A carregar...
Publicação
Seismic performance-based assessment of urban cultural heritage assets through different macroelement approaches
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 2.92 MB | Adobe PDF |
Orientador(es)
Resumo(s)
This paper aims at providing an insightful comparison between three of the most widely used commercially available macroelement models for assessing the global seismic performance of existing masonry structures: the equivalent frame model of 3Muri®, and the two- and three-dimensional discrete macroelements available in 3D-Macro®. To this aim, a stone masonry building, representative of the Urban Cultural Heritage (UCH) typology of the Azores archipelago (in Portugal), was considered as a case study. Firstly, sensitivity analyses were performed to investigate the impact of a few modelling aspects on the seismic performance of the case study building, and ultimately to define the reference model. Secondly, this reference model was analysed both linearly and nonlinearly. Finally, the seismic performance was evaluated by applying the N2 Method.
With this comparative study, the authors aim at discussing, from the user viewpoint, the features that these software codes and corresponding macroelement models have in common and those where they most diverge, as well as their main advantages and drawbacks. Results demonstrate that these models should be applied to UCH assets with due diligence, bearing in mind both the particularities of the case study as well as features and limitations associated with the chosen modelling strategy and software.
Descrição
Palavras-chave
UCH assets Macroelement models Modal analysis Pushover analyses Seismic performance-based assessment
Contexto Educativo
Citação
Maio, Rui; Ferreira, Tiago M.; Estêvão, João M.C.; Pantò, Bartolomeo; Caliò, Ivo; Vicente, Romeu. 2020. "Seismic performance-based assessment of urban cultural heritage assets through different macroelement approaches". Journal of Building Engineering 29: 101083. doi: 10.1016/j.jobe.2019.101083.
Editora
Elsevier