LAUSR

Abstract Due to wide applications of hyper-viscoelastic material models in medicine and industry, many researchers have focused on determination of the parameters of these models. In problems for identification of material parameters of hyper-elastic and hyper-viscoelastic members, detailed information about boundary conditions is necessary. In reality, for an in vivo soft tissue or an engineering part in service, detailed information about the supports of the member may be unavailable. In such cases, assuming some kind of boundary conditions that may be far from truth will result in unacceptable solutions. In this work, for the first time, an inverse analysis-based method for the identification of hyper-viscoelastic parameters of a member with arbitrary shape under plane strain conditions is presented. The unknowns are found using displacement measurements in an elasto-dynamic loading, while details about the support of the member are unclear. The proposed algorithm minimizes the differences between measured and calculated displacements. The minimization algorithm needs some sensitivity analyses, which are performed via finite difference approximation and analytic differentiation. For modeling the hyper-viscoelastic behavior, a model consisting of some Maxwell elements in parallel with a neo-Hookean hyper-elastic spring is considered. The effectiveness of the proposed method is evaluated by presenting several numerical examples.