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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Updating of a Nonlinear Finite Element Model Using Discrete-Time Volterra Series

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Author(s):
Bussetta, Philippe ; Shiki, Sidney Bruce ; da Silva, Samuel
Total Authors: 3
Document type: Journal article
Source: LATIN AMERICAN JOURNAL OF SOLIDS AND STRUCTURES; v. 14, n. 7, p. 1183-1199, 2017.
Web of Science Citations: 3
Abstract

Abstract In this study, the discrete-time Volterra series are used to update parameters in a nonlinear finite element model. The main idea of the Volterra series is to describe the discrete-time output of a nonlinear system using multidimensional convolutions between the Volterra kernels represented in a Kautz orthogonal basis and the excitations. A metric based on the residue between the experimental and the numerical Volterra kernels is used to identify the parameters of the numerical model. First, the identification of the linear parameters is performed using a metric based only on the first order Volterra kernels. Then the nonlinear parameters are identified through a metric based on the higher-order kernels. The originality of this nonlinear updating method stems from the decoupling of linear and nonlinear parameters and the use of global nonlinear model. In order to put in light the applicability of this technique, this work focus on the identification of the parameters in a nonlinear finite element model of a beam that was preloaded by compression mechanism. This work shows that the updated numerical model was able to represent the behaviour observed in the experimental measurements. (AU)

FAPESP's process: 13/25148-0 - Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems
Grantee:Sidney Bruce Shiki
Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
FAPESP's process: 12/09135-3 - Structural health monitoring in nonlinear mechanical systems through Volterra models
Grantee:Samuel da Silva
Support Opportunities: Research Grants - Young Investigators Grants