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  5. Probabilistic-based structural assessment of a historic stone arch bridge

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Article
English
2020

Probabilistic-based structural assessment of a historic stone arch bridge

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English
2020
Structure and Infrastructure Engineering
Vol 17 (3)
DOI: 10.1080/15732479.2020.1752261

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Daniel V. Oliveira
Daniel V. Oliveira

Institution not specified

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Borja Conde
José C. Matos
Daniel V. Oliveira
+1 more

Abstract

A probabilistic analysis approach for reliability-based assessment of masonry arch bridges is presented in this work. The methodology is tested on a medieval in-service construction located in Galicia, northwest of Spain. To estimate its ultimate load-carrying capacity, two different numerical approaches are employed; a three-dimensional non-linear finite element model and a two-dimensional rigid blocks limit analysis model. Aiming to alleviate the computational burden associated with the probabilistic analysis procedure, a surrogate modelling strategy is adopted. A complete understanding of the influence of model input parameters on the limit load of the structure is attained through the employment of global variance-based sensitivity analysis. The reliability assessment procedure is subsequently carried out, allowing to estimate the bridge failure probability. A difference of approximately 33% is obtained between the reliability index values drawn from both structural modelling strategies, so revealing the key role played by transversal effects on the strength capacity of masonry arch bridges. The proposed probabilistic assessment framework might be deemed as a useful tool, from which more reliable and objective information about the actual safety condition of existing masonry arch bridges can be derived, taking advantage of readily available numerical tools, but still demanding an affordable computational effort.

How to cite this publication

Borja Conde, José C. Matos, Daniel V. Oliveira, B. Riveiro (2020). Probabilistic-based structural assessment of a historic stone arch bridge. Structure and Infrastructure Engineering, 17(3), pp. 379-391, DOI: 10.1080/15732479.2020.1752261.

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Publication Details

Type

Article

Year

2020

Authors

4

Datasets

0

Total Files

0

Language

English

Journal

Structure and Infrastructure Engineering

DOI

10.1080/15732479.2020.1752261

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