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The viscoelastic behavior of short fiber reinforced polymers (SFRPs) partly depends on different microstructural parameters such as the local fiber orientation distribution. To account for this by simulation on component level, two‐scale methods couple simulations on the micro‐ and macroscale, which involve considerable computational costs. To circumvent this problem, the generation of a viscoelastic surrogate model is presented here. For that purpose, an adaptive sampling technique is investigated and data are obtained by creep simulations of representative volume elements (RVEs) using a fast Fourier transform (FFT) based homogenization method. Numerical tests confirm the high accuracy of the surrogate model. The possibility of using that model for efficient material optimization is shown.

In short‐fiber reinforced polymers, fatigue damage is typically characterized by measuring the dynamic stiffness and its degradation under cyclic loading. Computational homogenization methods may be used to characterize the fatigue behavior of the composite via numerical predictions. Such an approach may reduce the experimental effort significantly. In the previous works, the authors proposed an elastic fatigue damage model for predicting the relative stiffness degradation of short‐fiber reinforced materials. However, the absolute value of the dynamic stiffness within the first cycle showed deviations from the expected elastic material behavior. Thus, the effect of viscoelastic polymer behavior as well as different microstructure descriptors on the dynamic stiffness is studied in the work at hand.