A simple interpolation-based approach towards the development of an accurate phenomenological constitutive relation for isotropic hyperelastic materials

TL;DR

This paper introduces an interpolation-based method for developing accurate phenomenological constitutive models for isotropic hyperelastic materials, simplifying model construction and improving prediction accuracy using basic experimental data.

Contribution

It proposes expressing strain energy functions as interpolations of experimental curves based on principal stretches, eliminating the need for initial guesses in model formulation.

Findings

Interpolation from two experimental curves predicts other behaviors well.

Additional experiments improve model accuracy.

Method simplifies constitutive model development for soft materials.

Abstract

Soft materials such as rubber and hydrogels are commonly used in industry for their excellent hyperelastic behaviour. There are various types of constitutive models for soft materials, and phenomenological models are very popular for finite element method (FEM) simulations. However, it is not easy to construct a model that can precisely predict the complex behaviours of soft materials. In this paper, we suggest that the strain energy functions should be expressed as functions of ordered principal stretches, which have more flexible expressions and are capable of matching various experimental curves. Moreover, the feasible region is small, and simple experiments, such as uniaxial tension/compression and hydrostatic tests, are on its boundaries. Therefore, strain energy functions can be easily constructed by the interpolation of experimental curves, which does not need initial guessing in the form of the strain energy function as most existing phenomenological models do. The proposed strain energy functions are perfectly consistent with the available experimental curves for interpolation. It is found that for incompressible materials, the function via an interpolation from two experimental curves can already predict other experimental curves reasonably well. To further improve the accuracy, additional experiments can be used in the interpolation.