Microstructural heterogeneities and fatigue anisotropy of forged steels

MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

卷:529

Article

Pessard, Etienne¹  Morel, Franck¹  Verdu, Catherine²  Flaceliere, Laurent³  Baudry, Gilles³ 

[1] Arts & Metiers ParisTech Angers, LAMPA, F-49035 Angers 01, France

[2] Univ Lyon, INSA Lyon, MATEIS, F-69621 Villeurbanne, France

[3] CREAS ASCOMETAL, F-57301 Hagondange, France

关键词: Anisotropy;    Forged steel;    Manganese sulfide inclusions;    High cycle fatigue;    Self-heating;   

DOI  :  10.1016/j.msea.2011.09.031

来源: Elsevier

【 摘 要 】

In this study, various experimental methods are employed to determine the anisotropic fatigue behavior of a 25MnCrSiVB6 forged steel (Metasco MC). This material has a bainitic microstructure and contains many elongated non-metallic inclusions in the rolled direction, which are grouped into clusters. Specimens with different orientations relative to the rolling direction have been extracted from a hot rolled bar and the ability of certain experimental techniques to capture the fatigue anisotropy has been tested. Results obtained from monotonic tensile tests and Charpy impact tests show that the material has isotropic fracture strength and anisotropic ductility. The influence of the inclusion clusters is clearly demonstrated via observation of the fracture surfaces. Concerning the fatigue behavior, results from a classical staircase experimental procedure are compared to results from self-heating fatigue tests. For specimens orientated at 0 degrees relative to the rolled direction, microcrack initiation is controlled by the material matrix and the prediction of the fatigue strength with the self-heating method has been observed to be correct. For specimens orientated at 45 degrees and 90 degrees, the elongated manganese sulfide inclusion clusters are the origin of crack initiation and the fatigue strength drops significantly. For this case, it appears that the self-heating method has difficulty predicting the fatigue behavior. (C) 2011 Elsevier B.V. All rights reserved.

【 授权许可】

Free