2021
DOI: 10.1002/eqe.3467
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Dynamic calibration and seismic validation of numerical models of URM buildings through permanent monitoring data

Abstract: The construction of reliable numerical models is a key aspect within the seismic assessment of existing unreinforced masonry buildings. However, it is also a complex process due to the many uncertainties involved that can affect the structural response. In situ tests allow for the acquisition of data at a local scale. Nonetheless, supplementary information representing the global response is necessary to overcome other uncertainties (i.e., wall-to-wall connections or floor stiffness). To this end, data from am… Show more

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Cited by 23 publications
(25 citation statements)
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“…AVTs data were essential for refining the numerical models since they allowed to verify the assumptions made in the blind predictions and to address the most proper modelling choices in the validation phase. Moreover, such data represent a fundamental tool, especially for the calibration of models characterized by complex geometry or influenced by many modelling uncertainties (as discussed in Cattari et al 2021a;Brunelli et al 2021). This paper clearly shows the importance of having information from permanent monitoring systems, useful for an effective validation of the structural response in the linear and nonlinear range.…”
Section: Discussionmentioning
confidence: 92%
See 1 more Smart Citation
“…AVTs data were essential for refining the numerical models since they allowed to verify the assumptions made in the blind predictions and to address the most proper modelling choices in the validation phase. Moreover, such data represent a fundamental tool, especially for the calibration of models characterized by complex geometry or influenced by many modelling uncertainties (as discussed in Cattari et al 2021a;Brunelli et al 2021). This paper clearly shows the importance of having information from permanent monitoring systems, useful for an effective validation of the structural response in the linear and nonlinear range.…”
Section: Discussionmentioning
confidence: 92%
“…It is quite simple and computationally efficient particularly for nonlinear analyses. The reliability and effectiveness of this modelling strategy has been documented through numerical simulations of actual URM buildings damaged by earthquakes (Morandi et al 2019;Marino et al 2019;Cattari et al 2021a;Brunelli et al 2021).…”
Section: Introductionmentioning
confidence: 99%
“…It affects both the elastic field, since it alters the actual deformability of the wall due to the simplification of introducing rigid nodes, and the nonlinear phase of the response, since the regions where the cracks and nonlinearity are likely to develop are assumed a priori. Despite these simplifications, this approach is one of the most spread both in engineering practice and at the research level thanks to its computational efficiency in performing nonlinear analyses (e.g., in [48]) and its reasonable accuracy, as proven by various numerical simulations in the literature (e.g., in [49,50]). In the examined case, performing a complete model of the whole aggregate with other approaches, such as FEM, would have been almost unfeasible.…”
Section: Results Of Out-of-plane Seismic Assessmentmentioning
confidence: 99%
“…Apart from that, the setup of the EF model requires great care and accuracy in transferring as much information acquired during the knowledge phase as possible into the model (as discussed for example also in [27,50]). Some critical situations (Figure 7c,d) that may potentially reduce the strength and stiffness of structural elements (such as the presence of flues, recesses, infill openings, and non-continuous walls) were taken into account with specific expedients:…”
Section: Results Of Out-of-plane Seismic Assessmentmentioning
confidence: 99%
“…As the building under analysis had been monitored since 2010 by the Italian Structural Seismic Monitoring Network (the so-called, in Italian, Osservatorio Sismico delle Strutture [75]), it has been also thoroughly characterized under the point of view of dynamic identification. Based on available experimental data derived from on-site testing campaign and a dynamic monitoring system, a very comprehensive validation and calibration of adopted numerical models was possible by means of other software [76].…”
mentioning
confidence: 99%