A comparison between S-N Logistic and Kohout-Vechet formulations applied to the fatigue data of old metallic bridges materials

• Type: Article in International Scientific Journal
• Date: 2019

Authors

Joelton Fonseca Barbosa (Author) Other; José A.F.O. Correia (Author) FEUP; Pedro A. Montenegro (Author) Other; Raimundo Carlos Silverio Freire Júnior (Author) Other; Grzegorz Lesiuk (Author) Other; Abílio M. P. de Jesus (Author) FEUP; Rui A. B. Calçada (Author) Other

Journal

Title: Frattura ed Integrita Strutturale

Vol. 13 No. 48

Pages: 400-410

ISSN: 1971-8993

Publisher: Gruppo Italiano Frattura

Indexing

ISI Web of Knowledge - 17 Citations

Scopus - 16 Citations

Other information

Authenticus ID: P-00Q-F9D

DOI: 10.3221/igf-esis.48.38

Abstract (EN): A new formulation of a Logistic deterministic S-N curve is applied to fatigue data of metallic materials from ancient Portuguese riveted steel bridges. This formulation is based on a modified logistic relation that uses three parameters to fit the low-cycle-(LCF), finite-life-and high-cycle-fatigue (HCF) regions. This model is compared to the Kohout-Vechet fatigue model, which has a refined adjustment from very low-cycle fatigue (VLCF) to very high-cycle fatigue (VHCF). These models are also compared with other models, such as, power law and fatigue-life curve from the ASTM E739 standard. The modelling performance of the S-N curves was made using the fatigue data considering the stress fatigue damage parameter for the materials from the Eiffel, Luiz I, Fao and Trezoi riveted steel bridges. Using a qualitative methodology of graphical adjustment analysis and another quantitative using the mean square error, it was possible to evaluate the performance of the mean S-N curve formulation. The results showed that the formulation of the S-N curve using the Logistic equation applied to the metallic materials from the old bridges resulted in a superior performance when compared with others models under consideration, both in the estimation of fatigue behaviour in the low-cycle fatigue (LCF) region and in the lowest mean square error.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11