Characterization of human passive muscles for impact loads using genetic algorithm and inverse finite element methods

Area of Science:

• Biomechanics
• Materials Science
• Computational Modeling

Background:

• Accurate modeling of human passive muscle tissue is essential for understanding injury mechanisms in automobile crashes.
• Dynamic material properties of muscle tissue under high strain rates are not fully characterized.
• Existing models may not fully capture the complex viscoelastic behavior of muscle during impact events.

Purpose of the Study:

• To identify the dynamic material properties of human passive muscle tissues at strain rates relevant to automobile crashes.
• To implement a novel methodology combining genetic algorithms (GA) and finite element methods (FEM) for material parameter estimation.
• To model passive muscle tissue as an isotropic, linear, and viscoelastic material using a three-element Zener model.

Main Methods:

• Performing isolated unconfined impact tests on muscle tissues at average strain rates from 136 s⁻¹ to 262 s⁻¹.
• Utilizing a genetic algorithm (GA) for inverse mapping of impact test data to estimate material parameters.
• Employing the PAMCRASH™ explicit finite element software for material modeling and force calculations.

Main Results:

• Linear viscoelastic material parameters (bulk modulus, short-term shear modulus, long-term shear modulus) were identified at specific strain rates (136 s⁻¹, 183 s⁻¹, 262 s⁻¹).
• Identified parameters were comparable to existing literature values.
• Bulk modulus and short-term shear modulus demonstrated greater influence on the stress-strain response compared to long-term shear modulus within the tested strain rates.

Conclusions:

• The identified material parameters provide valuable data for simulating muscle tissue behavior in car crash scenarios.
• Variations in parameters across different strain rates suggest the need for advanced material models.
• Future research should focus on developing improved models capable of capturing strain rate dependency with a single parameter set for a wider range of strain rates.