OPUS - Publikationenserver der Technischen Hochschule Nürnberg Georg Simon Ohm
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A Novel Quasi-Dimensional Model for Transient Mixing Prediction in Two-Phase Multicomponent Sprays under Flash-Boiling Conditions
No full textA novel one-dimensional multiphase and multicomponent spray model - hereafter referred to as the Kattke-Weigand model - has been developed to predict the penetration length of both vapor and liquid gasoline sprays under flash-boiling conditions, such as superheated injections. Its formulation is based on mass and momentum equations for unsteady jets and is therefore capable of capturing dynamic effects. Experiments were conducted in a constant volume chamber using various ambient and fuel temperature conditions and a six-hole GDI injector with a separated jet. Macroscopic spray parameters were extracted from the measurements to verify the model's ability to predict both liquid and vapor penetration length and the corresponding spray angles. Apart from the separated jet of the injector used, the other five jets interact strongly with each other under flash boiling conditions, resulting in spray collapse, and thus affecting spray characteristics. The prediction of collapse is very sensitive to calculations of vaporization and air entrainment. Since these submodels cannot be validated directly, a calibration method was developed, that is based on a three- dimensional reconstruction of all fuel sprays of the injector used. For this purpose, all optical measurements performed in the constant volume chamber are utilized. As a result, a three-dimensional representation of the spray collapse can be calculated from the combination of the 3D spray reconstruction and the entrainment and vaporization submodels. The validation of the collapse leads indirectly to the calibration of the entrainment and vaporization submodels in the Kattke Weigand model. Latter is applied to gain a deeper understanding of the interaction between spray collapse and both liquid and vapor phase penetration
Psychiatriekritik auf die Straße bringen. Mad Pride-Paraden und Blaue Karawane als Arbeit an der Multiplizität
No full textIm Mittelpunkt dieses Beitrags stehen performative Artikulationen von Psychiatriekritik bei Demonstrationen: Wir betrachten Mad Pride-Paraden, die in verschiedenen deutschen Städten seit 2013 durchgeführt werden, in Relation zu Aktionen der Bremer „Blauen Karawane“ – einer Bewegung, die in den 1980er Jahren im Zuge der Auflösung einer psychiatrischen Großklinik entstand. Obwohl sie in unterschiedlichen zeitlich-lokalen Kontexten situiert sind, setzen beide auf Formen des Straßenprotests, um die Grenzziehung zwischen „normal“ und „verrückt“ infrage zu stellen und die gleichberechtigte Anerkennung psychischer Alterität voranzubringen. Eine detaillierte Untersuchung der Aktionsformen unterstreicht die Bedeutung von karnevaleskem Feiern, Provokationen und Spektakel für beide Formen der Psychiatriekritik. Wir argumentieren, dass diese Formen Kritik erfahrbar und zugleich Entwürfe einer anderen – besseren – Gesellschaft greifbar machen. Um diese Aspekte herauszuarbeiten, greifen wir auf queer- und gendertheoretische Überlegungen sowie auf Ansätze der Performance Studies zurück. Die Betrachtung von Mad Pride-Paraden und Blauer Karawane in ihren jeweiligen Kontexten offenbart Ähnlichkeiten in der Art und Weise, wie Kritik am Ausschluss von psychischer Alterität geübt wird, macht aber auch Unterschiede in Hinblick auf Betroffenheit, Teilhabe und Argumentationen deutlich
Laser color marking of stainless steel – Investigation of the fluence-dependent and thermal mechanisms in generating laser induced surface modifications
No full textLaser color marking is an attractive process to generate functional, aesthetic and durable colorations on various suitable metals such as stainless steel or titanium. The color generation is mainly based on interference effects on thin oxide layers, usually induced by nanosecond pulsed laser irradiation. Due to the large number of mutually influencing processing parameters and different thermal, chemical, structural and topological influences on the coloring results, the process is still not fully understood. Moreover, the reproducibility of the markings and the processing times often do not meet the requirements of industrial manufacturing processes. To improve the understanding of the underlying phenomena comparable colors are generated using different parameter sets. Spectroscopic, microscopic and SEM/EDS analyzes are carried out to investigate the effects of the surface topology, oxide layer properties, chemical composition and heat accumulation on the marking results
Entwicklung und Charakterisierung eines Erbium-dotierten Glasfasersensors zur Temperaturmessung
No full textIt’s Time to Take Action: Acoustic Modeling of Motor Verbs to Detect Parkinson’s Disease
No full textPre-trained models generate speech representations that are used in different tasks, including the automatic detection of Parkinson’s disease (PD). Although these models can yield high accuracy, their interpretation is still challenging. This paper used a pre-trained Wav2vec 2.0 model to represent speech frames of 25ms length and perform a frame-by-frame discrimination between PD patients and healthy control (HC) subjects. This fine granularity prediction enabled us to identify specific linguistic segments with high discrimination capability. Speech representations of all produced verbs were compared
w.r.t. nouns and the first ones yielded higher accuracies. To gaina deeper
understanding of this pattern, representations of motor and non-motor verbs were compared and the first ones yielded better results, with accuracies of around 83% in an independent test set. These findings support well-established neurocognitive models about action-related language highlighted as key drivers of PD. Index Terms: computational paralinguistics, interpretability of pre-trained models, action verbs, Parkinson’s diseas
Comparing the Ideation Quality of Humans With Generative Artificial Intelligence
No full textTraditionally, ideating new product innovations is primarily the responsibility of marketers, engineers, and designers. However, a rapidly growing interest lies in leveraging generative artificial intelligence (AI) to brainstorm new product and service ideas. This study conducts a comparative analysis of ideas generated by human professionals and an AI system. The results of a blind expert evaluation show that AI-generated ideas score significantly higher in novelty and customer benefit, while their feasibility scores are similar to those of human ideas. Overall, AI-generated ideas comprise the majority of the top-performing ideas, while human-generated ideas scored lower than expected. The executive's emotional and cognitive reactions were measured during the evaluation to check for potential biases and showed no differences between the idea groups. These findings suggest that, under certain circumstances, companies can benefit from integrating generative AI into their traditional idea-generation processes
Problem-Based E-Learning to Increase Motivationn of STEM-Students
No full textFirst semester students often face major challenges in adjusting to university studies. Inexperienced students may not appreciate the practical relevance of abstract, theoretical concepts taught using traditional, instructor-centered lectures. Furthermore, the rise of generative artificial intelligence (GenAI) can mislead some to believe they no longer need to exert effort to learn academic skills. To encourage students to engage in learning material and thus improve retention rates, two complementary teaching methods were integrated into a large, introductory course for first semester STEM students: Problem-Based Learning (PBL) and gamification. Problem-Based Learning was implemented to make the subject matter more meaningful by simulating a real world experience: How to start up a small business. This entrepreneurship task was simulated in an online game, to increase student motivation. Quantitative questionnaires of student motivation and experiences with e-learning were evaluated. Based on input obtained in expert interviews, a fictitious startup enterprise was designed to serve as the used case. An online e-learning game was developed, which leveraged gamification elements to try to increase motivation. Each phase of the startup process was represented as one level of the e-learning game. The e-learning game was tested by a group of first semester students. Their opinions were collected using an anonymous online survey. Aggregated results of the survey are discussed and plans for further research are presented
A closer look at social work field education in Germany: Reconstructing the “field education-arc of work”
No full textGoodbye Hello World - Research Questions for a Future CS1 Curriculum
No full textGenerative AI (GenAI) is currently capable of generating correct code for introductory level programming problems, and its performance is improving. We believe that this capability can be leveraged to improve student motivation, broaden students’ understanding of software development, and engage them in more authentic learning. We defined a set of assumptions about GenAI’s future capabilities (e.g., the ability to generate small pieces of code and to compose these pieces of code via user prompts) and engaged in a backcasting exercise to identify what else is needed to develop a CS1 course that places GenAI in a central role. Undertaking this thought experiment immediately revealed that aspects of the software development process usually reserved for later in the curriculum, such as requirements elicitation and design, could be introduced earlier in the process. With GenAI tools bearing the load of generating correct code snippets, students could focus on higher-level software design and construction skills and practice them in an authentic environment. Our thought experiment identified a set of questions that need to be addressed for such a course to actually exist, including questions about student preparation, and the ability of students to decompose problems effectively and to resolve problems that arise when integrating pieces of code. We also identified questions related to the design of a GenAI centered course, such as the impact on student motivation of using GenAI instead of engaging directly with code, the extent to which social learning theories apply to interactions with GenAI, and how existing pedagogies can integrate GenAI tools