Hyper-Data: A Matlab based optimization software for data-driven hyperelasticity

In this work, a parameter identification software for the data-driven hyperelasticity frameworks proposed by Dal et al. (Journal of the Mechanics and Physics of Solids 179, 105381, 2023), and Tikenoğullarıet al. (Journal of the Mechanics and Physics of Solids 181, 105453, 2023) is introduced. These data-driven hyperelasticity frameworks allow direct incorporation of experimental data into the constitutive model with the usage of B-splines, removing the requirement of a predetermined mathematical formula for the strain–energy density function. Three isotropic and two dispersion-type anisotropic data-driven formulations are embedded in the software. Additionally, three established models from the literature are included for comparison purposes. An optimization procedure is employed to identify the control points, also referred to as material parameters. This process involves tailoring the model to best fit data obtained from uniaxial tension, triaxial shear, pure shear, and (equi)biaxial tension experiments. The model calibration phase incorporates the normalization condition and the polyconvexity condition is enforced through the control points of the B-splines in order to ensure a stable constitutive response.