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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.
The glass industry is facing increased challenges regarding climate protection targets and rising energy costs. The integration of renewable energy including conversion and storage is a key for both challenges in this energy-intensive industrial sector, which has been mainly relying on fossil gas so far. The options considered to this point for reducing CO2 emissions and switching to a renewable energy supply involve far-reaching changes of the established melting processes. This entails significant risks in terms of influences on glass quality and stable production volumes. The presented approach for the integration of a Power-to-Methane (PtM) system into the glass industry is a completely new concept and has not been considered in detail before. It allows the use of established oxyfuel melting processes, the integration of fluctuating renewable energy sources and a simultaneous reduction of CO2 emissions by more than 78%. At the same time, natural gas purchases become obsolete. A techno-economic evaluation of the complete PtM process shows, that 1,76 €/m3 or 1,26 €/kg synthetic natural gas are possible with renewable energy supply. Using electricity from the energy grid would require electricity prices < 0,126 €/kWh to allow cost competitive PtM processes in the glass industry. Such electricity prices could be achieved by electricity market-based optimization and operation of the PtM system. This operation strategy would require AI-based algorithms predicting availabilities and prices on future-based markets.
Dual front steering axles are quite common in multi-axled heavy duty trucks. In standard layouts of such axle combinations, the steer motions of the wheels depend not only on the rotation of the steering wheel but also on the movements of the axles. As a consequence, the model complexity of the steering system should match with the complexity of the suspension model. The development of new technologies like advanced driver assistance systems or autonomous driving can only be accomplished efficiently using extensive simulation methods. Such kind of applications demand for computationally efficient vehicle models. This paper presents a steering system model for dual front axles of heavy duty trucks which supplements the suspension model of the axles. The model takes the torsional compliance of the steering column as well as the stiffness of the tie rods and the coupling rod into account. A quasi-static solution provides a straight forward computation including the partial derivatives required for an efficient implicit solver. The steering system model matches perfectly with comparatively lean, but sufficiently accurate multibody suspension models.
Acoustic emission (AE) testing recently found its application in the wafer testing sector of the semiconductor industry. To find out the mechanical robustness of semiconductor devices, contact pads on the chip surface are intentionally overstressed with an indenter tip and the appearing oxide cracks are detected with help of the generated AE signals. This is done in a customized test bench with a patented sensor-indenter system. This paper presents an improved version of the measurement setup that solves certain disadvantages of it and can be used in a standard wafer prober. The main components of the developed sensor system are a strain gauge for contact force measurement and a piezoelectric sensor element for AE signal detection. Both components are integrated on a cantilever beam which has an exchangeable indenter tip at its free end. The cantilever probe is electrically conductive to enable electrical tests via the indenter tip. This smart sensor-cantilever combination (SCC) can be mounted with several adapter components on a carrier plate to place it in a wafer prober. For both sensor elements amplifier circuits are developed to enhance their signal-to-noise ratios (SNRs). A prototype setup is shown together with simulated and experimental results to demonstrate its performance. The mechanical properties of the cantilever, as well as the force sensor and the AE crack signals, already fulfill the requirements for an implementation in a wafer prober. To further improve the sensor resolutions and detection limits, several optimizations regarding the design of the SCC are in progress.
Industrial plants can provide reactive power (Q) for system- and grid-serving behavior, for which a functioning reactive power management system is essential. To make reactive power retrieval as efficient and safe as possible, the selection of reactive power sources to meet the Q-demand must consider their sensitivities and the restrictions of the industrial grid, such as operating equipment utilization or voltage limits. On this basis, a concept for a sensitivity-based control strategy that manages the reactive power retrieval of multiple reactive power sources depending on a predefined reactive power demand value is proposed. Based on the simulation of an industrial plant in the medium-voltage grid, which can provide reactive power in the form of industrial compensation systems (ICS) and generators, the operation of the algorithm is shown.
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.
The laminated steel core of transformers is one of the main sources of the generated sound, as it is excited by different electromagnetic effects during its normal operation. If the core is excited in its eigenfrequencies, the sound generated by a transformer will increase significantly. Therefore, knowledge of the core’s eigenmodes and -frequencies in an early design stage can decrease expenses by avoiding costly modifications that might be required to avoid the sound levels exceeding the specified values after the final factory acceptance test. The current study focuses on developing a core resonance model to determine the eigenmodes and -frequencies of a transformer core. The core’s geometry was simplified to a connected-beam structure and a numerical-based approach was applied. The accuracy of the developed model was validated against finite element method (FEM), using ANSYS on a reference core model.
During the factory acceptance test, the sound levels are measured. If the measured sound levels exceed pre-specified values, modifications on the transformer’s active part and/or tank need to be conducted. Tank resonance, if occurs, at twice main power frequency and its higher harmonics is one of the main reasons of amplifying the generated sound levels. Therefore, it is preferable to know already in the design stage about the occurrence of the tank resonance and propose reliable tank solutions. The current study presents a newly developed model for calculating the mode shapes and its corresponding eigenfrequencies of the tank.
Um einen sicheren und zuverlässigen Stromnetzbetrieb zu gewährleisten, muss die Spannung im Grundfall als auch bei ungeplanten Ausfällen in definierten Bereichen gehalten werden. Im Übertragungsnetz wird hierfür bisher Blindleistung hauptsächlich aus Blindleistungskompensationsanlagen und konventionellen Großkraftwerken eingesetzt. Zukünftig wird nach §12h EnWG eine marktgestützte Beschaffung dieser Dienstleistung zur Spannungsregelung vorgeschrieben. Zugleich verändert sich der Blindleistungsbedarf der Netzbetriebsmittel durch die Integration erneuerbarer Energieanlagen und der Elektromobilität sowie durch den Netzausbau bei Übertragungs- und Verteilungsnetzbetreibern. Es bedarf somit angepasster Netzbetriebs- und Netzplanungskonzepte für ein technisch effizientes und wirtschaftlich günstiges Blindleistungsmanagement. Dieser Beitrag beschäftigt sich damit, Prozessansätze und Methodiken für ebendieses in der Netzplanung aufzuzeigen, um erforderliche Blindleistungskapazitäten unter minimalen Gesamtkostenaufwand und unter Berücksichtigung einer effizienten Blindleistungsbedarfsdeckung zu bestimmen. Dabei liegt der Fokus verstärkt in der Bedarfsanalyse.
Im Zuge der Energiewende ergibt sich ein Wandel in der Struktur des Elektrizitätsversorgungsnetzes. Die Verschiebung der Erzeugungsleistung von konventionellen Großkraftwerken in höheren Netzebenen hin zu dezentralen erneuerbaren Energieanlagen in niedrigeren Netzebenen resultiert sowohl in bidirektionalen Lastflüssen als auch in schwankenden Einspeisecharakteristiken. Des Weiteren folgen durch den Wegfall von Großkraftwerken als Blindleistungsquellen Leistungsdefizite in der Übertragungsnetzebene, die kompensiert werden müssen. Daraus resultieren Herausforderungen an einen sicheren und zuverlässigen Betrieb der Verteil- und Übertragungsnetze. Neue Konzepte müssen für die Erbringung von Blindleistung entwickelt werden, es soll mehr Blindleistung aus dem Verteilungsnetz zur Verfügung gestellt werden, um die Systemstabilität zu wahren. Im Rahmen des Projektes Q-Integral wird das Thema „Blindleistung“ (Q) ganzheitlich untersucht. Es werden dazu verschiedene Erbringungsoptionen für Blindleistung hinsichtlich technischer und wirtschaftlicher Potentiale untersucht, die in ein funktionales und effizientes Blindleistungsmanagement eingebracht werden. Die Untersuchungsansätze dafür sind sowohl spannungsebenen-übergreifend als auch netzbetreiber-übergreifend. Ein Ansatzpunkt des Projektes ist die Betrachtung der Blindleistungsbereitstellung von Industriebetrieben. Dazu wird das Potential von Betrieben, die an das Verteilnetz angeschlossen sind und Blindleistung durch Kompensations- oder Erzeugungsanlagen bereitstellen können, untersucht. Ziel ist es, das gesicherte und maximale induktive sowie kapazitive Potential zu bestimmen. Das gesicherte kapazitive Potential kann genutzt werden, um Aussagen darüber zu treffen, wie stark dem Spannungsfall im vorgelagerten Netz zu Starklastzeiten entgegengewirkt werden kann. Anhand des gesicherten induktiven Potentials kann ein Spannungsanstieg während Schwachlastzeiten ausgeglichen werden kann. In diesem Beitrag werden Ergebnisse aus dem Projekt Q-Integral vorgestellt. Dazu werden zuerst die Berechnungsgrundlagen der induktiven und kapazitiven Blindleistungspotentiale aufgezeigt und die Ergebnisse der Berechnungen vorgestellt. Die gewonnen Ergebnisse entstammen aus Messungen an einem Industriebetrieb mit Blindleistungskompensationsanlagen (BKA), den entsprechenden Reglern der Anlagen und einer installierten Kompensationsleistung von 1600 kvar. Sowohl die Lastgänge als auch das Schaltverhalten der einzelnen Kompensationsanlagen liegen den Berechnungen zugrunde. Um den Austausch der Blindleistung an der Übergabestelle des Betriebs zum Mittelspannungsnetz netzdienlich einzustellen, bedarf es eines geeigneten Regelkonzepts, das neben den BKAs auch weitere Q-Quellen berücksichtigt. Deshalb wird abschließend ein Regelkonzept vorgestellt, das den technisch-optimierten Blindleistungsabruf unter Berücksichtigung mehrerer Blindleistungsquellen behandelt.