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As fish farming is becoming more and more important worldwide, this ongoing project aims at the simulation and test-based analysis of highly stressed wire contacts, as they are found in off-shore fish farm cages in order to make them more reliable. The quasi-static tensile test of a wire mesh provides data for the construction of a finite element model to get a better understanding of the behavior of high-strength stainless steel from which the cages are made. Fatigue tests provide new insights that are used for an adjustment of the finite element model in order to predict the probability of possible damage caused by heavy mechanical loads (waves, storms, predators (sharks)).
Techniken zur Energiewende - studentische Fachkonferenz im Masterstudiengang Elektrische Systeme
(2013)
Die studentische Fachkonferenz im Rahmen des Seminars im Masterstudiengang Elektrische Systeme in der Fakultät für Elektrotechnik und Informationstechnik wird zum sechsten Mal veranstaltet.
Alle Studierenden erarbeiten unter dem vorgegebenen Rahmenthema eigene Beiträge, recherchieren, ergänzen, stellen die aktuellen Erkenntnisse zu wissenschaftlichen Publikationen zusammen.
Die Energiewende ist seit einigen Jahren ein heiß diskutiertes Thema. Die dezentrale Energieversorgung
unter Anwendung erneuerbarer Quellen, insbesondere Wind- und Solarkraft, ist langfristig gesehen die
einzige Antwort auf die Ausbeutung der Erde und Zerstörung der Umwelt durch Gewinnung nichtregenerativer
Energien, insbesondere Öl, Erdgas und Uran. Allerdings gibt es noch viele Bereiche, die intensive wissenschaftliche und entwicklungstechnische Arbeiten benötigen. Wie aus dem Titel durch Verwendung des Wortes „zur“ anstatt „der“ schon erkennbar, werden in dieser Fachtagung weniger die Techniken betrachtet, die schon zum Einsatz kommen, sondern zukünftige Techniken, die gedanklich auf Papier gebracht wurden, oder inzwischen das Stadium der Machbarkeitsstudie erreicht haben.
Das Thema Energiewende beinhaltet ein sehr breites Feld von Techniken. Daher haben sich die Teilnehmer
auf nur wenige, wichtige Gebiete konzentriert: Regenerative Energiegewinnung, Elektromobilität,
Speichertechnologien und Smart Grid. Durch das intensive Befassen mit diesen Themen haben sich die
Studierenden zum ersten Mal richtig mit den Problemen der Energiewende vertraut gemacht. Sie haben
dabei erkannt, dass für die Ingenieure der Fachrichtungen Elektrotechnik und Informationstechnik überaus
vielfältige, spannende und auch aus gesellschaftspolitischer Sicht notwendige und lohnende Aufgaben auf
sie warten.
Smart-Future-Living-Bodensee
(2018)
SInCom 2015
(2015)
In the past years, algorithms for 3D shape tracking using radial functions in spherical coordinates represented with different methods have been proposed. However, we have seen that mainly measurements from the lateral surface of the target can be expected in a lot of dynamic scenarios and only few measurements from the top and bottom parts leading to an error-prone shape estimate in the top and bottom regions when using a representation in spherical coordinates. We, therefore, propose to represent the shape of the target using a radial function in cylindrical coordinates, as these only represent regions of the lateral surface, and no information from the top or bottom parts is needed. In this paper, we use a Fourier-Chebyshev double series for 3D shape representation since a mixture of Fourier and Chebyshev series is a suitable basis for expanding a radial function in cylindrical coordinates. We investigate the method in a simulated and real-world maritime scenario with a CAD model of the target boat as a reference. We have found that shape representation in cylindrical coordinates has decisive advantages compared to a shape representation in spherical coordinates and should preferably be used if no prior knowledge of the measurement distribution on the surface of the target is available.
In this paper, a novel measurement model based on spherical double Fourier series (DFS) for estimating the 3D shape of a target concurrently with its kinematic state is introduced. Here, the shape is represented as a star-convex radial function, decomposed as spherical DFS. In comparison to ordinary DFS, spherical DFS do not suffer from ambiguities at the poles. Details will be given in the paper. The shape representation is integrated into a Bayesian state estimator framework via a measurement equation. As range sensors only generate measurements from the target side facing the sensor, the shape representation is modified to enable application of shape symmetries during the estimation process. The model is analyzed in simulations and compared to a shape estimation procedure using spherical harmonics. Finally, shape estimation using spherical and ordinary DFS is compared to analyze the effect of the pole problem in extended object tracking (EOT) scenarios.
In tourism, energy demands are particularly high.Tourism facilities such as hotels require large amounts ofelectric and heating resp. cooling energy. Their supply howeveris usually still based on fossil energies. This research approachanalyses the potential of promoting renewable energies in BlackForest tourism. It focuses on a combined and hence highlyefficient production of both electric and thermal energy bybiogas plants on the one hand and its provision to local tourismfacilities via short distance networks on the other. Basing onsurveys and qualitative empiricism and considering regionalresource availability as well as socio-economic aspects, it thusexamines strengths, weaknesses, opportunities and threats thatcan arise from such a cooperation.
In tourism, energy demands are particularly high. Tourism facilities such as hotels require large amounts of electric and heating / cooling energy while their supply is usually still based on fossil energies.
This research approach analyses the potential of promoting renewable energies in tourism. It focuses on a combined and hence highly efficient production of both electric and thermal energy by biogas plants on the one hand and its provision to local tourism facilities via short distance networks on the other. Considering regional resource availability as well as socio-economic aspects, it thus examines strengths, weaknesses, opportunities and threats that can arise from such a micro-cooperation. The research aim is to provide an actor-based, spatially transferable feasibility analysis.
Probabilistic Short-Term Low-Voltage Load Forecasting using Bernstein-Polynomial Normalizing Flows
(2021)
The transition to a fully renewable energy grid requires better forecasting of demand at the low-voltage level. However, high fluctuations and increasing electrification cause huge forecast errors with traditional point estimates. Probabilistic load forecasts take future uncertainties into account and thus enables various applications in low-carbon energy systems. We propose an approach for flexible conditional density forecasting of short-term load based on Bernstein-Polynomial Normalizing Flows where a neural network controls the parameters of the flow. In an empirical study with 363 smart meter customers, our density predictions compare favorably against Gaussian and Gaussian mixture densities and also outperform a non-parametric approach based on the pinball loss for 24h-ahead load forecasting for two different neural network architectures.