The relational dynamics of anger and shame: scripts for emotional interactions in Germany and Japan

status: publishe

Different Bumps in the Road: The Emotional Dynamics of Couple Disagreements in Belgium and Japan

In the present study, we propose that the emotional "bumps" that couples experience during relationship disagreements differ systematically among cultures. We predicted that self-assertive emotions such as anger or strength play a central role in Belgium, where they are instrumental for relational independence. In comparison, other-focused emotions such as shame or empathy for the partner should play a central role in Japan, where they support relational interdependence. Romantic couples from Belgium (n = 58) and Japan (n = 80) discussed relationship disagreements in the lab, which were video-recorded. After the interaction, participants separately rated their emotional experience during video-mediated recall. We identified the emotions that played a central role during the interactions in terms of attractors; these are the emotions around which couples stabilize and that likely play a central role in realizing different relationship ideals. In line with our predictions, attractors reflected states of the interpersonal emotional system that support independence in Belgium (e.g., angry or strong feelings) and interdependence (e.g., empathy) in Japan. Moreover, we found that-at least in Belgium-having more culturally typical interactions was associated with a stronger endorsement of culturally valued relationship ideals and, in turn, better relational functioning

A Qualitative Comparison of ANSYS and OpenFOAM results for Carbon dioxide Plume Transport

This research presents Computational Fluid Dynamics (CFD) simulations in ANSYS® illustrating emissions of to the air. The CFD simulations is employed to study plume transport in urban environment, i.e., Breivika port in the city of Tromsø. The case study presents a two-phase model considering specific wind strength and direction in the city of Tromsø. Geographical coordinates, temperature, and wind data were obtained from the open sources, such as Google Maps, and Norwegian Meteorological Institute. The results from the simulations indicates a potential outcome with respect to various weather conditions. It was revealed for vessels less than 30 meter chimney height, the higher the wind strength, the lower the plume dispersion, causing the plume to stay closer to the terrain. This brings in a concentrated amount of pollutants closer to the public areas. The terrain in the model is recognizable for the Tromsø port’s location. From the CFD results, it is illustrated that onshore wind with high wind strength could affect the environment. The results simulated in OpenFOAM are qualitatively showing the same as visible in ANSYS®

Multiphysics Modelling of Powder Coating of U-Profiles: Towards Simulation-based Optimization of Key-Performance Attributes by Variation of Powder-Parameters

Multiphysics simulation software has been developed to predict the key performance attributes of industrial powder coating applications based on applied process-parameter settings. The software is a Eulerian-Lagrangian finite-volume Multiphysics solver based on OpenFOAM, capable of modelling mass transfer effects between powder-coating pistols and electrically grounded metallic substrates. It considers various factors such as fluid dynamics of process airflow, coating-particle dynamics, particle-substrate interactions, and particle charging mechanisms within the corona. The software is fully compatible with Massive Simultaneous Cloud Computing technology, allowing hundreds of simulated coating scenarios to be computed simultaneously. Experimental validation efforts have been conducted, indicating a high degree of practical relevance of the technology. The current simulation study aims to demonstrate the potential of the simulation software for adjusting coating lines and optimizing powder coating of U-profiles. Specifically, the study focuses on optimizing the key-performance-attributes of the powder coating application with respect to varying material parameters of the applied powder, namely mean particle diameter, standard deviation of Gaussian particle size distribution, and powder particle density. The software predicts and visualizes coating patterns, coating efficiencies, and the batch-based standard deviation of coating thickness on a U-shaped metallic substrate, resulting in concrete and optimized powder settings. The presented results and the applied software are highly relevant for powder material suppliers

Standardized microstructure characterization of SOC electrodes as a key element for Digital Materials Design

Performance and durability of solid oxide cell (SOC) electrodes are closely linked to their microstructure properties. Thus, the comprehensive characterization of 3D microstructures e.g., obtained by FIB-SEM tomography is essential for SOC electrode optimization. Recent advances and trends call for a standardized and automated microstructure characterization. Advances in FIB-SEM tomography enable the acquisition of more samples, which are also more frequently shared within the research community due to evolving open science concepts. In addition, the emerging methods for Digital Materials Design (DMD) enable to create numerous virtual but realistic microstructure variations using stochastic microstructure modeling. In this publication, a standardized microstructure characterization tool for SOC electrodes is presented, which is implemented as a Python app for the GeoDict software-package. A large number of microstructure characteristics can be determined with this app, which are relevant for the performance of conventional electrodes like Ni-YSZ and for more recent MIEC-based electrodes. The long list of 3D characteristics that can be determined selectively includes morphological characteristics, interface properties and effective transport properties deduced from morphological predictions and from numerical simulations. The extensive possibilities of the standardized microstructure characterization tool are illustrated for a dataset of three LSTN-CGO anode microstructures reconstructed with FIB-SEM tomography and for a dataset of three virtual sphere-packing structures. The automated microstructure characterization is a key element to exploit the full potential of open science, Digital Materials Design (DMD) and artificial intelligence (AI) for the data-driven optimization of SOC electrodes by providing standardized high quality microstructure property data

Hierarchical structuring of black silicon wafers by ion-flow-stimulated roughening transition : fundamentals and applications for photovoltaics

Ion-flow-stimulated roughening transition is a phenomenon that may prove useful in the hierarchical structuring of nanostructures. In this work, we have investigated theoretically and experimentally the surface texturing of single-crystal and multi-crystalline silicon wafers irradiated using ion-beam flows. In contrast to previous studies, ions had relatively low energies, whereas flow densities were high enough to induce a quasi-liquid state in the upper silicon layers. The resulting surface modifications reduced the wafer light reflectance to values characteristic of black silicon, widely used in solar energetics. Features of nanostructures on different faces of silicon single crystals were studied numerically based on the mesoscopic Monte Carlo model. We established that the formation of nano-pyramids, ridges, and twisting dune-like structures is due to the stimulated roughening transition effect. The aforementioned variety of modified surface morphologies arises due to the fact that the effects of stimulated surface diffusion of atoms and re-deposition of free atoms on the wafer surface from the near-surface region are manifested to different degrees on different Si faces. It is these two factors that determine the selection of the allowable "trajectories" (evolution paths) of the thermodynamic system along which its Helmholtz free energy, F, decreases, concomitant with an increase in the surface area of the wafer and the corresponding changes in its internal energy, U (dU>0), and entropy, S (dS>0), so that dF=dU - TdS<0, where T is the absolute temperature. The basic theoretical concepts developed were confirmed in experimental studies, the results of which showed that our method could produce, abundantly, black silicon wafers in an environmentally friendly manner compared to traditional chemical etching

Composite conductivity of MIEC-based SOFC anodes : implications for microstructure optimization

Fully ceramic anodes such as LSTN-CGO offer some specific advantages compared to conventional cermet anodes. Ceria- and titanate-based phases are both mixed ionic and electronic conductors (MIEC), which leads to very different reaction mechanisms and associated requirements for the microstructure design compared to e.g. Ni-YSZ. Due to the MIEC-property of both solid phases, the transports of neither the electrons nor the oxygen ions are limited to a single phase. As a consequence, composite MIEC electrodes reveal a remarkable property that can be described as ‘composite conductivity’ (for electrons as well as for ions), which is much higher than the (hypothetical) single phase conductivities of the same microstructure. In composite MIEC anodes, the charge carriers can reach the reaction sites even when the volume fraction of one MIEC phase is below the percolation threshold, because the missing contiguity is automatically bridged by the second MIEC phase. The MIEC properties thus open a much larger design space for microstructure optimization of composite electrodes. In this contribution, the composite conductivities of MIEC-based anodes are systematically investigated based on virtual materials testing and stochastic modeling. For this purpose, a large number of 3D microstructures, representing systematic compositional variations of composite anodes, is created by microstructure modeling. The underlying stochastic model is fitted to experimental data from FIB-SEM tomography. For the fitting of the stochastic model, digital twins of the tomography data are created using the methodology of gaussian random fields. By interpolation between and beyond the digital twin compositions, the stochastic model then allows to create numerous virtual 3D microstructures with different compositions, but with realistic properties. The effect of microstructure variation on the composite conductivity is then determined with transport simulations for each 3D microstructure. Furthermore, the corresponding microstructure effects on the cell-performance are determined with a Multiphysics model that describes the anode reaction mechanism. Especially the impact of the composite conductivities on the cell performance is studied in detail. Finally, microstructure design regions are discussed and compared for three different anode materials systems: titanate-CGO (with composite conductivities), Ni-YSZ (with single-phase conductivities), Ni-CGO (with single-phase ionic and composite electronic conductivities)