4.7 Article

3D progressive damage modeling of fiber reinforced plastics laminates including drilling-induced damage

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ELSEVIER SCI LTD
DOI: 10.1016/j.compositesa.2022.107230

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Process simulation; Damage mechanics; Strength; Delamination; Fracture; Drilling

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This work develops a 3D progressive damage model to predict drilling-induced damage and its effect on the load-carrying capacity of fiber reinforced plastics laminates. The model is validated and applied to simulate drilling and its induced damage, showing good agreement with experimental data.
This work focuses on developing a 3D progressive damage model (PDM) to predict drilling-induced damage and its effect on the load-carrying capacity of fiber reinforced plastics (FRP) laminates. The proposed PDM is based on 3D Hashin's failure criterion and a linear damage evolution law. It was implemented as a VUMAT subroutine in an Abaqus/explicitTM. Specifically, the model allows defining pre-existing damage through state-dependent variables. The PDM was first validated with a single element, mesh dependency, and open hole tension tests. Subsequently, it was applied to model drilling and drilling-induced damage. Single element tests verify primary damages. Further, open hole lamina in tension fails with matrix cracking along the fiber direction irrespective of their fiber orientation. Furthermore, in open hole [45/-45/90/45/0/-45/0/45/-45/0]S laminate in tension, 0 degrees plies fail with fiber damage, whereas other plies fail with matrix damage. In drilling of a carbon fiber reinforced plastics (CFRP) laminate, the damage at the exit ply significantly increases with an increase in feed, while it slightly reduces with an increase in speed. The drilling-induced damage was then incorporated as pre-existing damage in the open hole laminate using cohesive interaction and state-dependent variables. The presence of the pre-existing drilling-induced damage has lowered the load-carrying capacity of the laminate by 8%. The predictions are in excellent agreement with experimental data from the literature.

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