Assessing and updating the reliability of concrete bridges subjected to spatial deterioration – principles and software implementation

Abstract

Inspection and maintenance of concrete bridges is a major cost factor in transportation infrastructure IntroductionDeterioration processes can reduce the reliability and the safety of engineering structures. Knowledge of the actual condition of the structure is therefore essential in order to comply with element and system target reliabilities (see [1][2][3]). Inspections and structural health monitoring are effective means of acquiring information on the actual condition of an ageing structure and should be utilized to reduce the uncertainty in engineering models and, ultimately, to optimize the management of deteriorating structures. This task is ideally carried out through a Bayesian analysis approach [4][5][6][7][8].As most deterioration processes are spatially distributed in structures and the deterioration progress at different locations in a structure is correlated, such an analysis should be performed considering the structure as a whole (e.g. [9][10][11][12]). However, the integral assessment of spatially distributed deterioration is computationally demanding, and novel computational strategies are required for probabilistic assessment and Bayesian updating of spatial deterioration [13,14]. Ultimately, the modelling approach and the computational methods should lead to software that can be used by engineers who are not experts in reliability analyses. Only in this way can Bayesian methods enhance the integrity management of ageing structures in practice.This paper describes an approach in which the uncertain system deterioration state of an ageing concrete structure is described by a Dynamic Bayesian Network (DBN) model of the underlying stochastic deterioration processes. This approach was motivated by the work of Straub [15] and Qin and Faber [16]. DBN models provide a computational framework that enables the evaluation of the joint distribution function of the system deterioration state based on the prior stochastic model and, in particular, Bayesian updating of the joint distribution function of the system deterioration state with observations of the underlying deterioration process, i.e. inspection and monitoring results.To prove the concept, the approach is implemented in a software prototype employing a DBN model of chloride-induced reinforcement corrosion, which can approximate the spatial correlation of the corrosion process. The prototype is applied to assess and update the deterioration state and structural reliability of a single-cell prestressed concrete box girder. This construction type is typical of long, multi-span highway bridges in Germany. However, the general solution strategy applies to all common concrete bridge structures.Section 2 gives an overview of the underlying system model. The deterioration model and the structural capacity model are described in more detail in sections 3 and 4. The implementation of the prototype is briefly described in section 5. A case study applying the prototype is summarized in section 6. System modelTo model the deterioration state, the box girder i...

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