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The dynamic material characterization shows different macroscopic strain rate effects. The causal mechanisms cannot be identified at this level in most cases. Micro-tests allow a local transient analysis, which is illustrated in this article using the example of a long-fibre reinforced thermoplastic (LFRT). After a general introduction, the development and validation of a micro-test for a large strain rate range is presented. The validation explained for steel shows the advantage of the small sample for the dynamic characterization, if a homogenous material behaviour of this magnitude still exists, especially in the case of low-vibration force measurement. For a heterogeneous LFRT material, the micro-test shows strongly scattering test results that are no longer representative of the homogenized mechanical material behaviour, but reflect the local characteristics. These local properties are directly caused by the injection moulding process. Further SEM analyses of the samples indicate different macromolecular deformation mechanisms of the matrix at the different strain rates.

Modeling the nonlinear material behaviour of long fiber reinforced thermoplastics (LFT) presents a challenging task since local inhomogeneities and nonlinear effects must be taken into account also on the microscale. We present a computational method with which we can predict the nonlinear material response of a composite material using only standard DMA measurements on the pure polymer matrix material. The material models considered include plasticity, damage, viscoelasticity, and viscoplasticity as described in [1]. These models can be combined similar to the model from [2] and extended to the composite by assigning linear elastic properties to the fibers. The mechanical response of the composite is computed using an FFT-based technique [3]. The geometry of the composite, in particular the fiber orientation, can be characterized using injection molding simulations or micro CT scans. We create virtual models of the composite using the algorithm of [4]. We show that with this method, the material behaviour of the composite can be predicted while the experimental complexity needed for the material characterization is low.