Simulation-Based Material Characterization for Elastomers

The patent creates a virtual copy of the physical testing process through simulation. Instead of performing multiple complex physical tests (uniaxial, biaxial, triaxial) to characterize material behavior, the system uses computational models that replicate these test conditions numerically. This virtual copying allows repeated testing at different deformation modes without physical constraints, dramatically reducing testing time while maintaining measurement precision through accurate material parameter fitting.

The patent replaces the physical mechanical testing system with a computational simulation system. Traditional mechanical testers requiring complex biaxial and triaxial setups are substituted by finite element analysis software that performs the same measurements virtually. This substitution eliminates the need for complex mechanical apparatus while achieving the same material characterization goals, thereby reducing both time and cost.

The system creates virtual replicas of physical test setups through computational models. Instead of requiring actual biaxial and triaxial testing equipment, the patent uses software-based simulation environments that replicate these complex test conditions. This virtual copying approach maintains measurement precision by accurately modeling material behavior under various deformation modes while eliminating the need for complex physical apparatus.

The patent substitutes complex mechanical testing systems with computational simulation systems. The physical biaxial and triaxial testing setups are replaced by finite element analysis software that performs the same measurements numerically. This replacement maintains accuracy in material characteristic determination while significantly reducing device complexity and associated costs.

The patent implements an iterative feedback process where simulation results are continuously compared with experimental data, and material parameters are adjusted accordingly. The system uses optimization algorithms that take prediction errors as feedback and automatically adjust material model parameters to minimize discrepancies between simulated and measured behavior. This feedback mechanism maintains simulation simplicity while significantly improving prediction accuracy through data-driven parameter calibration.

The patent dynamically adjusts material model parameters based on experimental data and simulation performance. Instead of using fixed analytical models, the system optimizes parameters such as hyperelastic constants and viscoelastic coefficients by comparing predictions with actual measurements. This parameter optimization process maintains the simplicity of the simulation framework while improving accuracy through empirical calibration, allowing the same simple model structure to achieve high prediction accuracy across different finite element resolutions.