2016
DOI: 10.1016/j.engstruct.2016.05.044
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Calibration of the numerical model of a stone masonry railway bridge based on experimentally identified modal parameters

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Cited by 70 publications
(29 citation statements)
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“…A numerical model of the masonry arch railway bridge was calibrated using dynamic modal parameters estimated from ambient vibration [34]. The problem of flood-induced scour on masonry arch bridges was also investigated using nonlinear three-dimensional modelling [29,35].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…A numerical model of the masonry arch railway bridge was calibrated using dynamic modal parameters estimated from ambient vibration [34]. The problem of flood-induced scour on masonry arch bridges was also investigated using nonlinear three-dimensional modelling [29,35].…”
Section: Introductionmentioning
confidence: 99%
“…To determine the actual properties of masonry arch bridge components, it is necessary to conduct the appropriate test procedure. Non-destructive, minor-destructive, and monitoring methods are used to assess masonry arch bridges [22,34,44]. A new assessment method to identify the historic masonry arch bridges was also proposed [45].…”
Section: Introductionmentioning
confidence: 99%
“…Finally, the experimental results were compared with those obtained with the computational model. Costa et al [4] calibrated a numerical model of a railroad bridge, using modal parameters estimated through an ambient vibration test. Suleyman [5] developed an algorithm to automate the dynamic identification of structures using the stochastic subspace identification (SSI) method.…”
Section: Introductionmentioning
confidence: 99%
“…With this need in mind, in recent years, different calculation methods and guidelines (e.g., UIC guideline) 1 for the evaluation of the ultimate (ULS) and serviceability limit states (SLS) of masonry bridges have been developed. Among the available methods for the structural analysis of masonry bridges, it is possible to find: simplified methods (Zhang et al, 2018), numerical method for assess the seismic capacity (Pelà et al, 2013;Zampieri et al, 2014Zampieri et al, , 2015aSarhosis et al, 2016;Mahmoudi Moazam et al, 2018;Marefat et al, 2019), methods based on the limit analysis (Basilio et al, 2014;Chiozzi et al, 2017;Bertolesi et al, 2018), analysis strategies able to take into account the settlement of the supports (Galassi et al, 2018a,b;Zampieri et al, 2018aZampieri et al, ,b, 2019 or geometry uncertainties (Cavalagli et al, 2017), macro-element models (Cannizzaro et al, 2018;D'Altri et al, 2019), and methods based on finite element modeling (FEM) (Brencich and Sabia, 2008;Costa et al, 2016;Scozzese et al, 2019), discrete element modeling (DEM) (Sarhosis et al, 2016(Sarhosis et al, , 2019Forgács et al, 2017Forgács et al, , 2018Stockdale et al, 2019) or a combination of both (Milani and Lourenço, 2012).…”
Section: Introductionmentioning
confidence: 99%