Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/45444

TítuloPrediction of the load carrying capacity of elevated steel fibre reinforced concrete slabs
Autor(es)Salehian, Hamidreza
Barros, Joaquim A. O.
Palavras-chaveElevated slabs
Steel fibre reinforced concrete
Load carrying capacity
Yield line theory
Fibre distribution
Data2017
EditoraElsevier 1
RevistaComposite Structures
Resumo(s)A novel methodology is developed for predicting the load carrying capacity of elevated steel fibre reinforced concrete (E-SFRC) slab systems. In the proposed approach the depth of slab’s cross section is discretized into several layers, and the number of steel fibres per each layer is determined by considering the distribution of fibres along the depth of cross section. This information, together with the one obtained from the threepoint notched beam bending tests performed on four series of SFRC made of different concrete strength class and content of fibres, have provided the stress-crack width laws for defining the post-cracking behaviour of each layer. These constitutive laws are implemented in a numerical model developed based on the moment-rotation approach for determining the positive and negative resisting bending moment of the slab’s unit width cross section. By using the yield line theory, the load carrying capacity of ESFRC slab is predicted for the most current load conditions. Predictive performance of the proposed methodology is assessed comparing to the results recorded in experiment and the ones obtained by the numerical simulation. Finally the developed model is utilised in a parametric study to evaluate the influence of parameters that affect the load-carrying capacity of E-SFRC slabs.
TipoArtigo
URIhttps://hdl.handle.net/1822/45444
DOI10.1016/j.compstruct.2017.03.002
ISSN0263-8223
e-ISSN1879-1085
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:ISISE - Artigos em Revistas Internacionais

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
IJ(ISI)_149.pdf1,82 MBAdobe PDFVer/Abrir

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID