An inverse parallel genetic algorithm for the identification of skin/core debonding in honeycomb aluminium panels
Author
dc.contributor.author
Meruane Naranjo, Viviana
Author
dc.contributor.author
Fierro, V. del
Admission date
dc.date.accessioned
2015-12-23T01:13:40Z
Available date
dc.date.available
2015-12-23T01:13:40Z
Publication date
dc.date.issued
2015
Cita de ítem
dc.identifier.citation
Struct. Control Health Monit. 2015; 22:1426–1439
en_US
Identifier
dc.identifier.issn
1545-2255
Identifier
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DOI: 10.1002/stc.1756
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/135911
General note
dc.description
Artículo de publicación ISI
en_US
Abstract
dc.description.abstract
Honeycomb sandwich structures are used in a wide variety of applications. Nevertheless, because of manufacturing defects or impact loads, these structures can experience imperfect bonding or debonding between the skin and the honeycomb core. Instances of debonding reduce the bending stiffness of the composite panel, which causes detectable changes in its vibration characteristics. This article presents a new methodology to identify debonded regions in aluminium honeycomb panels that uses an inverse algorithm based on parallel genetic algorithms. The honeycomb panels are modelled with finite elements using a simplified three-layer shell model. The adhesive layer between the skin and core is modelled using linear springs, with reduced rigidity for the debonded sectors. The algorithm is validated using experimental data from an aluminium honeycomb panel containing different damage scenarios. Copyright (c) 2015 John Wiley & Sons, Ltd.