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Descripción
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| Using a multi-objective optimization algorithm avoid the use of weighting factors to balance the different residuals in a finite element model updating procedure under the maximum likelihood method. By using this approach, the fittest model is not unique and a set of solutions that form a curve, so-called Pareto optimal front, is obtained. Within this paper, first a review of the state of the art on the criteria used to determine the most adequate model among all the solutions of the Pareto front is presented. Subsequently, a case study of a real footbridge is considered. A finite element model of the footbridge is updated based on its experimental modal parameters. The Non-Dominated Sorting Genetic Algorithm is used to obtain the Pareto front. Since all the solutions in the Pareto front are non-dominated, the selection of the best candidate requires a reasonable criterion. Herein, different procedures to select the best updated model are discussed. | |
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Internacional
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Si |
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Nombre congreso
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IABSE Symposium 2019: Towards a Resilient Built Environment Risk and Asset Management |
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Tipo de participación
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960 |
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Lugar del congreso
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Guimaraes |
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Revisores
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Si |
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ISBN o ISSN
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978-3-85748-163-5 |
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DOI
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Fecha inicio congreso
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27/03/2019 |
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Fecha fin congreso
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29/03/2019 |
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Desde la página
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1 |
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Hasta la página
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8 |
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Título de las actas
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Proceedings of the IABSE Symposium 2019 |