A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription.For more information, please contact eprints@nottingham.ac.uk This article presents a case study involving the assessment of an existing bridge, starting with simple methods and ending with a probabilistic analysis, the latter emphasizing Bayesian methods. When assessing an existing bridge, it is common practice to collect information from the bridge in the form of samples. These samples are in general of small size, raising the question of how the corresponding statistical uncertainty can be taken into account on reliability estimates. The case study illustrates how Bayesian methods are especially suitable to deal with that source of uncertainty. Another strong point of the Bayesian methods is their ability to combine the information contained in the samples collected from the bridge with prior information, if any. This aspect will also be illustrated through the case study.November 29, 2014 1:41 Structure and Infrastructure Engineering jacinto14 Structure and Infrastructure Engineering, Vol. 00, No. 00, Month 200x, 1-

This study focus on the probabilistic modelling of mechanical properties of prestressing strands based on data collected from tensile tests carried out in Laboratório Nacional de Engenharia Civil (LNEC), Portugal, for certification purposes, and covers a period of about 9 years of production. The strands studied were produced by 6 manufacturers from 4 countries, namely Portugal, Spain, Italy and Thailand. Variability of the most important mechanical properties is examined and the results are compared with the recommendations of the Probabilistic Model Code, as well as the Eurocodes and earlier studies. The obtained results show a very low variability which, of course, benefits structural safety. Based on those results, probabilistic models for the most important mechanical properties of prestressing strands are proposed.

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This article aims to present a procedure to take into account the variability of the time‐dependent behavior of concrete on its structural effects, evaluated from the study of creep and shrinkage based on experimental data obtained on‐site. For this purpose, the São João Bridge, a railway bridge built in Porto, Portugal in 1991, is presented as a case study. São João Bridge is a railway bridge crossing the river Douro. It is a prestressed concrete structure, with a total length of 1,028 m, including the main span of 250 m, two side spans of 125 m, six approaching spans on the left river bank, and three approaching spans on the right river bank (Porto). During bridge construction, a comprehensive structural health monitoring (SHM) system was set up, as well as an on‐site study of time‐dependent behavior of concrete. This study was based on creep 15 specimens and 15 shrinkage specimens, prepared simultaneously with some segments of the deck, using the same material, and it was kept running during almost 20 years. The results of this study were treated statistically and used as random variables in a probabilistic analysis of the time‐dependent behavior of the bridge. After a brief description of the mentioned on‐site study and the bridge SHM system, the paper presents the procedure followed on the bridge numerical probabilistic analysis. Finally, the values computed by the numerical model are presented and compared with the experimental values provided by the SHM.

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