Título
An analytical approach to calculate stress concentration factors of machined surfacesAutor-a
Versión
Postprint
Derechos
© 2020 Elsevier Ltd.Acceso
Acceso embargadoVersión del editor
https://doi.org/10.1016/j.ijmecsci.2020.106040Publicado en
International Journal of Mechanical Sciences Vol. 190. N. artículo 106040, 2021Editor
Elsevier Ltd.Palabras clave
Surface topographyStress concentration factor
Fatigue
Modelling
Resumen
Machining operations affect the properties of the final surface layer, and these can impact on its functional per- formance, particularly on fatigue behaviour. Among the properties of the machined sur ... [+]
Machining operations affect the properties of the final surface layer, and these can impact on its functional per- formance, particularly on fatigue behaviour. Among the properties of the machined surface, surface topography is one major parameter affecting fatigue behaviour. The literature review has demonstrated that stress concen- tration factors K t of the surface provide a more reliable estimation of the impact on the fatigue behaviour of machined components. Finite Element (FE) simulations can accurately calculate the stress concentration factor of machined surfaces, but they incur a high computational cost. Recent advances have shown that analytical models can reliably determine stress concentration factors of 2D roughness profiles. However, analytical models that predict stress concentration factors of 3D surface topographies are still lacking. This paper is aimed at devel- oping an analytical method to calculate the stress concentration factor K t of 3D surfaces generated by machining operations. To validate the model, a specimen of 7475-T7351 aluminium alloy was face milled and its surface topography was characterised using an Alicona IFG4 profilometer. Stress concentration factors were calculated in the selected surface regions using the proposed analytical model, and later compared to results obtained by FE simulations. The mean difference in the stress concentration factor K t calculated by the proposed analytical and FE models is of 1.53%. Importantly, the developed analytical model reduces the computing time by 3000 times compared to FE models, and enables the analysis of larger surfaces. [-]
Sponsorship
Gobierno VascoID Proyecto
GV/Elkartek 2019/KK-2019-00077/CAPV/Superficies multifuncionales en la frontera del conocimiento/FRONTIERS VColecciones
- Artículos - Ingeniería [684]