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In einer vorrangegangenen Studie wurde der Einfluss psychoakustischer Parameter auf Präferenzurteile für konsonante und dissonante Geräusche untersucht. Diese Geräusche hatten die gleiche Lautheit und basierten auf einem festen Rauschhintergrund und eingebetteten hochfrequenten Tonkomponenten. Es zeigte sich, dass die Präferenzurteile eines Probandenkollektives durch ebenfalls erhobene Subjektivurteile zu Schärfe, Tonhaltigkeit und Dissonanz mit hoher Präzision vorhergesagt werden konnten.Durch das angewandte Versuchsdesign konnte diese rein auf Subjektivbeurteilungen bestehende Vorhersage mit einer instrumentellen Vorhersage der Präferenzurteile verglichen werden. Der Vergleich ergab einen niedrigeren Korrelationskoeffizienten für die modellbasierte Vorhersage, was auch durch die sehr niedrige Korrelation (R2<0,2) der berechneten Schärfe nach DIN45692 mit den Schärfe-Subjektivurteilen zu begründen war. Eine mögliche Erklärung der unzureichenden Prognose der Schärfeurteile könnte in der Bewertungsstrategie der Proband:innen zu finden sein. Für die getesteten Geräusche mit auffälligen tonalen Komponenten könnte statt der Schärfe des Gesamtgeräuschs nur die Schärfe des tonalen Geräuschobjekts berücksichtigt worden sein. Die Schärfe-Analyse der auf ihren tonalen Anteil reduzierten Signale zeigt eine sehr gute Übereinstimmung mit den Subjektivurteilen, was die Hypothese einer Trennung von Ton- und Rauschobjekten unterstützt. Es wird diskutiert, ob und wie das Paradigma der akustischen Objekttrennung in der Modellierung psychoakustischer Empfindungsgrößen Anwendung finden kann.
An electric traction machine for an electric or a hybrid electric vehicle is usually designed for a specific operating point or cycle. For such an operating point or cycle, the masses and the cooling circuit of the electric machine determine the time dependent temperature distribution within the machine. For a specific load cycle, the thermal simulation of the machine can reveal possible mass and size reductions for a given insulation class of the machine. In addition, such simulations allow the comparison of various cooling concepts. In the machine design process, the first step is a conventional electromagnetic machine design. From the geometric data of this design and the material properties, the parameters of a thermal equivalent circuit can be derived. The differential and algebraic equations of the thermal equivalent circuit are solved by a simulation tool to predict the temperatures of the critical parts in the electric machine. A thermal equivalent circuit is accurate enough to predict the thermal behavior of the critical parts in the electric machine, and yet not too complex, to obtain simulation results with moderate numerical effort. This enables an iterative design process to optimize the drive.
A magnetic levitation system is a perfect educational example of a nonlinear unstable system. Only with suitable control, a small permanent magnet can be held floating stable below a coil. After modeling and simulation of the system, control of the system can be developed. At the end, the control algorithm can be coded on a microcontroller, connected to a pilot plant.
As global demand for green hydrogen rises, potential hydrogen exporters move into the spotlight. However, the large-scale installation of on-grid hydrogen electrolysis for export can have profound impacts on domestic energy prices and energy-related emissions. Our investigation explores the interplay of hydrogen exports, domestic energy transition and temporal hydrogen regulation, employing a sector-coupled energy model in Morocco. We find substantial co-benets of domestic climate change mitigation and hydrogen exports, whereby exports can reduce domestic electricity prices while mitigation reduces hydrogen export prices. However, increasing hydrogen exports quickly in a system that is still dominated by fossil fuels can substantially raise domestic electricity prices, if green hydrogen production is not regulated. Surprisingly, temporal matching of hydrogen production lowers domestic electricity cost by up to 31% while the effect on exporters is minimal. This policy instrument can steer the welfare (re-)distribution between hydrogen exporting firms, hydrogen importers, and domestic electricity consumers and hereby increases acceptance among actors.
Automated use of wired measures in grid planning for solving current and voltage band problems
(2019)
This work deals with the use of cable exchange and parallel cabling as network expansion measures in the context of an automated grid planning for the elimination of current and voltage band problems in a distribution network. Inter alia, reference is made to a higher-level program, which is being developed in the EU project "CrossEnergy", and the procedures for remedying the limit value violations are presented.
Im Rahmen der vier Kopernikus-Projekte – Ariadne, ENSURE, P2X und SynErgie – wird die Transformation des deutschen Energiesystems hin zur Klimaneutralität analysiert. Im vorliegenden Bericht werden hierbei robuste Kernaussagen und relevante Unsicherheiten derjenigen Szenarien der Kopernikus-Schwesterprojekte dargestellt, die zur Zielsetzung die Klimaneutralität 2045 haben. Hierbei liegt der Fokus auf Indikatoren, die eine besonders hohe klimapolitische Relevanz haben.
Analysis and Improvement of Engineering Exams Toward Competence Orientation by Using an AI Chatbot
(2024)
ChatGPT is currently one of the most advanced general chatbots. This development leads to diverse challenges in higher education, like new forms of teaching and learning, additional exam methods, new possibilities for plagiarism, and many more topics. On the other side with the development of advanced AI tools, pure knowledge will be less and less important, and demands from industry will change toward graduates with higher competencies. Education has therefore to be changed from knowledge-centered toward competence centered. The goal of this article is to use ChatGPT for analyzing and improving the competence orientation of exams in engineering education. The authors use ChatGPT to analyze exams from different engineering subjects to evaluate the performance of this chatbot and draw conclusions about the competence orientation of the tested exams. The obtained information is used to develop ideas for increasing the competence orientation of exams. From this analysis, it is visible that ChatGPT gives good performance mainly where knowledge is tested. It has, however, much more problems with transfer questions or tasks where students need creativity or complex insights for finding new solutions. Based on this result, exams and also lectures can be optimized toward competence orientation.
Increasingly stringent emission limits have made particulate filters necessary for gasoline engines. Similar to diesel applications, gasoline particulate filters (GPFs) can be monitored by differential pressure measurement or by the radio-frequency-based filter diagnosis (RF sensor). In addition to measuring the soot loading, ash detection is critical for monitoring the GPF over the entire vehicle lifetime. Because the RF sensor detects the filter loading through a change in the dielectric properties of the GPF, it can detect not only soot but also ash. In diesel applications, the RF sensor has already demonstrated its potential for ash detection. To verify the feasibility of simultaneous ash and soot monitoring for GPFs, filters were loaded with ash on an engine test bench and measured on a lab test bench under defined synthetic exhaust gas conditions. By evaluating resonant modes, soot and ash could be clearly distinguished, as ash mainly affects the resonant frequency, while soot also changes the quality factor due to its high dielectric losses. However, higher soot loadings could not be detected by the resonant parameters, but instead by a frequency-averaged transmission signal. While the presence of ash caused an offset in this signal, its sensitivity to soot was not affected. Thus, the influence of ash can be corrected if the signal in the soot-free filter state is known, e.g., from the behavior of the resonant parameters. Therefore, even with a continuously increasing ash loading over the lifetime of a vehicle, an accurate soot detection is possible with the RF sensor.