2016
DOI: 10.1108/aeat-02-2015-0064
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Model updating of finite element model using optimisation routine

Abstract: Purpose The present paper aims to describe the model updating of a small aircraft dynamic finite element model (FEM) to improve its agreement with ground vibration test (GVT) data. Design/methodology/approach An automatic updating method using an optimization procedure is carried out. Instead of using dedicated updating tools, the procedure is implemented using standard MSC/NASTRAN because of wide availability of the software in small aircraft industries. The objective function is defined to minimize the dif… Show more

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Cited by 6 publications
(3 citation statements)
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References 6 publications
(9 reference statements)
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“…Concerning the formulation of the optimization problem we choose to use the MAC value to represent the closeness between two vibration modes. The methodology that we present is close to the one described by Prananta et al [18] and Gupta et al [19], which they used to update finite element models to match experimental data. As described by Allemang [20], if {φ ri } is one of the reference eigenvectors, and {φ mj } is one of the eigenvectors from the current model, we define a matrix whose elements are…”
Section: Definition Of the Optimization Problem For Modal Similaritymentioning
confidence: 65%
“…Concerning the formulation of the optimization problem we choose to use the MAC value to represent the closeness between two vibration modes. The methodology that we present is close to the one described by Prananta et al [18] and Gupta et al [19], which they used to update finite element models to match experimental data. As described by Allemang [20], if {φ ri } is one of the reference eigenvectors, and {φ mj } is one of the eigenvectors from the current model, we define a matrix whose elements are…”
Section: Definition Of the Optimization Problem For Modal Similaritymentioning
confidence: 65%
“…Algumas alternativas podem ser para seleção de parâmetros. O agrupamento dos parâmetros disponíveis, utilizado por Prananta et al (2016), conseguiu diminuir de 800 parâmetros a serem atualizados para 40 variáveis, mantendo a melhoria do método. A diminuição do tempo de processamento se torna ainda mais válida quando se pretende testar estratégias de otimização em mais de uma análise.…”
Section: Métodos De Atualizaçãounclassified
“…This is at the core of the updating method herein employed. The modeling errors causing low correlation can be filled by the implementation of an optimization problem aiming at finding the model parameters values to minimize the numerical vs. experimental errors [28][29][30].…”
Section: Model Updating Strategymentioning
confidence: 99%