it is based on observations while incorporating key features from the degradation process necessary for the maintenance decision. We propose to stimulate the construction of the degradation model based on the crack propagation of a submerged reinforced concrete structure subject to chloride-induced corrosion. Furthermore, a set of numerical illustrations is performed to demonstrate the advantages and applicability of the proposed approach in risk management and maintenance contexts.

Physics-based models are intensively studied in mechanical and civil engineering but their constant increase in complexity makes them harder to use in a maintenance context, especially when degradation model can/should be updated from new inspection data. On the other hand, Markovian cumulative damage approaches such as Gamma processes seem promising; however, they suffer from lack of acceptability by the civil engineering community due to poor physics considerations. In this article, we want to promote an approach for modeling the degradation of structures and infrastructures for maintenance purposes which can be seen as an intermediate approach between physical models and probabilistic models. A new statistical, data-driven state-dependent model is proposed. The construction of the degradation model will be discussed within an application to the cracking of concrete due to chloride-induced corrosion. Numerical experiments will later be conducted to identify preliminary properties of the model in terms of statistical inferences. An estimation algorithm is proposed to estimate the parameters of the model in cases where databases suffer from irregularities.