OPUS - Publikationenserver der Technischen Hochschule Nürnberg Georg Simon Ohm
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Exploring New Frontiers in Multi-Material Additive Manufacturing
No full textMulti-Material Additive Manufacturing (MMAM) introduces a new dimension to production technologies by seamlessly integrating multiple materials into a single object, enabling unparalleled design possibilities. This paper explores MMAM value chains and methods and showcases real-world applications in the aerospace, biomedical and industrial sectors. While MMAM holds promise for application in high-tech industries, its widespread adoption is contingent on quantity, utilization and technical requirements. Continued research into developing material properties and reducing unit costs is needed. Only once these two key challenges have been addressed is mainstream adoption likely
Dynamic accelerated stress test and coupled on-line analysis program to elucidate aging processes in proton exchange membrane fuel cells
No full textAbstractThe application of hydrogen proton exchange membrane fuel cells (PEMFC) in greenhouse gas emission free heavy-duty vehicles requires extremely durable PEMFC components with service lives in the range of 30,000 h. Hence suitable test and analysis methods are required that reflect realistic operation scenarios, but significantly accelerate aging. For this purpose, a dynamic accelerated stress test was developed, which is coupled with a comprehensive in-depth in-situ and ex-situ analysis program to determine the aging processes of a PEMFC membrane electrode assembly (MEA). The test comprehends dynamic cycling between low, moderate and high load, different temperature and humidity conditions as well as recovery sequences to distinguish between reversible and irreversible failure modes. All phases of the PEMFC system (i.e. solid, liquid and gaseous) are monitored on-line during aging by sophisticated electrochemical, mass spectrometric and ion chromatographic analytical methods. The structural and elemental composition of the MEA before and after the aging program (post-mortem) are investigated by X-ray fluorescence, scanning and transmission electron microscopy. This program was able to age a commercial PEMFC to end-of-life in 1000 h, while providing an accurate picture of the aging processes involved
Improved energy transfer model for mechanistic scale-up of stirred media mills
No full textWet-operated stirred media mills are commonly used in the field of fine and ultra-fine grinding. Depending on the application, there are different mill geometries, sizes and mill equipment materials of which the grinding chamber lining and the stirrer are made. Increasing energy prices demand an energy-efficient mill operation for a desired product, which can be achieved with mechanistic stress models. Here, besides the mill geometry and volume, the process parameters and various energy-transfer-coefficients are of importance. In this work, the impact of different mill equipment materials affecting the mill-related-energy-transfer-coefficients on performance prediction and scale-up using the advanced stress model are investigated. It was found that the mill-related-energy-transfer-coefficients as well as the improved grinding-media-energy-transfer-coefficients have a significant effect on the prediction precision of the comminution times and specific energies for chosen target particle sizes
Startup Behavior of Harmonic Suppression in Electrical Machines Using Iterative Learning Control and Neural Networks
No full textElectrical machines generate unwanted flux and current harmonics. Harmonics can be suppressed by using various methods. In this paper, the harmonics are reduced by using iterative learning control (ILC) and neural networks (NNs). This paper focuses on the startup behavior of the control system. The ILC can compensate well for the harmonics in operation at constant speed and constant current reference values, but needs multiple rotations to learn. The NNs are trained with the data from the ILC and help to suppress the harmonics well even in transient operation and from the first rotation. The simulation model is based on flux and torque maps, depending on dq-currents and the electrical angle. The methods are also applied on the test bench and measurement results are presented
Doing Housing First und Wohnraumakquise
No full textWohnungslosigkeit ist in Deutschland ein bestehendes Phänomen extremster Armut. Der in den USA entwickelte Ansatz Housing First wird als Paradigmenwechsel in der Wohnungsnotfallhilfe diskutiert, indem er am dringendsten Bedarf wohnungsloser Menschen im Hilfeprozess als Erstes ansetzt: der bedingungslosen Bereitstellung einer eigenen Wohnung. Der Housing First-Ansatz wurde bereits in den USA, Kanada und europäischen Ländern erfolgreich erprobt und stellt das Menschenrecht auf Wohnen sowie die Selbstbestimmung im gesamten Hilfeprozess in den Vordergrund. Auch in Deutschland etablierten sich in den vergangenen Jahren Housing First-Modellprojekte. Ziel des explorativen Forschungsvorhabens ist es, Erkenntnisse über die Selbstverständnisse, Perspektiven und Aushandlungen zentraler Akteur*innen sowie Mechanismen der Umsetzung von solchen Modellprojekten in Nordbayern zu gewinnen, die sich als Housing First-Projekte verstehen. Dabei steht weder eine Testung der Prinzipientreue, noch die Prüfung der Mindestansprüche von Housing First-Projekten im Vordergrund der Betrachtung. Vielmehr sollen anhand qualitativer Forschungsmethoden die individuellen Erfahrungen, subjektiven Deutungen und Relevanzsetzungen der zentralen Akteur*innen im Umgang und Aushandeln mit den Housing First-Grundprinzipien in ihren Modellprojekten vor Ort rekonstruiert werden. Berücksichtigt werden die Perspektiven von Initiator*innen, Fachkräften der Wohnraumakquise, Sozialarbeiter*innen, (ausgeschiedenen) neuen Mieter*innen sowie Vermieter*innen. Die leitfadengestützten verstehenden Interviews werden mithilfe von inhaltsanalytischen sowie rekonstruktiven Methoden ausgewertet
Sustainable Development Goals (SDGs) im Hochschulkontext
Get PDFDie bestehenden Verknüpfungen von Hochschulaktivitäten mit den SDGs werden aufgrund einer Analyse der dazu im Sommersemester 2021 vorliegenden Infor-mationen von allen deutschen Universitäten, Fachhochschulen und Pädagogischen Hochschulen zusammengestellt. Diese Verknüpfungen werden zudem für 35 ausländische Hochschulen sowie für hochschulübergreifende Ansätze betrachtet. Oftmals spielen die SDGs gerade auch an deutschen Hochschulen in der Außen-darstellung noch keine oder nur eine untergeordnete Rolle. Z. T. werden die Bezüge zu den SDGs aber auch systematisch hergestellt. Die unterschiedlichen Herangehens-weisen können in Stufenschemata eingeordnet werden. Die bereits vorliegenden Vorschläge für Indikatoren zur Beschreibung dieser Bezüge zeigen die Möglichkeit auf, in ihrer Verbindung zu einem umfassenden System von Kenngrößen zu kommen. Der Bezug zu den konkreten Unterzielen der SDGs ist jedoch nur rudimentär ausgebildet
Wer löscht morgen? Engagement und Freiwillige Feuerwehr
No full textRund 320.000 Aktive leisten in den Feuerwehren Bayerns ehrenamtlich einen Beitrag zur kommunalen Daseinsvorsorge. Die empirische Studie analysiert Einflussfaktoren einer nachhaltigen Sicherung dieses Engagements, das sich absehbar wandelt. Ein multimethodisches Forschungsdesign verbindet standardisierte Befragungen der Aktiven, qualitative Interviews sowie demografische Projektionen in den Regionen. Analytischer Rahmen ist das Konzept des »Strategischen Freiwilligenmanagements«. Als Beitrag zur Engagementforschung werden empirisch fundiert konkrete praxisorientierte Handlungsimpulse für die Zukunft dieser Daseinsvorsorge durch Freiwillige Feuerwehren abgeleitet
Machine Learning in Industrial Quality Control of Glass Bottle Prints
No full textIn industrial manufacturing of glass bottles, quality control of bottle prints is necessary as numerous factors can negatively affect the printing process. Even minor defects in the bottle prints must be detected despite reflections in the glass or manufacturing-related deviations. In cooperation with our medium-sized industrial partner, two ML-based approaches for quality control of these bottle prints were developed and evaluated, which can also be used in this challenging scenario. Our first approach utilized different filters to supress reflections (e.g. Sobel or Canny) and image quality metrics for image comparison (e.g. MSE or SSIM) as features for different supervised classification models (e.g. SVM or k-Neighbors), which resulted in an accuracy of 84%. The images were aligned based on the ORB algorithm, which allowed us to estimate the rotations of the prints, which may serve as an indicator for anomalies in the manufacturing process. In our second approach, we fine-tuned different pre-trained CNN models (e.g. ResNet or VGG) for binary classification, which resulted in an accuracy of 87%. Utilizing Grad-Cam on our fine-tuned ResNet-34, we were able to localize and visualize frequently defective bottle print regions. This method allowed us to provide insights that could be used to optimize the actual manufacturing process. This paper also describes our general approach and the challenges we encountered in practice with data collection during ongoing production, unsupervised preselection, and labeling
Automatic Evaluation of a Sentence Memory Test for Preschool Children
No full textAssessment of memory capabilities in preschool-aged children is crucial for early detection of potential speech development impairments or delays. We present an approach for the automatic evaluation of a standardized sentence memory test specifically for preschool children. Our methodology leverages automatic transcription of recited sentences and evaluation based on natural language processing techniques. We demonstrate the effectiveness of our approach on a dataset comprised of recited sentences from preschool-aged children, incorporating ratings of semantic and syntactic correctness. The best performing systems achieve an F1 score of 91.7% for semantic correctness and 86.1% for syntactic correctness using automatic transcripts. Our results showcase the potential of automated evaluation systems in providing reliable and efficient assessments of memory capabilities in early childhood, facilitating timely interventions and support for children with language development needs