Fakultät für Elektrotechnik und Informatik
https://www.repo.uni-hannover.de/handle/123456789/4
Frei zugängliche Publikationen aus der Fakultät für Elektrotechnik und Informatik2024-03-29T05:33:09ZStatus Quo Analysis of German Airports Regarding Fuel Infrastructure and Hydrogen Development Opportunities
https://www.repo.uni-hannover.de/handle/123456789/16934
Status Quo Analysis of German Airports Regarding Fuel Infrastructure and Hydrogen Development Opportunities
Fruhstorfer, Cordia; Bienefeld, Julia; Schenke, Finn
This study explores the feasibility of transitioning the aviation sector to green hydrogen as part of efforts to achieve net-zero CO2 emissions by 2050. Emphasizing the role of Sustainable Aviation Fuels and direct use of hydrogen as fuel, the study examines the current state of German airport infrastructure and outlines the challenges associated with adopting hydrogen as an alternative fuel source. Despite optimistic projections, the lack of practical experience with hydrogen supply at German airports underscores the need for infrastructure development and research. Through a detailed analysis of airport organization, fuel supply infrastructure, and potential impacts on hydrogen supply, the study provides insights into the transformative potential of green hydrogen in aviation and identifies key areas for future research and development.
2024-01-01T00:00:00ZUnterstützung der Manuskripterstellung mithilfe strukturiertem wissenschaftlichem Wissen
https://www.repo.uni-hannover.de/handle/123456789/16935
Unterstützung der Manuskripterstellung mithilfe strukturiertem wissenschaftlichem Wissen
Ludwig, Oliver
In den letzten Jahren ist die Anzahl veröffentlichter wissenschaftlicher Publikationen stark angestiegen. Da die meisten Veröffentlichungen in schriftlicher Form vorliegen, können gesammelte Ergebnisse nur schwer von Maschinen verwendet werden. Auch der Vergleich verschiedener Arbeiten ist zeitintensiv und erfordert ein menschliches Eingreifen. Um diesen Herausforderungen zu begegnen, wurde der Open Research Knowledge Graph (ORKG) entwickelt, um Wissen aus wissenschaftlichen Publikationen in einen maschinenlesbaren Wissensgraphen zu strukturieren. Diese Arbeit untersucht, wie Autoren mithilfe einer Software unterstützt werden können, die passende Visualisierungen generiert, wenn strukturierte Daten eingegeben werden. Ziel ist es, eine Implementierung zu entwickeln, die Autoren dazu anregt, Ergebnisse ihrer wissenschaftlichen Arbeiten in Wissensgraphen wie dem ORKG zu integrieren. Anhand eines im Rahmen dieser Arbeit erstellten Microsoft Word Add-Ins wird gezeigt, wie mithilfe strukturierter Daten und ORKG-Templates Visualisierungen automatisch erstellt werden können. Dabei wurde beobachtet, dass eine solche Umsetzung eine große Unterstützung für den Nutzer sein kann und effiziente Darstellungen generiert werden können. Eine besondere Eigenschaft der generierten Visualisierungen ist, dass sie sich leicht innerhalb des Dokuments verändern lassen, ohne diese neu generieren zu müssen. Trotz der erfolgreichen Ergebnisse sind weitere Anpassungen des implementierten Systems erforderlich, um eine vollständige Unterstützung aller Funktionalitäten und eine ausreichende Menge an Visualisierungen zu gewährleisten.; In recent years, the number of published scientific publications has significantly increased. As most publications are only published as an written Manuscript, collected results are challenging for machines to utilize. Additionally comparisons of different works are time-consuming and require human intervention. To address these challenges, the Open Research Knowledge Graph (ORKG) was developed to structure informations from scientific publications into a machine-readable knowledge graph. This Thesis explores how authors can be supported by software that generates appropriate visualizations when structured data is given. The aim is to develop an implementation that encourages authors to integrate results of their scientific work into knowledge graphs like the ORKG. A Microsoft Word Add-In created as a part of this work, demonstrates how visualizations can be automatically generated using structured data and ORKG templates. It was observed that such an implementation can greatly support users and efficiently generate representations. A notable feature of the generated visualizations is their ability to easily be edited within the document without requiring regeneration. Despite the successful results, further adjustments to the implemented system are necessary to ensure full support of all functionalities and a sufficient amount of visualizations.
2024-03-01T00:00:00ZResource-Efficient Gigawatt Water Electrolysis in Germany—A Circular Economy Potential Analysis
https://www.repo.uni-hannover.de/handle/123456789/16912
Resource-Efficient Gigawatt Water Electrolysis in Germany—A Circular Economy Potential Analysis
Matz, Levin; Bensmann, Boris; Hanke-Rauschenbach, Richard; Minke, Christine
Green hydrogen will play a key role in the future energy system. For the production of green hydrogen, an installation of alkaline (AWE) and proton exchange membrane water electrolysis (PEMWE) of several gigawatts per year is projected in the upcoming decades. The development of the hydrogen economy is associated with a great demand for scarce and expensive resources. To reduce resource demand and avoid supply bottlenecks, actions toward a circular economy are required. In the present study, three circular economy actions (repair, reuse, and recycling) are analyzed with regard to AWE and PEMWE installation taking Germany as an example. It is found that, so far, only recycling is a viable strategy for a circular economy. For further analysis, a model is developed to assess the impact of recycling on resource demand for AWE and PEMWE scale-up. Mass flows from end-of-life recycling are intergrated into the model, and their economic value is estimated. The results imply that closed-loop recycling can reduce the cumulated primary resource demand by up to 50% in the long run. However, recycling will first be relevant after 2040, while water electrolysis capacities installed before still depend on primary materials. The outlook on the economic value of the recycling materials indicates a volume of up to 2.15 B € per decade for PEMWE and 0.98 B € per decade for AWE recycling. To realize the potential, a recycling industry specialized for those technolgies considering the whole value chain covering dismantling, collection, and recycling must be introduced.
2024-01-01T00:00:00ZBlind extraction of guitar effects through blind system inversion and neural guitar effect modeling
https://www.repo.uni-hannover.de/handle/123456789/16905
Blind extraction of guitar effects through blind system inversion and neural guitar effect modeling
Hinrichs, Reemt; Gerkens, Kevin; Lange, Alexander; Ostermann, Jörn
Audio effects are an ubiquitous tool in music production due to the interesting ways in which they can shape the sound of music. Guitar effects, the subset of all audio effects focusing on guitar signals, are commonly used in popular music to shape the guitar sound to fit specific genres or to create more variety within musical compositions. Automatic extraction of guitar effects and their parameter settings, with the aim to copy a target guitar sound, has been previously investigated, where artificial neural networks first determine the effect class of a reference signal and subsequently the parameter settings. These approaches require a corresponding guitar effect implementation to be available. In general, for very close sound matching, additional research regarding effect implementations is necessary. In this work, we present a different approach to circumvent these issues. We propose blind extraction of guitar effects through a combination of blind system inversion and neural guitar effect modeling. That way, an immediately usable, blind copy of the target guitar effect is obtained. The proposed method is tested with the phaser, softclipping and slapback delay effect. Listening tests with eight subjects indicate excellent quality of the blind copies, i.e., little to no difference to the reference guitar effect.
2024-01-01T00:00:00Z