Hochschule Bonn-Rhein-Sieg
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Zweite Änderungsordnung vom 23. Oktober 2025 der Fachbereichsordnung für den Fachbereich Angewandte Naturwissenschaften am Standort Rheinbach der Hochschule Bonn-Rhein-Sieg vom 20. Januar 2022
No full textBalancing Biodiversity and Economic Viability: Farmers' Motivations and Challenges in Nature-Protected Areas
No full textBiodiversity loss is one of the most urgent environmental challenges, particularly in nature-protected areas (NPAs), where agriculture and conservation come together. Farmers play a central role in land management and can significantly influence ecological outcomes through their practices. Despite the agricultural sector being widely recognised as having an impact on biodiversity, participation in conservation efforts is inconsistent and the levels of commitment are often insufficient. This study looks at the economic, social, and psychological drivers that influence farmers' engagement in biodiversity conservation within NPAs, using Maslow's Hierachy of Needs as an analytical framework.
The research is based on a unique triangulation of complementary qualitative and quantitative findings derived from the "Diversity of Insects in Nature-Protected Areas (DINA)"-project and its subsequent associated studies, which examine farmers' land use trilemma, hesitations and aspirations. The DINA-project was funded by the Federal Ministry of Education and Research (BMBF) as part of the Action Programme for Insect Conservation. Together, these empirical data sources collected provide a multi-faceted understanding of the factors influencing farmers' willingness to implement biodiversity-friendly practices. Applying Maslow's model to the agricultural sector provides a structured approach to understanding how economic security, regulatory stability, social belonging, recognition, and self-actualization collectively determine farmers' decision-making processes.
By integrating psychological theory with solid empirical evidence from the DINA-project and its related studies, this research offers a comprehensive framework for understanding the complex motivational factors and constrains that farmers deal with in biodiversity conservation. The findings demonstrate that effective interventions have to address the full spectrum of farmers' needs, from economic security to self-actualization, and also that they have to be integrated into a supportive social and regulatory environment. Combining Maslow's motivational theory with empirical insights produced by the research streams provides a comprehensive basis for designing targeted, flexible, and socially embedded conservation incentives that align with the realities of farming life. In conclusion, the study recognises that a meaningful and sustainable engagement with biodiversity conservation in NPAs depends on a holistic understanding of farmers' needs and motivations. Only by addressing these needs in a structured and integrated manner can policymakers strengthen the long-lasting commitment necessary to biodiversity-friendly practices
GaN-HighPower "Kosten- und gewichtseffiziente PV- und Batterie-Wechselrichter großer Leistung für internationale Märkte der Zukunft durch Gallium-Nitrid (GaN) Halbleiter"; Teilvorhabenbeschreibung der VACUUMSCHMELZE GmbH & Co KG: Entwicklung und Bereitstellung von Induktivitäten und Stromsensoren: Schlussbericht der VAC zu GaN-HighPower
No full textZiel des Verbundforschungsvorhabens GaN-HighPower ist es, die nächste Generation kostengünstiger, ressourcenschonender und effizienter Stromrichter für Photovoltaikanwendungen zu erforschen und zu erproben, wobei der Fokus auf Stringwechselrichter mit größerer Leistung im Bereich von 150 kVA liegt. Hierfür sollen Galliumnitrid (GaN) Halbleitermodule zusammen mit anwendungsorientiert stark verbesserten induktiven Bauelementen und Stromsensoren erforscht und erprobt werden. Im Rahmen von GaN-HighPower wurde dazu ein Demonstrator-Inverter aufgebaut. Im Zuge dessen wurde gezeigt, dass mit dem anvisierten Konzept der gekoppelten Induktivitäten eine Gewichtseinsparung von 50% realisiert wurde. Zum einen wurde diese Einsparung durch die magnetische Kopplung erzielt, zum anderen durch den Einsatz von nanokristallinen Bandmaterial mit niedriger Permeabilität und niedrigen Verlusten. Die Erhöhung der Schaltfrequenz hatte ebenfalls einen Beitrag, jedoch zeigte sich bei der Betrachtung des Gesamtsystems eine optimale Schaltfrequenz bei 70kHz anstatt der bei der Antragstellung anvisierten 140kHz. Durch die Erhöhung der Gesamt-Leistungsdichte des Inverters, ist es möglich Material einzusparen und Ressourcen zu schonen. Bei der Übertragung dieser Erkenntnisse in die Serie, kann der PV-Standort Deutschland durch die Entwicklung effizienterer PV-Wechselrichter gestärkt werden. Im Zuge der Entwicklung des Demonstrator-Inverters wurde weiterhin ein closed-loop Stromsensor mit hoher Bandbreite und höher Genauigkeit entwickelt, der es ermöglicht Ströme bis 800kHz zuverlässig zu messen. Dieser Sensor ist bereit zur Einführung in die Serie für PV-Inverter der nächsten Generation mit schnellschaltenden GaN Halbleitern. Diese Möglichkeit stärkt den Umsatz im PV-Geschäft und damit den Standort Deutschland. Es wurden alle anvisierten Meilensteine innerhalb des Projektvorhabens und innerhalb der Projektverlängerung erfüllt.The aim of the GaN-HighPower joint research project is to research and test the next generation of cost-effective, resource-saving and efficient power converters for photovoltaic applications, with a focus on string inverters with power in the 150 kVA range. For this, gallium nitride (GaN) semiconductor modules are to be researched and tested together with application-oriented greatly improved inductive components and current sensors. Therefore, a demonstrator inverter was built within GaN-HighPower project. It was shown that a weight saving of 50% was achieved with the envisaged concept of coupled inductors. On the one hand, this saving was achieved by magnetic coupling, and on the other hand, by the use of nanocrystalline strip material with low permeability and low losses. The increase in the switching frequency also had a contribution, but when looking at the overall system, an optimal switching frequency of 70 kHz instead of the 140 kHz envisaged in the application was found. By increasing the overall power density of the inverter, it is possible to save material and conserve resources. When transferring these findings to series production, Germany can be strengthened as a PV location by developing more efficient PV inverters. Within the development of the demonstrator inverter, a closed-loop current sensor with high bandwidth and high accuracy was also developed, which makes it possible to reliably measure currents up to 800kHz. This sensor is ready to be introduced into series production for next-generation PV inverters with fast-switching GaN semiconductors. This opportunity strengthens sales in the PV business and thus Germany as a business location. All targeted milestones within the project and within the project extension were met
Machine-learning-enhanced collision operator for the lattice Boltzmann method based on invariant networks
No full textIntegrating machine learning (ML) techniques in established numerical solvers represents a modern approach to enhance computational fluid dynamics simulations. Within the lattice Boltzmann method (LBM), the collision operator serves as an ideal entry point to incorporate machine learning (ML) techniques to enhance its accuracy and stability. In this work, an invariant neural network is constructed, acting on an equivariant collision operator, optimizing the relaxation rates of nonphysical moments. This optimization enhances robustness to symmetry transformations and ensures consistent behavior across geometric operations. The proposed neural collision operator (NCO) is trained using forced isotropic turbulence simulations driven by spectral forcing, ensuring stable turbulence statistics. The desired performance is achieved by minimizing the energy spectrum discrepancy between direct numerical simulations and underresolved simulations over a specified wave number range. The loss function is further extended to tailor numerical dissipation at high wave numbers, ensuring robustness without compromising accuracy at low and intermediate wave numbers. The NCO's performance is demonstrated using three-dimensional Taylor-Green vortex (TGV) flows, where it accurately predicts the dynamics even in highly underresolved simulations. Compared to other LBM models, such as the BGK and KBC operators, the NCO exhibits improved accuracy while maintaining stability. In addition, the operator shows robust performance in alternative configurations, including turbulent three-dimensional cylinder flow. Finally, an alternative training procedure using time-dependent quantities is introduced. It is based on a reduced TGV model along with newly proposed symmetry boundary conditions. The reduction in memory consumption enables training at significantly higher Reynolds numbers, successfully leading to stable yet accurate simulations
Validierung neuer Betriebsverfahren und Sicherstellung der Interoperabilität in lokalen Energienetzen – die „Sandbox Ortsnetze“
No full textTogether for a Sustainable, Climate-Resilient, and Liveable Green Campus – Education for Sustainable Development (ESD) at the Hochschule Bonn Rhein-Sieg - A case study
No full textThis paper outlines the implementation of the interdisciplinary course “Green Campus: Together for a Sustainable, Climate-Resilient, and Livable University” with the objective of engaging students in developing ideas for a sustainable campus by building ESD competencies, such as active participation and reflective and critical thinking. It employed a problem-based learning approach to generate ideas on climate adaptation, waste management, and noise pollution. The framework for the course was based on the UN Sustainable Development Goals (SDGs), the climate adaptation strategy of the city of Sankt Augustin, and the sustainability strategy and infrastructure plans for a Green Campus at Hochschule Bonn Rhein-Sieg (H-BRS). To facilitate this, students conducted independent research in groups, used relevant crowd-sourcing apps and measuring devices, collected and mapped data, conducted interviews and surveys, and engaged with local stakeholders, including other students and representatives of the university’s facility and sustainability management
Severe Cases of Odontogenic Abscesses, Next-Generation Sequencing Searching for Superpathogens. Case Series and Review of Current Literature
No full textObjectives
This paper aimed to identify possible causes of complications in odontogenic abscesses. In particular, infections with specific pathogens should be highlighted.
Materials and Methods
We report on two young patients with odontogenic abscesses who required an extended hospitalization in the intensive care unit due to serious local (Lemierre's syndrome, mediastinitis) and systemic complications. During the extraoral abscess incision, we obtained sequencable wound swabs and carried out genetic microbiological diagnostics using next-generation sequencing (NGS) searching for superpathogens. Besides the conducted analysis, the article summarises the current literature on the microbiome of odontogenic abscesses and its analysis using gene-based microbiological techniques.
Results
Microbiological analysis revealed a polymicrobial infection characterised by anaerobic bacteria with microorganisms such as Prevotella or Peptostreptococcus in both patients. In addition, the particularly virulent pathogen Fusobacterium necrophorum was detected in one patient.
Conclusions
Infections with specific pathogens such as Fusobacterium necrophorum should be considered as possible triggers of complications in patients with odontogenic abscesses. Gene-based microbiological analysis is a valid and rapid technique for pathogen detection and should be used in particular for atypical, severe treatment courses in order to enable pathogen detection and targeted antibiotic therapy
Explainability Analysis for Skill Execution
No full textExplainability holds significant importance for autonomous robots deployed in human-centered situations, particularly when errors occur during execution. In the context of robot action, it is important to consider various levels and types of explainability. The social dimension of Artificial Intelligence (AI) and robotic explanations, which highlights how they affect social interaction, values, and decision-making, has received little to no attention in prior research. With a particular emphasis on item handover, we hypothesize that users prefer systems with explanations and that explanations in natural language are more appealing than heatmaps. A user study, involving participants from diverse backgrounds and levels of expertise, is conducted to evaluate different levels and preferred types of explainability. The study results support our hypotheses and offer additional valuable information for future system development
A Methodological Approach to Sustainable Product Development by Combining Life Cycle Assessment and Systems Enginieering
No full textProduct requirements and the reduction of its ecological footprint are often in conflict with each other. However, sustainable development is seen to be important as shown by international agreements. Environmental improvement of a product, e.g. with material substitution, might change a product-significant physical parameter. Therefore, a methodology is conducted which combines the result of Life Cycle Assessment with modelling and simulation concepts to design an environmentally friendly and physically functional product. By applying life cycle impact data to different system model configurations, their results can be compared to show a more sustainable product design, mitigating global warming for example. This is achieved by linking Life Cycle Assessment to the topology of a system in a five-step method. The conducted five-step method consists of Life Cycle Assessment, hotspots, data sorting, system topology and solutions. The developed method enables the identification of materials and components with high environmental impact already in early design stages, even before the physical product exists. This allows targeted decisions for sustainable design by evaluating environmental performance alongside functional requirements at a conceptual level