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Parameter identification for constitutive models of innovative textile composite materials using digital image correlation

This contribution focuses on an innovative composite material consisting of textile layers made from continuous wooden fibers embedded in a thermoplastic matrix. A finite element simulation of potential use‐cases is planned to support the development process and to study the suitability of the material in an architectural context. The simulation is based on a constitutive model assuming homogenous orthotropic elastic behavior and will be expanded to include multiscale modeling in future research. The material parameters used in such models can often be determined based on a small number of local measurements during experiments like tensile tests, which assume classical one dimensional load scenaria at least in parts of the specimen. However, this is not sufficient for non‐homogeneous materials, especially when dealing with non‐isotropic materials in off‐axis configurations and the need for full‐field measurements like digital image correlation (DIC) arises. Experimental results of uniaxial on‐ and off‐axis tensile tests using DIC are presented and used in the identification of the material parameters of the given model. Results of simulations and experiments are compared and the suitability of the material model is discussed.

Citation
In: Proceedings in applied mathematics and mechanics (PAMM) Volume 19 / Issue 1 (2019-11-18) , S. ; EISSN 1617-7061
Collections
@article{doi:10.17170/kobra-202012072399,
  author    ={Hofmann, Justin Felix and von Boyneburgk, Claudia Louise and Tunger, Sophie and Heim, Hans-Peter and Kuhl, Detlef},
  title    ={Parameter identification for constitutive models of innovative textile composite materials using digital image correlation},
  keywords ={600 and Verbundwerkstoff and Finite-Elemente-Methode and Simulation and Textilfaser},
  copyright  ={http://creativecommons.org/licenses/by/4.0/},
  language ={en},
  journal  ={Proceedings in applied mathematics and mechanics (PAMM)},
  year   ={2019-11-18}
}