Finite Element Model Updating Combined with Multi-Response Optimization for Hyper-Elastic Materials Characterization.

Area of Science:

• Materials Science
• Mechanical Engineering
• Computational Mechanics

Background:

• Standardized tests for elastomer behavior yield complex stress-strain curves requiring expensive equipment.
• Current model updating methods for determining material constants (Cᵢ) are computationally intensive.
• Simpler force-displacement curves are preferred but require robust parameterization.

Purpose of the Study:

• To develop an automated, economical methodology for determining elastomer material constants (Cᵢ).
• To combine model updating with multi-response surface (MRS) methods and desirability functions.
• To reduce the computational cost associated with elastomer behavior modeling.

Main Methods:

• Utilized standardized tensile, compression, and shear tests.
• Employed parameterized finite element (FE) models with experimental force-displacement data.
• Integrated multi-response surface (MRS) and desirability functions for automated Cᵢ constant determination.
• Generated quadratic regression models for error functions (ER) between experimental and FE curves.

Main Results:

• The proposed methodology successfully determined Cᵢ constants for NBR, EVA, SBR, and PUR elastomers.
• The Mooney-Rivlin hyper-elastic model demonstrated the least error across studied materials.
• Achieved low error in Cᵢ constant adjustment (e.g., MAEnorm = 0.054 for NBR).

Conclusions:

• The combined MRS and desirability function approach offers a simpler, more economical alternative for obtaining optimal Cᵢ constants.
• This methodology can be applied to any elastomer type, reducing computational expense.
• Validated the effectiveness of the proposed method for accurate elastomer behavior modeling.