Fatigue Life Prediction of Aluminum Alloys Based on Surface and Internal Defects

Fatigue of engineering materials is caused by the gradual degradation of materials under cyclic loading, from the evolution of internal and surface defects. It is quite necessary to combine internal and surface defects together in fatigue life prediction for materials. In this paper, an integrated method was proposed to predict fatigue life based on internal and surface defects. Based on five-stage damage testing, internal defects were obtained by x-ray CT and reconstructed. A simplified internal defects classification method is proposed. Surface defects were observed by microscope, then extracted by MATLAB, and reconstructed in SolidWorks. Then, an integrated defect model combining both internal and surface defects was proposed by using Python script to ABAQUS software. The model was verified by experiments. Finally, a regression fatigue life prediction method was obtained by combining surface roughness and stress concentration coefficient. It is shown that the proposed integrated defect model can achieve life prediction effectively.