Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/68315

TítuloA micro-modeling approach for the prediction of TRM bond performance on curved masonry substrates
Autor(es)Scacco, J.
Milani, G.
Lourenço, Paulo B.
Palavras-chaveCurved elements
Masonry
Non-linear analysis
TRM bond
Data2021
EditoraElsevier 1
RevistaComposite Structures
Resumo(s)Retrofitting of arches, vaults and domes is needed for vulnerability mitigation of historical structures. Lately, the external application of composite materials embedded within an inorganic matrix addressed the compatibility issues related to FRP applications. Great efforts have been made for a correct identification of tensile and bond properties of TRM reinforcement, but scarce data are available for understanding the effect of curvature in debonding. This paper provides a numerical approach that enables to predict the reinforcement performance on curved masonry elements, when the same is designed without having specific single lap shear tests for the adopted materials. Such an approach relies on a separate modeling of each constituent material of the reinforcement and the substrate: matrix, fibers and the interface between them, and bricks and mortar joints. The FE-based software Abaqus is used for the simulations, addressing the non-linear material properties by means of the CDP constitutive model. In order to calibrate and validate the proposed numerical approach, experimental data are used and through a comparison of the load–displacement curves obtained the capabilities of the method are discussed. Finally, an extension of such approach to curvatures not experimentally tested is presented, opening the way to future applications of the approach.
TipoArtigo
URIhttps://hdl.handle.net/1822/68315
DOI10.1016/j.compstruct.2020.113065
ISSN0263-8223
Versão da editorahttps://www.sciencedirect.com/science/article/pii/S0263822320329913
Arbitragem científicayes
AcessoAcesso restrito UMinho
Aparece nas coleções:ISISE - Artigos em Revistas Internacionais

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