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In this contribution, selected results from [1–3] are presented in a compact and simplified way. In addition, the variety of fiber orientation tensors is used to determine a maximum deviation of the direction-dependent Young's modulus, which can arise if only second-order directional information is included in a specific meanfield homogenization. Focusing on the special case of planar fiber distributions, the variety of fiber orientation tensors identified in [1] is considered as a design space. This design space is completely explored for the orientation-averaging homogenization following [4], fixed material parameters and fixed fiber volume content. The possible directional dependence of the resulting effective stiffnesses is graphically presented using polar plots of the direction-dependent Young's modulus. These polar plots are arranged on two-dimensional slices within the parameter space of planar fourth-order fiber orientation tensors. This gives a complete representation of the influence of the orientation tensor on the anisotropic stiffness tensor. Consequences of closure approximations, i.e., restriction to second-order directional information, are demonstrated and motivate measurement of fourth-order fiber orientation tensors.

Thermoplastic polyamides are used in many industrial areas due to their potential in lightweight applications. Polyamides serve as matrix material in fiber reinforced thermoplastics, for instance. The mechanical behavior of polyamides is characterized by pronounced viscoelastic effects that are strongly affected by environmental conditions like temperature or humidity. In this work, linear thermoviscoelastic behavior of polyamide 6 is considered. Viscoelastic behavior is modeled by the generalized Maxwell model while extended time-temperature superposition is used to model temperature dependency. A temperature-frequency sweep conducted by dynamic mechanical analysis serves as input for the model. By horizontal and vertical shifting, master curves of the loss factor, storage modulus, and loss modulus are obtained. Based on this, limitations of time-temperature superposition and linear thermoviscoelastic modeling are discussed. Furthermore, it is shown that the horizontal shifts can be well approximated by the Williams-Landel-Ferry equation for temperatures above and below the glass transition temperature.

For material modeling of microstructured media, an accurate characterization of the underlying microstructure is indispensable. Mathematically speaking, the overall goal of microstructure characterization is to find simple functionals which describe the geometric shape as well as the composition of the microstructures under consideration, and enable distinguishing microstructures with distinct effective material behavior. For this purpose, we propose using Minkowski tensors, in general, and the quadratic normal tensor, in particular, and introduce a computational algorithm applicable to voxel-based microstructure representations. Rooted in the mathematical field of integral geometry, Minkowski tensors associate a tensor to rather general geometric shapes, which make them suitable for a wide range of microstructured material classes. Furthermore, they satisfy additivity and continuity properties, which makes them suitable and robust for large-scale applications. We present a modular algorithm for computing the quadratic normal tensor of digital microstructures. We demonstrate multigrid convergence for selected numerical examples and apply our approach to a variety of microstructures. Strikingly, the presented algorithm remains unaffected by inaccurate computation of the interface area. The quadratic normal tensor may be used for engineering purposes, such as mean-field homogenization or as target value for generating synthetic microstructures.