An open-source FEniCS-based framework for hyperelastic parameter estimation from noisy full-field data: Application to heterogeneous soft tissues

We introduce a finite-element-model-updating-based open-source framework to identify mechanical parameters of heterogeneous hyperelastic materials from in silico generated full-field data which can be downloaded here https://github.com/aflahelouneg/inverse_identification_soft_tissue. The numerical process consists simulating an extensometer performing vivo uniaxial tensile experiment on soft tissue. reaction forces and displacement fields are respectively captured by force sensor Digital Image Correlation techniques. By means forward nonlinear FEM model inverse solver, the estimated through constrained optimization function with no quadratic penalty term. As case study, our Finite Element Model Updating (FEMU) tool has been applied composed keloid scar surrounded healthy skin. results show that at least 4 accurately identified test only. originality this work lies two major elements. Firstly, we develop low-cost technique able characterize properties materials. Secondly, explore accuracy via detailed study interplay between discretization error due measurement uncertainty. Next steps consist identifying real so finding matching preferential directions scars growth.