Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/81031

TítuloLateral capacity of URM walls: a parametric study using macro and micro limit analysis predictions
Autor(es)Szabó, Simon
Funari, Marco Francesco
Pulatsu, Bora
Lourenço, Paulo B.
Palavras-chaveBond patterns
Limit analysis
Parameter influence
In-plane masonry wall
Data26-Out-2022
EditoraMultidisciplinary Digital Publishing Institute
RevistaApplied Sciences
CitaçãoSzabó, S.; Funari, M.F.; Pulatsu, B.; Lourenço, P.B. Lateral Capacity of URM Walls: A Parametric Study Using Macro and Micro Limit Analysis Predictions. Appl. Sci. 2022, 12, 10834. https://doi.org/10.3390/app122110834
Resumo(s)This research investigates the texture influence of masonry walls’ lateral capacity by comparing analytical predictions performed via macro and micro limit analysis. In particular, the effect of regular and quasi-periodic bond types, namely Running, Flemish, and English, is investigated. A full factorial dataset involving 81 combinations is generated by varying geometrical (panel and block aspect ratio, bond type) and mechanical (friction coefficient) parameters. Analysis of variance (ANOVA) approach is used to investigate one-way and two-way factor interactions for each parameter in order to assess how it affects the horizontal load multiplier. Macro and micro limit analysis predictions are compared, and the differences in terms of mass-proportional horizontal load multiplier and failure mechanism are critically discussed. Macro and micro limit analysis provide close results, demonstrating the reliability of such approaches. Furthermore, results underline how the panel and block aspect ratio had the most significant effect on both the mean values and scatter of results, while no significant effect could be attributed to the bond types.
TipoArtigo
URIhttps://hdl.handle.net/1822/81031
DOI10.3390/app122110834
e-ISSN2076-3417
Versão da editorahttps://www.mdpi.com/2076-3417/12/21/10834
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:BUM - MDPI

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Este trabalho está licenciado sob uma Licença Creative Commons Creative Commons

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