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Reliability-Based Bayesian Updating Using Visual Inspections of Existing Bridges

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Proceedings of the 1st Conference of the European Association on Quality Control of Bridges and Structures (EUROSTRUCT 2021)

Abstract

Structural reliability has become a widely accepted performance indicator for infrastructures over the past decade, providing valuable information about their structural condition. As a result, it has been assessed in combination with deterioration prediction, aiming at defining optimal maintenance, and rehabilitation strategies for bridge networks. In that case, reliability values need to be updated based on collected data. To this purpose, there has been a rapid development of advanced bridge condition assessment techniques, both in the fields of structural health monitoring as well as on non-destructive assessment techniques. Most of the sophisticated non-destructive methods are the preferred option but sometimes are not possible. Thus, visual inspection is still the predominant bridge condition assessment technique being adopted within the majority of Bridge Management Systems (BMS). However, there is a procedural gap when incorporating information obtained from visual inspections into a reliability assessment. Therefore, this paper describes a methodology for a time-dependent reliability-based condition evaluation of existing bridges. The procedure is applied to a pre-stressed reinforced concrete railway bridge located in Portugal, in which prediction of reliability levels are calculated for different periods assuming corrosion initiation, causing a reduction in the cross-section area of the steel reinforcement and residual strength reduction, based on onsite inspection evidence. Finally, the updating is made through a Bayesian approach to compute the posterior bridge reliability based on inspection results. This approach may apply to other types of structures considering information obtained from visual inspection concerning the actual deterioration state in a quantitative way.

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Acknowledgments

This work was partly financed by FCT/MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Engineering Structures (ISISE), under reference UIDB/04029/2020. The first author would like to thank FCT – Portuguese Scientific Foundation for the research grant 2020.05755.BD. The second author would like to thank FCT – Portuguese Scientific Foundation for the research grant SFRH/BD/144749/2019.

This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 769255. This document reflects only the views of the author(s). Neither the Innovation and Networks Executive Agency (INEA) nor the European Commission is in any way responsible for any use that may be made of the information it contains.

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Correspondence to Erica Arango .

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Arango, E., Santamaria, M., Sousa, H.S., Matos, J.C. (2022). Reliability-Based Bayesian Updating Using Visual Inspections of Existing Bridges. In: Pellegrino, C., Faleschini, F., Zanini, M.A., Matos, J.C., Casas, J.R., Strauss, A. (eds) Proceedings of the 1st Conference of the European Association on Quality Control of Bridges and Structures. EUROSTRUCT 2021. Lecture Notes in Civil Engineering, vol 200. Springer, Cham. https://doi.org/10.1007/978-3-030-91877-4_19

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  • DOI: https://doi.org/10.1007/978-3-030-91877-4_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91876-7

  • Online ISBN: 978-3-030-91877-4

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