Identification of System Properties in a Square Frame Undergoing Large Deformations: Numerical and Experimental Investigations

The aim of this paper is to highlight and identify the influencing parameters of the nonlinear behavior of highly deformable structures. Therefore, as an example, a large deformable square frame consisting of four slender members of equal length has been investigated experimentally. Based on highly resolving measurements using the digital image correlation method (DIC), the inverse problem of nonlinear system identification has been solved by an automatic parameter identification algorithm. For this purpose, a numerical model is set up with a beam finite element model using the absolute nodal coordinate formulation (ANCF), which enables the modeling of geometrical and possible material nonlinearities. The influencing parameters as well as the system properties have been determined by using a genetic optimization algorithm. The impact of the main influencing parameter is carved out by an included sensitivity study. The final model with automatically identified parameters shows high agreement with the experimental setup. With this approach the influences and nonlinearities, e.g. material parameters, rigid behavior, real boundary conditions, etc., come up to surface leading to a deeper understanding of the structural behavior of the system itself. Therefore, the present approach can be utilized for further investigations of nonstandard structures undergoing large deformations.