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  1. Pubblicazioni

Intuitionistic fuzzy divergence for evaluating the mechanical stress state of steel plates subject to bi-axial loads

Articolo
Data di Pubblicazione:
2024
Citazione:
Intuitionistic fuzzy divergence for evaluating the mechanical stress state of steel plates subject to bi-axial loads / Versaci, M., | Angiulli, G., La Foresta, F., Laganà, F., | Palumbo, A.. - In: INTEGRATED COMPUTER-AIDED ENGINEERING. - ISSN 1069-2509. - 31:4(2024), pp. 363-379. [10.3233/ICA-230730]
Abstract:
The uncertainty that characterizes the external mechanical loads to which any connection plate in steel structures is subjected determines the non-uniqueness of the isochoric deformation distributions. Since the eddy currents induced on the plates produce magnetic field maps with a high fuzziness content, similar to those of the isochoric deformations, their use can be exploited to evaluate the extent of the external load that determines a specific induced current map. Starting from an approach known in the literature, according to which the map-external load association is operated through fuzzy similarity computations, in this paper, we generalize this method by reformulating it in terms of intuitionistic fuzzy logic by proposing a classification based on divergence computations. Our approach, acting adaptively on the fuzzification of the maps, results in a better classification percentage, besides significantly reducing the presence of doubtful cases due to the uncertainty of each applied load. Furthermore, a FEM software tool was developed, which turned out to be, to a certain extent, a substitute for the experimental procedure, notoriously more expensive. Even if the procedure was applied on plates subjected to bi-axial loads, it could be used for other types of loads since the classification operator processes the eddy current maps exclusively, regardless of their cause.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Versaci, Mario; | Angiulli, Giovanni; La Foresta, Fabio; Laganà, Filippo; | Palumbo, Annunziata
Autori di Ateneo:
ANGIULLI Giovanni
LA FORESTA Fabio
VERSACI Mario
Link alla scheda completa:
https://iris.unirc.it/handle/20.500.12318/142191
Pubblicato in:
INTEGRATED COMPUTER-AIDED ENGINEERING
Journal
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URL

https://content.iospress.com/articles/integrated-computer-aided-engineering/ica230730
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