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Theoretical considerations on 2D multistable tensegrity structures based on equilateral triangles
(2025)
This paper investigates the stability and stiffness characteristics of two-dimensional tensegrity structures based on two equilateral triangles connected by tensioned members, resulting in three multistable structural variants. The stability analysis is conducted by examining the system’s potential energy. Using a form-finding algorithm, the study reveals how the stiffness of tensioned members impacts global compliance distribution and the transition between equilibrium positions. By adjusting the stiffness of individual members and varying force application points, significant modifications in the overall stiffness of the structure can occur. The study shows that increasing the force amplitude can lead to equilibrium position changes, particularly in asymmetrical structures. These findings provide valuable insights for designing adaptable, stiffness-tunable structures. The results emphasize the critical role of force direction, stiffness distribution, and transitions between stable equilibrium states in the development of advanced mechanical systems.
This paper investigates the influence of the roller geometry and the manufacturing tolerances on the wear behavior of a short and wide flat-belt conveyor with three rollers, using the frictional power density as a qualitative wear indicator. Previous studies mainly focus on overall belt dynamics and wear with ideal cylindrical rollers. This work emphasizes the effect of geometric deviations arising from manufacturing or intentional shaping. Building upon an existing lumped mass model of the belt and a visualization approach of the frictional power density, the model is extended by a deflection-based roller geometry that enables the analysis of concave and convex roller profiles. The study reveals that small deviations from an ideal cylindrical roller significantly influence the distribution of frictional power density across the belt width. Convex roller geometries particularly increase edge wear, while concave rollers reduce it up to a certain point before it rises again. For the investigated three-roller system, the authors therefore propose a slightly concave roller geometry with a narrow tolerance band as a pragmatic trade-off between reduced frictional power density and belt-run stability, the latter being a known effect of concave roller geometries. These insights enhance the understanding of how geometric tolerances affect belt deformation and wear behavior. They establish a consistent framework for deriving design guidelines and conducting future parameter studies involving belt tension, speed, and alternative roller geometries.
Achieving climate neutrality requires large-scale production of green hydrogen and its derivatives. A persistent cost gap between producers and offtakers, however, impedes market growth. Our study couples European-African energy markets to analyse the role of the H2Global mechanism in bridging this gap, employing sector-coupled energy models. We find that no analysed pathway is cost-competitive in 2030, with African export costs (140-229 €/MWh) exceeding European willingness to pay (40-100 €/MWh) for hydrogen, ammonia, and methanol. The required annual funding ranges between 0.6 and 11.4 billion €. By 2050, early-stage support enables a market entry and the ramp-up of a hydrogen and Power-to-X economy: trade volumes of up to 236 TWh become cost-competitive, potentially reaching 450 TWh through reinvested savings. We conclude that, although ambitious European climate targets are the main reason for market ramp-up, the H2Global mechanism is a key and cost-effective instrument for overcoming the initial 'chicken-and-egg' problem, enabling market creation and ramp-up.
Adaptive learning environments aim to enhance student engagement and learning efficiency by tailoring educational content to individual needs. This paper presents a modular tool landscape designed to extend a learning management system like Moodle with adaptive learning paths based on learner profiles. To this end, the proposed architecture integrates multiple AI-driven tools - like Bayesian networks and Markov models - to generate personalized learning paths. The framework is implemented as a Moodle plugin named Pythia, which facilitates the selection and sequencing of learning elements by analyzing learning styles, completion data, and learning analytics.
The main goal of this work is to provide lecturers a modular architecture for an adaptive learning management system that can be used and expanded the way they want it. Therefore, the present work has the following contributions: The architecture with its tools has to be discussed on the basis of flexibility in tool integration. They should be open for extensions, the functionality of the used algorithms should be transparent, and they should offer the possibility of psychological questionnaire integration.
Dieses qualitative Forschungsprojekt untersucht die Mitwirkung von
Frauen in der Regensburger Zivilgesellschaft und analysiert zentrale
Hindernisse sowie Förderfaktoren auf individueller und organisatorischer
Ebene. Die Grundlage der Untersuchung bilden fünf leitfadengestützte
Interviews mit Frauen, die sich für die Belange ihrer Mitbürgerinnen
engagieren. Einer der zentralen Akteure, die im Rahmen der Studie
betrachtet wurden, ist der Katholische Deutsche Frauenbund (KDFB).
Die Ergebnisse verdeutlichen, dass das Engagement von Frauen
in Regensburg maßgeblich von sozialen Rahmenbedingungen,
organisatorischen Strukturen und individuellen Lebenssituationen
geprägt wird. Zu den größten Hindernissen zählen die geringe
Sichtbarkeit von Frauenthemen, traditionelle Rollenbilder, begrenzte
finanzielle Ressourcen sowie zeitliche und emotionale Belastungen.
Gleichzeitig zeigen die Interviews, dass insbesondere die Gemeinschaft
mit anderen Frauen sowie die Erfahrung von Wirksamkeit und
Anerkennung zentrale Faktoren darstellen, die Engagement trotz
bestehender Herausforderungen ermöglichen und fördern.
Auf Grundlage dieser Erkenntnisse formuliert die Arbeit einen
handlungsorientierten Vorschlag, der Organisationen dabei unterstützen
kann, das Engagement von Frauen sichtbarer zu machen und
nachhaltige Beteiligungsstrukturen zu stärken. Eine gemeinsame
Sichtbarkeitskampagne Regensburger Frauenvereine unter dem Titel
„Frauen bewegen Regensburg“ kann die Vernetzung zwischen Vereinen
und einzelnen engagierten Frauen fördern, als Grundlage für zukünftige
gemeinsame Projekte dienen und die Bedeutung des Engagements von
Frauen für die Regensburger Zivilgesellschaft hervorheben.
Advanced Persistent Threats (APTs) pose a growing challenge to critical infrastructure security. Their extended timescales, stealth, and multi-stage tactics limit the effectiveness of traditional Network Intrusion Detection Systems (NIDS), as signature-based methods miss novel techniques and anomaly detection alone produce a flood of low-confidence, low-specificity events. We propose a system that combines unsupervised anomaly detection with automated, large language model (LLM)-driven investigation to analyze suspicious network flows and reconstruct attack paths from network-level observations. Flagged flows are examined at both the feature and payload level using a locally hosted language model. Investigation results are aggregated in a graph database to reconstruct the attack progression through the network. Evaluation on the CICAPT-IIoT dataset shows that the system identifies all labeled malicious flows while uncovering mislabeled traffic containing clear indicators of compromise, suggesting detection capability without prior attack knowledge. We further discuss risks introduced by deploying language models in security-critical applications, including prompt injection via malicious payloads and data poisoning attacks.
Global warming and geopolitical challenges underscore the need for adapted and strengthened energy partnerships within and beyond Europe. While the European Green Deal provides a common framework, open questions remain on how national objectives and cross-border synergies can be jointly realized. This research presents a pathway for a Franco–German energy transition towards 2050 and unlocks the potential of energy partnerships within Europe, by using a cost-based, sector-coupled optimization model. Both countries are coupled through an isolated country optimization approach. Thus, the focus is on the development of each national energy system. The results highlight the increase of energy security in line with the European Green Deal. The main pillars of the energy transition are solar energy (32%–33%), wind energy (25%–38%) and biogenic energy sources (13%–27%). Nuclear power will be phased out in Germany and France. Efficiency
improvements reduce final energy demand by nearly 50%, with electricity playing a key role both directly and indirectly through PtX products. System stability is ensured through large-scale storage deployment, in particular batteries, pumped hydro and hydrogen cavern storage. Moreover, France can cost-effectively supply
25% of Germany’s hydrogen import needs (122 TWh) in 2050. At the same time, France can also benefit from the energy partnership in terms of economic growth and joint action to mitigate climate crisis.
PV and wind systems with PEM electrolysis offer great potential for producing hydrogen with low emissions. Our research has identified the ecologically optimal size of PEM in relation to fixed PV/wind capacities. We calculate efficiencies and production volumes for PEM with 240 capacity and site variations. We analyse the global warming potential of all systems and draw conclusions about the optimal system design. The lowest GWP is achieved at the site with the highest full load hours with 1.32 kg CO2-eq/kg H2 (Wind, 28 MW electrolysis) and 4.24 kg CO2-eq/kg H2 (PV, 23 MW electrolysis). We have identified a clear trend: increasing PV/wind full load hours leads to higher ideal PEM capacities. However, there is a significant discrepancy between the ideal economic and ecological capacity. Furthermore, higher electrolysis capacities can achieve lower emissions as they increasingly operate at a more efficient partial load.
Knitted textile antennas hold significant promise for wearable communication and sensing; however, designing and evaluating them requires simulation workflows that balance accuracy with computational efficiency. This study reviews knitted antennas and introduces a novel approach based on hybrid yarns with embedded microwires. Most textile antennas reported to date are fabricated using metallized polyamide fibers; however, this study focuses on the design, simulation, and realization of antennas based on so-called hybrid yarns containing embedded microwires, which exhibit significantly lower electrical resistance – by several orders of magnitude – compared to metallized polyamide yarns. Waveguide measurements reveal anisotropic permittivity and highlight the influence of material composition and knit geometry. These data are implemented in CST Studio Suite through an Effective Material Approach (EMA) that enables the emulation of real-world antenna behavior without modeling every individual yarn. A bowtie antenna serves as a representative design, simulated using the EMA and compared against both a solid silver simulation model and experimental measurements. Despite minor deviations, the results validate the approach and lay the groundwork for future design guidelines for knitted textile antennas. To illustrate the application potential, two demonstrators are presented: a knitted bowtie frequency resonator for wearable strain monitoring, and a wireless data-transmission link using knitted antennas with a textile LED readout.
The authors’ analysis of determinants of household electricity consumption is based on the 2018 Survey of Income and Expenditure (EVS), using Germany as an example. The EVS survey covered all variables identified through a scoping review, including the number and type of appliances, sociodemographic, and dwellingrelated aspects. This large representative dataset allows analyzing the effect of these determinants on electricity expenditure for German households. Expenditure on electricity is considered a reliable indicator of household electricity consumption. The determinants show weak to moderate correlations with energy expenditure in bivariate analyses. Multivariate analysis clearly shows the combined effects of householdspecific, dwelling-related, and appliance-specific factors. Models considering only one aspect overestimate the respective effect. Thus, it is essential to consider all three aspects simultaneously when explaining residential electricity consumption.
The largest effects are found for electricity as the main energy source for heating, the number of household members, as well as their presence at home. Household structure is an important factor in explaining residential energy consumption while dwelling and appliance-related aspects also have an effect. Appropriate policy measures may affect the latter aspects.
