Predicting biaxial failure strengths of aortic tissues using a dispersed fiber failure model

Despite advances in methods to incorporate patient-specific aortic geometries and tissue elastic properties into computational rupture risk analyses of aortic aneurysms, isotropic failure metrics remain widely used for aortic tissue, which oversimplifies its anisotropic failure characteristics. While classical failure criteria for engineered unidirectional fiber-reinforced composites demonstrate improved performance over isotropic metrics in predicting aortic failure properties, an accurate failure metric tailored to the aorta that accounts for dispersed collagen fiber architecture remains largely undeveloped and requires experimental validation. In this study, we employed a novel dispersed fiber failure metric that considers fiber dispersion and assessed its ability to predict the biaxial failure strengths of the aortic wall. We conducted off-axis uniaxial and planar biaxial failure tests, from which anisotropic failure strengths of aortic tissues were obtained through digital image correlation analysis. The off-axis uniaxial data were used to calibrate the failure model parameters, while the biaxial failure data provided direct experimental validations. Using this approach, we evaluated the performance of two variants of the dispersed fiber failure metric: the dispersed Tsai-Hill and dispersed Hashin-Rotem models, comparing them to their unidirectional counterparts. Results showed that the dispersed Tsai-Hill and dispersed Hashin-Rotem models outperformed their unidirectional counterparts, reducing errors by 33.8 % and 34.3 %, respectively. These findings highlight the significance of incorporating fiber dispersion in models that predict aortic tissue failure.