Open Access

‘Communication’ is the basic concept of an aesthetic media theory and, under the title ‘communication aesthetics’, is particularly suitable for defining a capacity of that phenomenon that also describes a holistic experience of so-called digitality in a new way. In the passage through this concept of communication, ‘communication aesthetics’ is therefore also the basic term for studies of digital media cultures and is used here as an example to determine the relevant phenomena of mediality, materiality and the contemporary technological body practices associated with them. ‘Aesthetics of communication’ is then also the title word for the sought-after answer to the question of whether the speech of transfer between different arts as ekphrastic representation acquires a significance of its own that cannot be decomposed by unconditionally necessary and, as a rule, even more important reflection on its effects. The essay examines how both sides of the term – the ‘aesthetic’ and the ‘communicative’ – can be discussed in order to reflect on their connection, especially against the background of the implications of the digital per se. In the first part, the contrasts that determine this conceptual construction are analyzed using an example of media culture in order to read them as the basic definitions of a dialectical concept of the ‘communicative-aesthetic’. Against this background, the second part of the essay deals with the related ‘communication-aesthetic’ practices that could be used as the ingredients and objects of a genuine interdisciplinary media theory.

This study examines the impact of integrating solar photovoltaic (PV) systems on power factor (PF) within low-voltage radial distribution networks, using empirical data from the Energy Self-Sufficiency for Health Facilities in Ghana (EnerSHelF) project sites in Ghana. The research included simulations focusing on optimal PV integration, with and without PF considerations, and the strategic placement of PV and shunt capacitors (SC). Three scenarios evaluated PV injection at high-load demand nodes, achieving penetration levels of 85.00 percent, 82.88 percent with high voltage drop, and 100.00 percent with high loss nodes. Additionally, three scenarios assessed SC allocation methods: proportional to the node's reactive power demand (Scenario I), even distribution (Scenario II), and proportional to installed PV capacity at PV nodes (Scenario III). The analysis used a twin-objective index (TOI), combining voltage deviations and power factor degradation. Results showed significant PV curtailment was necessary to achieve standard PF. Optimal penetration levels, considering TOI, reduced PV penetration from 85.00 percent to 63.75 percent, 82.88 percent to 57.38 percent, and 100.00 percent to 72.50 percent for high load, high voltage drops, and high loss nodes, respectively. Notably, all scenarios showed a concerning PF of 0.00 at dead-end nodes (P20, P21, P22). Scenario I achieved PF ranges of -0.26 to 1.00 with PV at high load, -0.69 to 1.00 with PV at high voltage drop, and 0.95 to 1.00 with PV at high loss nodes. Scenario II produced similar ranges, -0.48 to 1.00, -1.00 to 0.99, and 0.30 to 0.96, with PV placement at high load, voltage drops, and loss nodes, respectively. Scenario III yielded ranges of -0.19 to 0.97 (high load), -0.23 to 1.00 (high voltage drop), and 0.86 to 0.96 (high losses). The study concluded that the most effective strategy involves installing PVs at high-loss nodes and distributing SCs proportionally to the node's reactive power demand (Scenario I). This approach achieved a more uniform PF pattern throughout the network, highlighting the practical implications of strategic PV placement and targeted reactive power compensation for maintaining a healthy and efficient distribution system with solar PV integration.

The recent transformation of the energy sector brings new challenges in areas such as supply security, efficiency, and reliability. Especially the increase of decentralized power plants leads to a more complex energy system and an increasing complexity. This requires expansion and digitization of the power grid as well as an initiative-taking operation of the grid operator. To investigate such complex systems and its phenomena, modern development methods such as real-time simulation or digital twins (DT) can be used. In this approach a digital replica of the real-world system, a grid section, is developed, which can represent or predict the behavior of the real distribution grid. For this, a model of the real-world system is derived and implemented in a co-simulation environment, in which it receives data via an analyzer or measurement system from the grid model. This paper focuses on the development of the digital twin of a testing grid and a grid analyzer for the measurement. With the digital twin of the testing grid, a first approach is achieved in a real-time capable environment showing the functionalities and interactions of a digital twin. Subsequently the development of the digital twin model is explained, and the results are discussed.

Im neuen IHK-Zertifikatslehrgang „Ausbildung trifft Nachhaltigkeit“ erwerben die Teilnehmenden aus kaufmännischen Berufen umfangreiches Handlungswissen, das sie direkt im betrieblichen Alltag umsetzen können. Damit sind Ausbildende in der Lage, ein kompetenzorientiertes Nachhaltigkeitsprojekt zu konzipieren und es mit ihren Auszubildenden im Betrieb umzusetzen. Der modulare Lehrgang orientiert sich inhaltlich am Deutschen Nachhaltigkeitskodex (DNK). Ausbildende Fachkräfte sollen zudem für die neuen Standardberufsbildpositionen sensibilisiert werden. Nach erfolgreichem Abschluss können die Teilnehmenden das IHK-Zertifikat „Fachkraft Ausbildung für nachhaltige Entwicklung“ erhalten. Im Beitrag werden Chancen und Herausforderungen für den Transfer der Weiterbildung in die Strukturen der Bildungslandschaft der Industrie- und Handelskammern (IHK) erläutert.

OBJECTIVES: The present study aimed to evaluate the trueness and precision of monolithic zirconia crowns (MZCs) fabricated by 3D printing and milling techniques. METHODS: A premolar crown was designed after scanning a prepared typodont. Twenty MZCs were fabricated using milling and 3D-printing techniques (n=10). All the specimens were scanned with an industrial scanner, and the scanned data were analyzed using 3D measurement software to evaluate the trueness and precision of each group. Root mean square (RMS) deviations were measured and statistically analyzed (One-way ANOVA, Tukey's, p≤0.05). RESULTS: The trueness of the printed MZC group (140 ± 14 μm) showed a significantly higher RMS value compared to the milled MZCs (96 ± 27 μm,p<0.001). At the same time, the precision of the milled MZCs (61±17 μm) showed a significantly higher RMS value compared to that of the printed MZCs (31±5 μm,p<0.001). CONCLUSIONS: The Fabrication techniques had a significant impact on the accuracy of the MZCs. Milled MZCs showed the highest trueness, while printed MZCs showed the highest precision. All the results were within the clinically acceptable error values. CLINICAL SIGNIFICANCE: Although the trueness of the milled MZCs is higher, the manufacturing accuracy of the 3D-printed MZCs showed clinically acceptable results in terms of trueness and precision. However, additional clinical studies are recommended. Furthermore, the volumetric changes of the material should be considered.

Um ein Power-to-Gas-to-X-System effizient zu optimieren, kann ein digitaler Zwilling als Simulationsmodell auf Basis experimenteller Daten für ein Laborsystem erstellt und entsprechend verändert werden. Darüber hinaus müssen für die Überwachung des realen Systems bzw. die Online-Simulation kontinuierlich Daten aus Experiment und Simulation erfasst und verarbeitet werden. Insgesamt ist ein effizienter Datenmanagement-Workflow erforderlich. In dieser Arbeit wird ein Workflow aus freier, etablierter und skalierbarer Open-Source-Software für die vorliegende Anwendung skizziert und insbesondere ein geeignetes Datenmodell entwickelt, implementiert und seine ressourcensparende Realisierung auf kostengünstiger Hardware gezeigt. Abhängig von der Datenmodellierung kann preiswerte und alte Hardware für die geforderte Aufgabe ausreichend sein. Mit Apache NiFi wird ein visueller Workflow zum Abrufen und Verarbeiten von Daten aus verschiedenen Quellen geschaffen. Die extrahierten Daten werden in Apache Cassandra aggregiert, einem Datensystem, das aufgrund seiner Leistung, Skalierbarkeit und Haltbarkeit häufig verwendet wird. Grafana wird zur visuellen Überwachung des Systems eingesetzt. Das gesamte System wird mit Hilfe von Docker-Containern aufgebaut zum Zwecke der Reproduzierbarkeit und effizienten Bereitstellung. Benchmarks und realistische Hardware- und Datenmodellierungskonfigurationen demonstrieren die Leistung der vorgeschlagenen Lösung.

High-latitude intermediate-velocity clouds (IVCs) are part of the Milky Way’s H I halo and originate from either a galactic fountain process or extragalactic gas infall. They are partly molecular and can most of the time be identified in CO. Some of these regions also exhibit high-velocity cloud gas, which is mostly atomic, and gas at local velocities (LVCs), which is partly atomic and partly molecular. We conducted a study on the IVCs Draco and Spider, both were exposed to a very weak UV field, using the spectroscopic receiver upGREAT on the Stratospheric Observatory for Infrared Astronomy (SOFIA). The 158 µm fine-structure line of ionized carbon ([C II]) was observed, and the results are as follows: In Draco, the [C II] line was detected at intermediate velocities (but not at local or high velocities) in four out of five positions. No [C II] emission was found at any velocity in the two observed positions in Spider. To understand the excitation conditions of the gas in Draco, we analyzed complementary CO and H I data as well as dust column density and temperature maps from Herschel. The observed [C II] intensities suggest the presence of shocks in Draco that heat the gas and subsequently emit in the [C II] cooling line. These shocks are likely caused by the fast cloud’s motion toward the Galactic plane that is accompanied by collisions between H I clouds. The nondetection of [C II] in the Spider IVC and LVC as well as in other low-density clouds at local velocities that we present in this paper (Polaris and Musca) supports the idea that highly dynamic processes are necessary for [C II] excitation in UV-faint low-density regions.

This conference poster takes up the European recommendation (EU 2023/498), which proposes 57 individual measures to improve standardisation training and strategy in the European Research Area. To implement these measures, it is proposed to install "standardisation representatives" at universities and research institutions. Checklists and audit questions for their tasks can be requested from the first author. This could increase the sufficient standardisation competence of university graduates from the current estimated 1 percent many times over.

In the coming years, the European Union plans to establish Proton Exchange Membrane (PEM) electrolyzers, each with a 100 MW capacity. However, the selection of their locations has not been systematically optimized to leverage potential benefits, such as utilizing waste heat from large facilities for district heating. Presently, there are hardly any corresponding system models in the literature dynamically simulating a PEM electrolyzer of this size. This paper introduces a first model approach for such systems, drawing on parameters from existing literature. It addresses the inconsistency found in the literature regarding the use of the exchange current density, which varies by a factor of . A novel optimization process is developed by using an auxiliary parameter to fit the exchange current density with a newfound condition between the anode and cathode side. The outcome is a comprehensive model of a PEM electrolyzer plant, exemplarily adapted to the Siemens Silyzer 300.

Biometric authentication plays a vital role in various everyday applications with increasing demands for reliability and security. However, the use of real biometric data for research raises privacy concerns and data scarcity issues. A promising approach using synthetic biometric data to address the resulting unbalanced representation and bias, as well as the limited availability of diverse datasets for the development and evaluation of biometric systems, has emerged. Methods for a parameterized generation of highly realistic synthetic data are emerging and the necessary quality metrics to prove that synthetic data can compare to real data are open research tasks. The generation of 3D synthetic face data using game engines’ capabilities of generating varied realistic virtual characters is explored as a possible alternative for generating synthetic face data while maintaining reproducibility and ground truth, as opposed to other creation methods. While synthetic data offer several benefits, including improved resilience against data privacy concerns, the limitations and challenges associated with their usage are addressed. Our work shows concurrent behavior in comparing semi-synthetic data as a digital representation of a real identity with their real datasets. Despite slight asymmetrical performance in comparison with a larger database of real samples, a promising performance in face data authentication is shown, which lays the foundation for further investigations with digital avatars and the creation and analysis of fully synthetic data. Future directions for improving synthetic biometric data generation and their impact on advancing biometrics research are discussed.

This study addresses the common occurrence of cell-to-cell variations arising from manufacturing tolerances and their implications during battery production. The focus is on assessing the impact of these inherent differences in cells and exploring diverse cell and module connection methods on battery pack performance and their subsequent influence on the driving range of electric vehicles (EVs). The analysis spans three battery pack sizes, encompassing various constant discharge rates and nine distinct drive cycles representative of driving behaviours across different regions of India. Two interconnection topologies, categorised as “string” and “cross”, are examined. The findings reveal that cross-connected packs exhibit reduced energy output compared to string-connected configurations, which is reflected in the driving range outcomes observed during drive cycle simulations. Additionally, the study investigates the effects of standard deviation in cell parameters, concluding that an increased standard deviation (SD) leads to decreased energy output from the packs. Notably, string-connected packs demonstrate superior performance in terms of extractable energy under such conditions.

Force field (FF) based molecular modeling is an often used method to investigate and study structural and dynamic properties of (bio-)chemical substances and systems. When such a system is modeled or refined, the force field parameters need to be adjusted. This force field parameter optimization can be a tedious task and is always a trade-off in terms of errors regarding the targeted properties. To better control the balance of various properties’ errors, in this study we introduce weighting factors for the optimization objectives. Different weighting strategies are compared to fine-tune the balance between bulk-phase density and relative conformational energies (RCE), using n-octane as a representative system. Additionally, a non-linear projection of the individual property-specific parts of the optimized loss function is deployed to further improve the balance between them. The results show that the overall error is reduced. One interesting outcome is a large variety in the resulting optimized force field parameters (FFParams) and corresponding errors, suggesting that the optimization landscape is multi-modal and very dependent on the weighting factor setup. We conclude that adjusting the weighting factors can be a very important feature to lower the overall error in the FF optimization procedure, giving researchers the possibility to fine-tune their FFs.

Pipeline transport is an efficient method for transporting fluids in energy supply and other technical applications. While natural gas is the classical example, the transport of hydrogen is becoming more and more important; both are transmitted under high pressure in a gaseous state. Also relevant is the transport of carbon dioxide, captured in the places of formation, transferred under high pressure in a liquid or supercritical state and pumped into underground reservoirs for storage. The transport of other fluids is also required in technical applications. Meanwhile, the transport equations for different fluids are essentially the same, and the simulation can be performed using the same methods. In this paper, the effect of control elements such as compressors, regulators and flaptraps on the stability of fluid transport simulations is studied. It is shown that modeling of these elements can lead to instabilities, both in stationary and dynamic simulations. Special regularization methods were developed to overcome these problems. Their functionality also for dynamic simulations is demonstrated for a number of numerical experiments.

The lattice Boltzmann method (LBM) stands apart from conventional macroscopic approaches due to its low numerical dissipation and reduced computational cost, attributed to a simple streaming and local collision step. While this property makes the method particularly attractive for applications such as direct noise computation, it also renders the method highly susceptible to instabilities. A vast body of literature exists on stability-enhancing techniques, which can be categorized into selective filtering, regularized LBM, and multi-relaxation time (MRT) models. Although each technique bolsters stability by adding numerical dissipation, they act on different modes. Consequently, there is not a universal scheme optimally suited for a wide range of different flows. The reason for this lies in the static nature of these methods; they cannot adapt to local or global flow features. Still, adaptive filtering using a shear sensor constitutes an exception to this. For this reason, we developed a novel collision operator that uses space- and time-variant collision rates associated with the bulk viscosity. These rates are optimized by a physically informed neural net. In this study, the training data consists of a time series of different instances of a 2D barotropic vortex solution, obtained from a high-order Navier–Stokes solver that embodies desirable numerical features. For this specific text case our results demonstrate that the relaxation times adapt to the local flow and show a dependence on the velocity field. Furthermore, the novel collision operator demonstrates a better stability-to-precision ratio and outperforms conventional techniques that use an empirical constant for the bulk viscosity.