Abstract
Short fiber reinforced thermoplastics (SFRT) are widely used for automotive components. One of the significant challenges in designing industrial SFRT components is an efficient prediction of their mechanical response under mechanical and thermal loads. In this work, an anisotropic temperature-dependent elasto-viscoplastic model is implemented using the available macroscopic material models in commercial FE solver to describe polybutylene terephthalate with 30 wt.-% short glass fibers. The elastic behavior is described by the orthotropic linear elastic model generated through the mean-field homogenization method and the anisotropy in plastic region by Hill yield criterion dependent on fiber orientation. The rate-dependent plasticity is described by the unified viscoplasticity framework of Chaboche. To describe the continuous temperature dependency, model parameters are systematically determined as a function of temperature in the typical automotive temperature range, including regions below and above glass transition temperature. Further, an optimization method based on genetic algorithm is adopted for parameter optimization. The optimized model accurately describes the anisotropic material behavior observed in tensile and stress relaxation tests in a wide range of temperature, specimen orientation, and strain rate. The model's prediction capability is validated by simulating tensile tests at three intermediate temperatures, which are not included during the calibration process.
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