A material modeling approach for the effective response of planar soft tissues for efficient computational...

Area of Science:

• Biomechanics
• Computational Biology
• Materials Science

Background:

• Accurate soft tissue constitutive models are vital for predicting disease, injury, and surgical outcomes in biomechanical simulations.
• Meso- and multi-scale modeling approaches offer enhanced predictive capabilities but incur significant computational costs.
• Effective constitutive models, derived from homogenized responses of underlying models, can drastically increase simulation speed.

Purpose of the Study:

• To develop a robust effective constitutive model capable of fully reproducing the response of diverse planar soft tissues.
• To establish an optimal method for fast-convergent parameter estimation for these effective models.
• To evaluate the framework's performance in finite element simulations, particularly for complex structures like heart valves.

Main Methods:

• Development of a novel effective constitutive model for planar soft tissues.
• Implementation of a robust and fast-convergent parameter estimation technique.
• Validation through simulations of materials with varying stiffness and anisotropy, and finite element analysis of tri-leaflet heart valves.

Main Results:

• The developed effective constitutive model accurately reproduces a wide range of soft tissue responses.
• The parameter estimation method demonstrated robust and fast convergence.
• The framework successfully handled materials with diverse stiffness and anisotropy, and showed strong performance in heart valve simulations.

Conclusions:

• The effective constitutive modeling approach significantly enhances computational efficiency and numerical robustness of multi- and meso-scale models.
• This method facilitates efficient soft tissue simulations for demanding applications such as inverse modeling and growth.
• The developed framework holds substantial potential for advancing biomechanical simulations in medicine and research.