A tailor-made microstructure, especially regarding grain size and texture, improves the magnetic properties of non-oriented electrical steels. One way to adjust the microstructure is to control the production and processing in great detail. Simulation and modeling approaches can help to evaluate the impact of different process parameters and finally select them appropriately. We present individual model approaches for hot rolling, cold rolling, annealing and shear cutting and aim to connect the models to account for the complex interrelationships between the process steps. A layer model combined with a microstructure model describes the grain size evolution during hot rolling. The crystal plasticity finite-element method (CPFEM) predicts the cold-rolling texture. Grain size and texture evolution during annealing is captured by the level-set method and the heat treatment model GraGLeS2D+. The impact of different grain sizes across the sheet thickness on residual stress state is evaluated by the surface model. All models take heterogeneous microstructures across the sheet thickness into account. Furthermore, a relationship is established between process and material parameters and magnetic properties. The basic mathematical principles of the models are explained and demonstrated using laboratory experiments on a non-oriented electrical steel with $3.16$ wt.% Si as an example.

Within the FOR3010 Refrabund project, a new type of composite refractory consisting of alumina and refractory metals such as tantalum and niobium is developed. This material is characterized by its ability to conduct electricity, which offers new opportunities for functional parts in high‐temperature environments. To support the development of material properties and production technology, a new simulation approach is needed, which is able to describe irregularly shaped particles of at least two different phases. Current simulations of sintering processes work often with heavily idealized powder geometries. As sintering is mainly driven by gradients of chemical potential due to surface curvatures, a realistic description of the particle geometry is essential for achieving precise simulation results. Herein, a new approach of modeling the sintering behavior of irregularly shaped powder particles by the use of a finite differences approach is developed. A discrete description of irregular powder particles is introduced, and the diffusional flows at their surfaces and sintering necks as well as their development in time are calculated. The new model is compared with an older model using spherical particle geometries from literature. Comparison with experimental results follows in a subsequent publication.

Performing prosociality in public presents a paradox: only by doing so can people demonstrate their virtue and also influence others through their example, yet observers may derogate actors’ behavior as mere “virtue signaling.” Here we investigate the role of observability of actors’ behavior as one reason that people engage in such “virtue discounting.” Further, we investigate observers’ motivational inferences as a mechanism of this effect, using the comparison of generosity and fairness as a case study among virtues. Across 14 studies (7 preregistered, total N = 9,360), we show that public actors are perceived as less virtuous than private actors, and that this effect is stronger for generosity compared to fairness (i.e., differential virtue discounting). Exploratory factor analysis suggests that three types of motives—principled, reputation-signaling, and norm-signaling—affect virtue discounting. Using structural equation modeling, we show that observability’s effect on actors’ trait virtue ratings is largely explained by inferences that actors have less principled motivations. Further, we leverage experimental evidence to provide stronger causal evidence of these effects. We discuss theoretical and practical implications of our findings, as well as future directions for research on the social perception of virtue.

Current simulations of sintering processes work often with heavily idealized powder geometries. As sintering is mainly driven by gradients of chemical potential due to surface curvatures, a realistic description of the particle geometry is essential for achieving precise simulation results. In previous work, a model able to simulate sintering behavior of irregularly shaped particles was shown. Herein, a statistical approach for description of particles’ morphology in a powder mixture is developed by fitting a simplified particle shape model on image data. The obtained data are analyzed and conditioned for input into sintering simulation. Instead of building an equivalent volume cell of particles, as common, a Monte Carlo approach is applied to describe the sintering behavior of the powder. The resulting distributions of sintering time curves are analyzed regarding the influence of the morphology description in comparison to circular particles. Using thumb rules of Cohen's effect size, a small effect on shrinkage and a medium effect on neck radii is observed.

Aggregates of niobium–alumina refractory composites are characterized, which are produced by a castable technology followed by a crushing process. Phase separation between niobium and corundum is found for the obtained aggregate classes and the impurity phases NbO and β–Nb₂C are present according to X‐ray diffraction measurements. Among the studied aggregate classes, niobium shows differences in chemistry expressed by the corresponding lattice parameters. The determined morphology and roughness parameters show that the synthesized aggregates are not substantial different independent of their density and porosity.

Groove rolling is one of the main process routes for the production of metal long products, such as bars, beams, wires, and rods. In this process, a workpiece is deformed by two or more rotating rolls to reduce the cross-section to achieve a desired cross-section shape. The shape is determined by the contour of the rolls' surfaces, called the groove or calibre. The process is usually accomplished in multiple steps, each called a pass. The industry is currently under heavy pressure to optimize its processes regarding energy consumption while maintaining or increasing product quality. The introduction of new materials and alloys challenges production and technology engineers. In the past decades, numerical simulation tools have become an integral part of process development and maintenance. They are used to estimate forces and engine torques, as well as geometrical and microstructural evolution of the workpiece for a given pass sequence and input workpiece geometry and material. This knowledge is important to design or optimize a process, identify sources of errors, increase product quality or extend the product portfolio.