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Updated: May 30, 2026

A Coupled Experiment-finite Element Modeling Methodology for Assessing High Strain Rate Mechanical Response of Soft Biomaterials
Published on: May 18, 2015
Anisotropic AAA: computational comparison between four and two fiber family material models
P Di Achille1, S Celi, F Di Puccio
1Department of Mechanical, Nuclear and Production Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56100 Pisa, Italy.
Computational models for abdominal aortic aneurysm (AAA) wall mechanics differ significantly. A four-fiber model predicts higher circumferential stress, while a two-fiber model shows higher axial stress in AAA inflation simulations.
Area of Science:
- Biomedical Engineering
- Computational Mechanics
- Cardiovascular Research
Background:
- Abdominal aortic aneurysm (AAA) is a prevalent cardiovascular disease in the elderly.
- Accurate biomechanical modeling of AAA wall is crucial for understanding pathogenesis and clinical management.
- Existing constitutive models for AAA tissue show varying degrees of accuracy.
Purpose of the Study:
- To compare the predictive capabilities of two-fiber (2FF) and four-fiber (4FF) constitutive models for AAA wall behavior.
- To investigate the influence of different strain energy functions (SEFs) on AAA inflation simulations.
- To assess the impact of data extrapolation on model predictions.
Main Methods:
- Implemented 2FF and 4FF constitutive models in a finite element code.
- Simulated AAA inflation under physiological axial stretch (20%).
- Compared model predictions for stress distribution under simulated AAA conditions.
Main Results:
- Both 2FF and 4FF models fit experimental biaxial test data well.
- Significant differences in predicted stress outcomes between the 2FF and 4FF models were observed during AAA inflation.
- The 4FF model predicted increased circumferential stress, while the 2FF model predicted higher axial stress.
Conclusions:
- The choice of constitutive model significantly impacts biomechanical predictions for AAA.
- Model discrepancies arise from SEF behavior outside the range of fitting data, particularly during extrapolation.
- Experimental data should ideally be acquired under conditions relevant to the intended application, such as AAA inflation.
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