A Novel Approach for Optimization of Soft Material Constitutive Model Parameters Based on a Genetic Algorithm and...

Area of Science:

• Materials Science
• Computational Mechanics

Background:

• Soft materials are crucial for flexible devices, necessitating precise constitutive models.
• Accurate parameter determination is vital for reliable material modeling.

Purpose of the Study:

• To present a novel optimization approach for constitutive model parameters.
• To enhance the accuracy of modeling soft material behavior.

Main Methods:

• Utilized a genetic algorithm (GA) for parameter optimization.
• Employed uniaxial tensile test data and finite element analysis (FEA).
• Incorporated Drucker's stability criterion for solution validation.

Main Results:

• Achieved high correlation between experimental and predicted data (low RMSE values).
• Warner's model: RMSE 0.022 (ANSYS), 0.024 (ABAQUS).
• Yeoh's model: RMSE 0.014 (ANSYS), 0.012 (ABAQUS).
• Demonstrated high reproducibility and stability.

Conclusions:

• The GA-FEA approach effectively optimizes constitutive parameters for soft materials.
• The method ensures accurate prediction of material behavior and meets stability criteria.
• Applicable to elastomers like Ecoflex 00-30 using Warner and Yeoh models.