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Informierte Souveränität: Leitplanken für Forschungssicherheit in der China-Kooperation
No full textVo
Cross second virial coefficients of the N₂–H₂, O₂–H₂, and CO₂–H₂ systems from first principles
No full textThis article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).The cross second virial coefficients B_12 for interactions of molecular nitrogen (N₂) with molecular hydrogen (H₂), of molecular oxygen (O₂) with H2, and of carbon dioxide (CO₂) with H₂ were obtained at temperatures ranging from 36 K to 2000 K for the former two systems and from 100 K to 2000 K for the latter system from new rigid-rotor intermolecular potential energy surfaces (PESs) for the three molecule pairs. Each PES is based on interaction energies calculated for a large number of pair configurations employing high-level quantum-chemical ab initio methods up to coupled cluster with single, double, triple, and perturbative quadruple excitations [CCSDT(Q)]. Core-core and core-valance correlation and relativistic effects were accounted for as well. B_12 values were extracted from the PESs classically and semiclassically using the Mayer-sampling Monte Carlo approach. The deficiencies of the semiclassical calculations at the lowest temperatures were partly remedied by a more rigorous treatment of translational quantum effects using the phase-shift method. The results for the N2–H2 and CO₂–H₂ systems are in excellent agreement with the most accurate experimental data. For the O₂–H₂ system, there are no experimental B_12 data because this mixture is highly explosive. There are, however, previous first-principles results for B_12 of this system by Van Tat and Deiters [Chem. Phys. 457, 171–179 (2015)], which were obtained at a much lower level of sophistication for both the PES and the method to extract B_12 and differ significantly from the present values.Vo
Comprehensive overview of the effective thermal conductivity for hydride materials
No full textThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).In metal hydride beds (MHBs), reaction heat transfer often limits the dynamic performance. Heat transfer within the MHB usually involves solid and gas phases. To account for both, an effective thermal conductivity (ETC) is defined. Measuring and predicting the ETC of metal hydride beds is of primary importance when designing hydride-based systems for high dynamics. This review paper presents an integral overview of the experimental and modeling approaches to characterize the ETC in MHBs. The most relevant methods for measuring the ETC of metal hydride beds are described, and the results and scopes are shown. A comprehensive description of the models applied to calculate the ETC of the MHBs under different conditions is developed. Moreover, the effects of operation parameters such as P, T, and composition on the ETC of the presented models are analyzed. Finally, a summary and conclusions about experimental techniques, a historical overview with a classification of the ETC models, a discussion about the needed parameters, and a comparison between ETC experimental and calculated results are provided.Vo
Prime ministers in Central and Eastern Europe
No full textPrime ministers are the most powerful and visible politicians in established parliamentary democracies. But is this also true for post-communist Central and Eastern Europe (CEE)? Conventional wisdom suggests that prime ministers in CEE perform weakly because they lack political experience and operate in an extraordinarily difficult context, but this assumption has not been systematically examined. To close this research gap, this book presents a new approach to measuring prime-ministerial performance and offers a novel dataset of 131 cabinets in eleven CEE countries between 1990 and 2018. Comparative analyses of this data reveal that post-communist prime ministers range from politically inexperienced outsiders to insiders with long-standing careers in parliament, government, and party leadership. Their institutional, political, and economic contexts are more favourable in some countries and periods than in others. Some incumbents have performed rather poorly, while others have been very successful. Moreover, analyses of quantitative data and qualitative cases demonstrate that the variations in the careers, contexts, and performance of prime ministers are systematically connected. Their success particularly depends on their experience as party leaders, on the strength of their political allies in the executive and legislative arenas, and on favourable economic conditions. In this way, the book not only qualifies conventional assumptions about prime ministers in CEE but also substantiates the theoretical relationship between their careers, contexts, and performance. Prime Ministers in Central and Eastern Europe thus contributes to an enhanced understanding of the functioning of post-communist democracies and provides new insights for scholarly work engaging with political leadership.Vo
An analysis of methods for emotion recognition via wearables
No full textDie automatische Erkennung von Emotionen mit Hilfe biologischer Signale ist ein sehr vielversprechendes Forschungsgebiet in den Gesundheitswissenschaften. Vor allem die fortschreitende Entwicklung von Wearables und Cloud-Computing ermöglicht eine kontinuierliche Erfassung der Daten und die Erkennung der Emotionen, welche helfen frühzeitige Diagnosen von psychologischen Erkrankungen wie Depression festzustellen. Ebenfalls können Therapiemethoden entsprechend dem psychologischen Wohlbefinden individuell angepasst/gestaltet werden. Gängige Sensordaten hierbei sind der Blutvolumenpuls, die Herzrate, die Herzraten-Varibilität, die Hautleitfähigkeit und die Hauttemperatur. Nach einer Filterung und (statistischen) Merkmalsextraktionen der Signale werden öfteres maschinelle Lernverfahren zur Klassifizierung benutzt (Support Vector Machines, K-Nearest-Neighbor, Random-Forest...). Neuerdings gibt es auch Forschungen für Deep-Learning Methoden wie Convolutional-Neural-Networks. Für die Emotionsklassifizierung gibt es zwei konkrete Emotionenmodelle, das diskrete, in welchem vorbestimmte Emotionen analysiert und das dimensionale, in welchem Emotionen als Kombination (Vektoren) aus mehreren Komponenten (Dimensionen) dargestellt werden. Hierbei ist das zwei dimensionale Model am gängigsten, in welchem eine Achse die Intensität und die andere die Polung der Emotion darstellt. In dieser Arbeit wurde mittels bereits durchgeführter Studien, welche das zwei dimensionale Model benutzt haben, unter Betrachtung der verfügbaren Sensoren analysiert, ob Wearables eine gute Basis für die Ermittlung von Emotionen darbieten. Die Analyse zeigt, dass Wearables vielversprechend sind und genaue Ergebnisse liefern können, jedoch müssen Daten sehr gut für die Klassifizierungsmethode vorbereitet werden. Zudem ist eine große Datenmenge und homogen verteilte Gruppe an Probanden notwendig. Es wird festgestellt, dass die Genauigkeit stark von den Probanden abhängt und Emotionen sehr subjektiv bewertet werden. Des weiteren scheint das vorgestellte zwei-dimensional Model nicht ausreichend zu sein und es wird eine Erweiterung vorgeschlagen, um bessere Grenzen zwischen ähnlichen Emotionen zu ziehen. Letztlich kann durch den Vergleich verschiedener Arbeiten angenommen werden, dass es nicht das genau Richtige oder die Beste Klassifizierungsmethode/Algorithmus gibt und für jede Datenmenge die beste Methode “erkundet” werden sollte.Automatic emotion recognition through physiological parameters is a promising research field in the health sciences. In particular, advancements in wearable technology and cloud computing enable continuous data collection and emotion recognition, which can aid in the early diagnosis of psychological disorders such as depression. Additionally, therapy methods can be customized/designed according to psychological well-being. Commonly used sensor data include blood volume pulse, heart rate, heart rate variability, skin conductance and skin temperature. After data filtering and (statistical) feature extraction, machine learning methods are often used for classification (Support Vector Machines, K-Nearest-Neighbor, Random-Forest...). Recently, there has also been research into deep learning methods such as convolutional neural networks. There are two specific emotion models for emotion classification, the discrete model, in which predefined emotions are analyzed and the dimensional model, in which emotions are described as a combination (vectors) of several components (dimensions). The two-dimensional model is the most common, in which one axis represents the intensity and the other represents the polarity of the emotion. This study investigates whether wearables provide a good basis for emotion recognition using the two-dimensional model. The analysis shows that wearables are promising and can provide accurate results, but data must be well prepared for the classification method. In addition, a large datasets and a homogeneously distributed group of test subjects is necessary. The accuracy heavily depends on the test subjects and emotions are very subjective. Furthermore, the presented two-dimensional model is not sufficient and an extension is proposed to differentiate between similar emotions. Finally, by comparing different works, it can be assumed that there is no single best classification method/algorithm and that the best method should be “explored” for each data set.Vo
Towards distributed network security monitoring in smart microgrids
No full textThe transition of power grids towards open, dynamic, and automated systems requires advanced network security monitoring approaches that comprehensively address emerging threats. These threats can range from targeted attacks on control systems to large-scale disruptions of critical energy infrastructure. The consequences of such attacks can be severe, leading to power outages, compromised energy supply stability, and threats to public safety. This concept paper proposes a decentralized network security monitoring approach designed explicitly for networked microgrids. Our solution monitors microgrids regarding communication networks and power infrastructure, combining information from all microgrid subsystems to detect threats early and automatically initiate countermeasures (e.g., isolating or shutting down the subsystem causing the attack). Furthermore, our approach facilitates the sharing of threat intelligence among microgrids, enhancing the resilience of individual microgrids and the overall power grid.Vo
Anthology for the workshop: developments and research results of the chair of electrical machines and drive systems 2024
No full textIn diesem Sammelband werden die aktuellen Entwicklungen und Forschungsergebnisse der Professur für Elektrische Maschinen und Antriebssysteme im Jahr 2024 vorgestellt.
Die Professur ist seit diesem Jahr Mitglied des neu gegründeten KI Institutes sowie des Forschungsschwerpunktes „Nachhaltige Energie“ der HSU.
An der Professur wurden vier Promotionen abgeschlossen und erfolgreich verteidigt. Das Thema der Dissertation von Herrn Matthias Kowalski lautet „Über Wirbelstromphänomene in Ständerstäben in Nutaustrittsbereichen leistungsstarker Turbogeneratoren“. Er entwickelt hierin eine effiziente Submodell-Methode zur genauen Berechnung von Wirbelstromverlusten und wendet diese sehr ausführlich für verschiedene Geometrien und Betriebspunkte an. Der zusätzlich entwickelte thermische Alterungsrechner bietet ein großes Potential, die Auslegung von großen elektrischen Maschinen weiter zu optimieren und auch die Alterung der Maschine während des Betriebs besser zu überwachen.
Herr Florian Dreishing hat zum Thema „Auslegung und methodische Entwicklung von biegeflexiblen elektrischen Linearmotoren” promoviert. Neben der Methodenentwicklung zur Auslegung hat Herr Dreishing auch die Fertigung und Regelung dieses neuartigen Antriebssystems umfänglich erforscht. Durch die Arbeit wurde ein signifikanter Erkenntnisgewinn auf dem Gebiet der biegeflexiblen Linearmotoren erzielt. Die Ergebnisse tragen dazu bei, neue Softrobotikanwendungen und Exoskelettlösungen zu erschließen.
Herr Florian Zellmer hat zum Thema „Methodenentwicklung zur Auslegung segmentierter Schienenbeschleuniger, welche mehrphasig betrieben werden können” promoviert. Durch den segmentierten Aufbau werden neue Anwendungsfelder im Transportbereich und für Testaufbauten erschlossen. Diese reichen vom schnellen Transport von beispielsweise Organen und Gewebeproben zwischen zwei medizinischen Zentren bis hin zur Beschleunigung von Mikrosatelliten.
Das Thema der Dissertation von Herrn Moritz Benninger lautet „KI-basiertes Monitoring und Diagnose von elektrischen Maschinen im industriellen Umfeld“. Durch die Arbeit von Herrn Benninger wurde ein signifikanter Fortschritt auf dem Gebiet der Fehlererkennung in elektrischen Maschinen erzielt. Die Ergebnisse tragen dazu bei, praxistaugliche, kostengünstige und automatisierte Monitoring und Diagnosesysteme für elektrische Maschinen zu entwickeln.
Die Beiträge des Sammelbandes setzen sich aus Fortschrittsberichten und Gastvorträgen zusammen, welche im Rahmen des jährlichen EMA Workshops am 05.12.2024 vorgestellt wurden.In this anthology, the current developments and research results of the Chair of Electrical Machines and Drive Systems in 2024 are presented. The chair became a member of the newly founded AI Institute and the research focus "Sustainable Energy" at HSU.
Four doctoral theses were completed and successfully defended at the chair. The topic of Mr. Matthias Kowalski's dissertation is „Über Wirbelstromphänomene in Ständerstäben in Nutaustrittsbereichen leistungsstarker Turbogeneratoren“. In this work, he develops an efficient submodel method for the precise calculation of eddy current losses and applies it extensively to various geometries and operating points. The additionally developed thermal aging calculator offers great potential to further optimize the design of large electrical machines and to better monitor the aging of the machine during operation.
Mr. Florian Dreishing completed his doctorate on the topic „Auslegung und methodische Entwicklung von biegeflexiblen elektrischen Linearmotoren”. In addition to the method development for design, Mr. Dreishing also extensively researched the manufacturing and control of this novel drive system. The work has led to significant insights in the field of bending-flexible linear motors. The results contribute to the development of new soft robotics applications and exoskeleton solutions.
Mr. Florian Zellmer completed his doctorate on the topic „Methodenentwicklung zur Auslegung segmentierter Schienenbeschleuniger, welche mehrphasig betrieben werden können”. The segmented design opens up new application fields in the transport sector and for test setups. These range from the rapid transport of, for example, organs and tissue samples between two medical centers to the acceleration of microsatellites.
The topic of Mr. Moritz Benninger's dissertation is „KI-basiertes Monitoring und Diagnose von elektrischen Maschinen im industriellen Umfeld“. Mr. Benninger's work has made significant progress in the field of fault detection in electrical machines. The results contribute to the development of practical, cost-effective, and automated monitoring and diagnostic systems for electrical machines.
The contributions of the anthology consist of progress reports and guest lectures, which were presented at the annual EMA Workshop on December 5, 2024.Vo
Konstruktive Optimierung der Spannungsfestigkeit am bestehenden Design des 110-kV-Netzimpedanzmesscontainers
No full textZur Messung der zeit- und frequenzabhängigen Netzimpedanz werden an der Professur für elektrische Energiesysteme der Helmut-Schmidt-Universität/Universität der Bundeswehr Hamburg mobile Messanlagen für die Mittel- und Hochspannung entwickelt. Diese Arbeit beschreibt den Lösungsansatz zum Erlangen der Spannungsfestigkeit der 110-kV-Messanlage unter dem Einsatz minimaler Mittel und der Verwendung des bestehenden Designs.Vo