Descripción
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The finite element model (FE) updating is a calibration method that allows minimizing the discrepancies between the numerical and experimental modal parameters. As result, a more accurate FE model is obtained and the structural analysis can represent the real behaviour of the structure. However, it is a high computational cost process. To overcome this issue, alternative techniques have been developed. This study focuses on the use of the unscented Kalman filter (UKF), which is a local optimization algorithm based on statistical estimation of parameters taken into account the measurements. The dome of a real chapel is considered as benchmark structure. A FE model is updated applying two different algorithms: (i) the multi-objective genetic algorithm and (ii) a hybrid unscented Kalman filter-multi-objective genetic algorithm (UKF-MGA). Finally, a discussion of the results will be presented to compare the performance of both algorithms. | |
Internacional
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Si |
Nombre congreso
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IABSE Symposium 2019: Towards a Resilient Built Environment Risk and Asset Management |
Tipo de participación
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960 |
Lugar del congreso
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Guimaraes |
Revisores
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Si |
ISBN o ISSN
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978-3-85748-163-5 |
DOI
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Fecha inicio congreso
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27/03/2019 |
Fecha fin congreso
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29/03/2019 |
Desde la página
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1 |
Hasta la página
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8 |
Título de las actas
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Proceedings of the IABSE Symposium 2019 |