4.7 Article

Progressive pseudograin damage accumulation model for short fiber-reinforced plastics and its application to fatigue life prediction

Journal

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.compositesa.2023.107871

Keywords

Short fiber-reinforced plastics; Two-step homogenization; Progressive pseudograin damage accumulation; Fatigue life prediction

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A progressive pseudograin damage accumulation (PPDA) model is proposed to predict the fatigue life of short fiber-reinforced plastics (SFRPs). The model combines the viscoelastic-viscoplastic (VEVP) two-step homogenization theory and Chaboche fatigue damage model. Each representative volume element (RVE) of SFRPs is decomposed into pseudograins, and the fatigue life of each pseudograin is predicted using a master S-N curve. The overall failure of RVE is predicted by a PPDA model, which takes into account the stress concentration of the living pseudograins and results in non-linear fatigue damage evolution. The PPDA model is implemented into ABAQUS, and the predicted fatigue lifetime agrees well with experimental data.
A progressive pseudograin damage accumulation (PPDA) model is proposed to predict the fatigue life of short fiber-reinforced plastics (SFRPs), combining viscoelastic-viscoplastic (VEVP) two-step homogenization theory with Chaboche fatigue damage model. Each representative volume element (RVE) of SFRPs is decomposed into pseudograins using a two-step homogenization framework. Then, the fatigue life of each pseudograin is predicted using a master S-N curve, which is prepared based on the normalized fatigue factor taking into account both the stress ratio and multiaxial stress state. Thereafter, the overall failure of RVE is predicted by a PPDA model, in which each pseudograin fails progressively considering the stress concentration of the living pseudograins, resulting in non-linear fatigue damage evolution. Finally, the PPDA model is successfully implemented into ABAQUS user material subroutine (UMAT), predicting the fatigue lifetime in good agreement with experimental data.

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