Comparative Analysis on Modelling Approaches for the Simulation of Fatigue Disbonding with Cohesive Zone Models
Adhesively bonded joints are essential in the aeronautical industry, offering benefits such as weight reduction and enhanced sustainability. However, certifying these joints is challenging due to unreliable methods for assessing their strength and the development of predictive models for fatigue-dri...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
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| Series: | Aerospace |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2226-4310/12/2/139 |
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| Summary: | Adhesively bonded joints are essential in the aeronautical industry, offering benefits such as weight reduction and enhanced sustainability. However, certifying these joints is challenging due to unreliable methods for assessing their strength and the development of predictive models for fatigue-driven disbonding remains an ongoing effort. This manuscript presents the implementation and validation of a cohesive zone model for studying high-cycle fatigue disbonding under Mode I and Mixed-Mode loading. The model was integrated into the commercial finite element analysis software Abaqus using user-defined material subroutine (UMAT). Two modelling approaches were investigated: one replacing the adhesive with a cohesive layer, and the other incorporating a cohesive layer at the adhesive’s mid-plane while modelling its entire thickness, using both 2D and 3D techniques. Validation was conducted against experimental data from the literature that examined the influence of adhesive thickness on fatigue behaviour in DCB and CLS tests. The findings of this study confirm that the model accurately predicts fatigue disbonding across all cases examined. Additionally, the analysis reveals that modelling adhesive thickness plays a critical role in the simulation’s outcomes. Variations in adhesive thickness can significantly alter the crack growth behaviour, highlighting the importance of carefully considering this parameter in future assessments and applications. |
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| ISSN: | 2226-4310 |