05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access Quantitative analysis of the sensitivity of UHF sensor positions on a 420 kV power transformer based on electromagnetic simulation(2019) Beura, Chandra Prakash; Beltle, Michael; Tenbohlen, Stefan; Siegel, MartinWith an increasing interest in ultra-high frequency (UHF) partial discharge (PD) measurements for the continuous monitoring of power transformers, it is necessary to know where to place the UHF sensors on the tank wall. Placing a sensor in an area with many obstructions may lead to a decrease in sensitivity to the UHF signals. In this contribution, a previously validated simulation model of a three-phase 300 MVA, 420 kV power transformer is used to perform a sensitivity analysis to determine the most sensitive sensor positions on the tank wall when PD activity occurs inside the windings. A matrix of UHF sensors located on the transformer tank is used to perform the sensitivity analysis. Some of the windings are designed as layer windings, thus preventing the UHF signals from traveling through them and creating a realistic situation with very indirect propagation from source to sensor. Based on these findings, sensor configurations optimized for UHF signal sensitivity, which is also required for PD source localization, are recommended for localization purposes. Additionally, the propagation and attenuation of the UHF signals inside the windings and the tank are discussed in both oil and air.Item Open Access Software Engineering und CASE - Begriffserklärung und Standortbestimmung(1991) Ludewig, JochenCASE-Tools werden heute als wichtige Mittel der Leistungs- und Qualitätssteigerung im Software Engineering betrachtet. Diese Einschätzung ist richtig, wenn sie mittel- und langfristig verstanden wird; sie ist falsch, wenn man erwartet, rasche Hilfe zu bekommen, die Versäumnisse in der Methodik und Schulung ausgleicht. Die heute angebotenen Werkzeuge weisen charakteristische Mängel auf, die - entgegen den Ankündigungen - ihren durchgehenden Einsatz sehr schwer machen. Trotzdem kann unter bestimmten Voraussetzungen, auch organisatorischen, die Qualität des Entwicklungsprozesses tatsächlich erhöht werden. Diese Verbesserung wirkt sich auch auf die Produktivität aus.Item Open Access Additively manufactured transverse flux machine components with integrated slits for loss reduction(2022) Kresse, Thomas; Schurr, Julian; Lanz, Maximilian; Kunert, Torsten; Schmid, Martin; Parspour, Nejila; Schneider, Gerhard; Goll, DagmarLaser powder bed fusion (L-PBF) was used to produce stator half-shells of a transverse flux machine from pure iron (99.9% Fe). In order to reduce iron losses in the bulk components, radially extending slits with a nominal width of 150 and 300 µm, respectively, were integrated during manufacturing. The components were subjected to a suitable heat treatment. In addition to a microscopic examination of the slit quality, the iron losses were also measured using both a commercial and a self-developed measurement setup. The investigations showed the iron losses can be reduced by up to 49% due to the integrated slits and the heat treatment.Item Open Access Top‐down approach to study chemical and electronic properties of perovskite solar cells : sputtered depth profiling versus tapered cross‐sectional photoelectron spectroscopies(2021) Das, Chittaranjan; Zia, Waqas; Mortan, Claudiu; Hussain, Navid; Saliba, Michael; Ingo Flege, Jan; Kot, MałgorzataA study of the chemical and electronic properties of various layers across perovskite solar cell (PSC) stacks is challenging. Depth‐profiling photoemission spectroscopy can be used to study the surface, interface, and bulk properties of different layers in PSCs, which influence the overall performance of these devices. Herein, sputter depth profiling (SDP) and tapered cross‐sectional (TCS) photoelectron spectroscopies (PESs) are used to study highly efficient mixed halide PSCs. It is found that the most used SDP‐PES technique degrades the organic and deforms the inorganic materials during sputtering of the PSCs while the TCS‐PES method is less destructive and can determine the chemical and electronic properties of all layers precisely. The SDP‐PES dissociates the chemical bonding in the spiro‐MeOTAD and perovskite layer and reduces the TiO2, which causes the chemical analysis to be unreliable. The TCS‐PES revealed a band bending only at the spiro‐MeOTAD/perovskite interface of about 0.7 eV. Both the TCS and SDP‐PES show that the perovskite layer is inhomogeneous and has a higher amount of bromine at the perovskite/TiO2 interface.Item Open Access Efficient exploratory clustering analyses in large-scale exploration processes(2021) Fritz, Manuel; Behringer, Michael; Tschechlov, Dennis; Schwarz, HolgerClustering is a fundamental primitive in manifold applications. In order to achieve valuable results in exploratory clustering analyses, parameters of the clustering algorithm have to be set appropriately, which is a tremendous pitfall. We observe multiple challenges for large-scale exploration processes. On the one hand, they require specific methods to efficiently explore large parameter search spaces. On the other hand, they often exhibit large runtimes, in particular when large datasets are analyzed using clustering algorithms with super-polynomial runtimes, which repeatedly need to be executed within exploratory clustering analyses. We address these challenges as follows: First, we present LOG-Means and show that it provides estimates for the number of clusters in sublinear time regarding the defined search space, i.e., provably requiring less executions of a clustering algorithm than existing methods. Second, we demonstrate how to exploit fundamental characteristics of exploratory clustering analyses in order to significantly accelerate the (repetitive) execution of clustering algorithms on large datasets. Third, we show how these challenges can be tackled at the same time. To the best of our knowledge, this is the first work which simultaneously addresses the above-mentioned challenges. In our comprehensive evaluation, we unveil that our proposed methods significantly outperform state-of-the-art methods, thus especially supporting novice analysts for exploratory clustering analyses in large-scale exploration processes.Item Open Access Impedance based temperature estimation of lithium ion cells using artificial neural networks(2021) Ströbel, Marco; Pross-Brakhage, Julia; Kopp, Mike; Birke, Kai PeterItem Open Access Cross-lingual citations in English papers : a large-scale analysis of prevalence, usage, and impact(2021) Saier, Tarek; Färber, Michael; Tsereteli, TornikeCitation information in scholarly data is an important source of insight into the reception of publications and the scholarly discourse. Outcomes of citation analyses and the applicability of citation-based machine learning approaches heavily depend on the completeness of such data. One particular shortcoming of scholarly data nowadays is that non-English publications are often not included in data sets, or that language metadata is not available. Because of this, citations between publications of differing languages (cross-lingual citations) have only been studied to a very limited degree. In this paper, we present an analysis of cross-lingual citations based on over one million English papers, spanning three scientific disciplines and a time span of three decades. Our investigation covers differences between cited languages and disciplines, trends over time, and the usage characteristics as well as impact of cross-lingual citations. Among our findings are an increasing rate of citations to publications written in Chinese, citations being primarily to local non-English languages, and consistency in citation intent between cross- and monolingual citations. To facilitate further research, we make our collected data and source code publicly available.Item Open Access Benchmarking the performance of portfolio optimization with QAOA(2022) Brandhofer, Sebastian; Braun, Daniel; Dehn, Vanessa; Hellstern, Gerhard; Hüls, Matthias; Ji, Yanjun; Polian, Ilia; Bhatia, Amandeep Singh; Wellens, ThomasWe present a detailed study of portfolio optimization using different versions of the quantum approximate optimization algorithm (QAOA). For a given list of assets, the portfolio optimization problem is formulated as quadratic binary optimization constrained on the number of assets contained in the portfolio. QAOA has been suggested as a possible candidate for solving this problem (and similar combinatorial optimization problems) more efficiently than classical computers in the case of a sufficiently large number of assets. However, the practical implementation of this algorithm requires a careful consideration of several technical issues, not all of which are discussed in the present literature. The present article intends to fill this gap and thereby provides the reader with a useful guide for applying QAOA to the portfolio optimization problem (and similar problems). In particular, we will discuss several possible choices of the variational form and of different classical algorithms for finding the corresponding optimized parameters. Viewing at the application of QAOA on error-prone NISQ hardware, we also analyse the influence of statistical sampling errors (due to a finite number of shots) and gate and readout errors (due to imperfect quantum hardware). Finally, we define a criterion for distinguishing between ‘easy’ and ‘hard’ instances of the portfolio optimization problem.Item Open Access Power quality mitigation via smart demand-side management based on a genetic algorithm(2022) Eisenmann, Adrian; Streubel, Tim; Rudion, KrzysztofIn modern electrical grids, the number of nonlinear grid elements and actively controlled loads is rising. Maintaining the power quality will therefore become a challenging task. This paper presents a power quality mitigation method via smart demand-side management. The mitigation method is based on a genetic algorithm guided optimization for smart operational planning of the grid elements. The algorithm inherits the possibility to solve multiple, even competing, objectives. The objective function uses and translates the fitness functions of the genetic algorithm into a minimization or maximization problem, thus narrowing down the complexity of the addressed high cardinality optimization problem. The NSGA-II algorithm is used to obtain feasible solutions for the auto optimization of the demand-side management. A simplified industrial grid with five different machines is used as a case study to showcase the minimization of the harmonic distortion to normative limits for all time steps during a day at a specific grid node, while maintaining the productivity of the underlying industrial process.Item Open Access Distributional measures of semantic abstraction(2022) Schulte im Walde, Sabine; Frassinelli, DiegoThis article provides an in-depth study of distributional measures for distinguishing between degrees of semantic abstraction. Abstraction is considered a “central construct in cognitive science” (Barsalou, 2003) and a “process of information reduction that allows for efficient storage and retrieval of central knowledge” (Burgoon et al., 2013). Relying on the distributional hypothesis, computational studies have successfully exploited measures of contextual co-occurrence and neighbourhood density to distinguish between conceptual semantic categorisations. So far, these studies have modeled semantic abstraction across lexical-semantic tasks such as ambiguity; diachronic meaning changes; abstractness vs. concreteness; and hypernymy. Yet, the distributional approaches target different conceptual types of semantic relatedness, and as to our knowledge not much attention has been paid to apply, compare or analyse the computational abstraction measures across conceptual tasks. The current article suggests a novel perspective that exploits variants of distributional measures to investigate semantic abstraction in English in terms of the abstract-concrete dichotomy (e.g., glory-banana) and in terms of the generality-specificity distinction (e.g., animal-fish), in order to compare the strengths and weaknesses of the measures regarding categorisations of abstraction, and to determine and investigate conceptual differences. In a series of experiments we identify reliable distributional measures for both instantiations of lexical-semantic abstraction and reach a precision higher than 0.7, but the measures clearly differ for the abstract-concrete vs. abstract-specific distinctions and for nouns vs. verbs. Overall, we identify two groups of measures, (i) frequency and word entropy when distinguishing between more and less abstract words in terms of the generality-specificity distinction, and (ii) neighbourhood density variants (especially target-context diversity) when distinguishing between more and less abstract words in terms of the abstract-concrete dichotomy. We conclude that more general words are used more often and are less surprising than more specific words, and that abstract words establish themselves empirically in semantically more diverse contexts than concrete words. Finally, our experiments once more point out that distributional models of conceptual categorisations need to take word classes and ambiguity into account: results for nouns vs. verbs differ in many respects, and ambiguity hinders fine-tuning empirical observations.