Probabilistic flexural fatigue strength of ultra-lightweight cement concrete and high strength lightweight aggregate concrete

• Tipo: Artigo em Revista Científica Internacional
• Data: 2022

Autores

Zhang, YY (Autor) Outra; Sun, Q (Autor) Outra; Xin, HH (Autor) Outra; Liu, YQ (Autor) Outra; Correia, JAFO (Autor) FEUP; Berto, F (Autor) Outra

Revista

Título: International Journal of Fatigue

Vol. 158

ISSN: 0142-1123

Editora: Elsevier

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00W-1KY

DOI: 10.1016/j.ijfatigue.2022.106743

Abstract (EN): Recently, more attention has been paid to the development of lightweight aggregate concrete due to its many advantages, such as low density, good thermal insulation, and fire resistance. The fatigue performance of ultra lightweight cement composite (ULCC) and lightweight aggregate concrete (LWAC) with comparable compressive and flexural strength was investigated and compared in this paper. The data of three-point flexural fatigue loading experiments were collected from the literature for 108 specimens sized as 100 mm x 76 mm x 406 mm. The least-squares regression (LR) and the orthogonal regression (OR) methods were adopted and compared to fit the experimental coefficients of the Wo & BULL;hler equations. Two-and three-parameter Weibull distribution models were used and compared when evaluating the probabilistic fatigue life of ULCC and LWAC at given stress levels. Analysis results show that the coefficients of the Wohler equations fitted by LR and OR methods in this study are similar. For stress levels in the middle ranges, namely, approximate 0.65-0.8, the differences of the S-N curves by two and three-parameter models are slight. When stress levels are larger than 0.8 or smaller than 0.65, significant differences exist between curves fitted by the two models. The nonlinear curves obtained from the three parameter model are deemed more consistent with the actual situation than the linear curves by the two parameter model.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10