Efficient identification of material parameters for an orthotropic hyperelastic nonlinear material model for textile membranes. (16th May 2023) - Motevalli, Mehran; Balzani, Daniel
Abstract: A recently proposed orthotropic nonlinear material model for general classes of woven fabrics is adapted to glass-PTFE and PES-PVC fabrics. The nonlinear model contains three governing stiffness-related material properties that will be shown to be separately and uniquely identified using a new optimization procedure. The parameter identification procedure is based on the separation into nonlinear model and linear material parameters. In a first step, the model parameters are optimized by minimizing a least-square functional which measures variations of the material parameters identified for each deformation state independently. Once the optimized model parameters are determined, the associated stiffness-related material parameters are uniquely identified. As a result, a highly efficient method is obtained, which allows for the independent identification of model and material parameters. The model parameters are shown to be kept fixed for a specific class of textile membrane materials and only the stiffness-related properties need to be adjusted for a new production batch or a new material from this class. By comparing differently identified parameters, the performance of the proposed procedure is analyzed in a numerical simulation of a roof structure. Highlights: A new framework for parameter identification of an orthotropic hyperelastic model. Method separates identification of nonlinear model- and stiffness-related parameters. Unique identification is achieved via uncommon strain-controlled objective function. Standardization of fabrics through meaningful uniquely identified parameters. Proof of the proposed concept in computational analysis of a realistic roof structure.