Stochastic Multiphasic Multivariate State-Based Degradation and Maintenance Meta-Models for RC Structures Subject to Chloride Ingress

The objective of this paper is to propose tools for the lifecycle management of infrastructure by showing the slow degradation processes for which inspection data are accessible, especially the data obtained from non-destructive testing (NDT) and structural health monitoring (SHM). One major characteristic of these degradation processes is their multiphasic nature; consequently, they can be discretised into different phases with specific physical kinematics where specific maintenance actions and measurement techniques can be performed. Within this framework, we propose implementing a degradation meta-modelling approach fed with measurements (NDT, SHM). This approach is based on state-dependent stochastic processes for modelling the degradation and maintenance of reinforced concrete structures that are subjected to chloride-induced deterioration. The benefit of using multiphasic degradation meta-models in the lifecycle management of infrastructure is illustrated through numerical examples that include single and multi-action management policies.

Automated summary

The objective of this paper is to propose tools for infrastructure lifecycle management by showing the degradation processes and utilizing inspection data, specifically non-destructive testing (NDT) and structural health monitoring (SHM). These processes are multiphasic and can be divided into different phases with specific maintenance actions and measurement techniques. The proposed degradation meta-modelling approach, based on state-dependent stochastic processes, is used to model the degradation and maintenance of reinforced concrete structures affected by chloride-induced deterioration. The benefits of using multiphasic degradation meta-models in infrastructure lifecycle management are demonstrated through numerical examples with different management policies.