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Mechanical characterization and modeling of knitted textile implants with permanent set
Baptiste Pierrat1, Vít Nováček2, Stéphane Avril1
1Mines Saint-Etienne, Univ Lyon, Univ Jean Monnet, INSERM, U 1059 Sainbiose, Centre CIS, F - 42023, Saint-Etienne, France.
Journal of the Mechanical Behavior of Biomedical Materials
|December 18, 2020
Summary
Researchers developed a new computational model for surgical mesh implants used in hernia repair. This model accurately captures the complex mechanical behaviors of these textiles, paving the way for improved surgical treatments.
Area of Science:
- Biomedical Engineering
- Materials Science
- Computational Mechanics
Background:
- Textile-based implants (meshes) are standard for abdominal wall hernia repair.
- Computational models offer a promising approach to study hernia repair biomechanics and enhance clinical outcomes.
Purpose of the Study:
- To present a novel anisotropic hypo-elastoplastic constitutive model for surgical knitted textile implants.
- To characterize the mechanical behavior of surgical meshes, including anisotropy and permanent set.
Main Methods:
- Extensive mechanical characterization of a surgical mesh using cyclic uniaxial tension, planar equibiaxial tension, and plunger testing.
- Development and identification of a novel anisotropic hypo-elastoplastic constitutive model based on tensile experiments.
Main Results:
- The study revealed complex mechanical behavior in surgical meshes, characterized by strong nonlinearity, anisotropy, and permanent set.
- The developed constitutive model successfully reproduced the major mechanical characteristics of the textile implants.
- The model was validated against plunger experiment data, demonstrating its effectiveness.
Conclusions:
- The novel constitutive model accurately represents the mechanical behavior of surgical knitted textile implants.
- This modeling approach, when applied to various surgical textiles, can aid in developing clinical decision support software for hernia repair.
- Further research should focus on implementing this characterization and modeling approach for broader clinical applications.
