Fatigue life prediction of aluminum alloy 6061 based on defects analysis

Mesoscopic physics Bridge (graph theory) Macro Paris' law
DOI: 10.1016/j.ijfatigue.2021.106189 Publication Date: 2021-02-23T05:36:08Z
ABSTRACT
Abstract Fatigue life prediction through defects is a challenging work. An approach to predict fatigue life based on defects information was proposed. Defects simplification and classification method was proposed based on damage data obtained by X-ray CT. Stress concentration factors was introduced as intermediate variable for virtual 3D reconstruction model of internal defects. A prediction model of relationship between defects and fatigue life was established by Support Vector Regression. It is shown that the proposed prediction model can built an accurate bridge between mesoscopic damage and macroscopic fracture by simple macro variables based on comprehensive defects information.
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