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This thesis aims at the presentation and discussion of well-accepted and new
imaging techniques applied to different types of flow in common hydraulic
engineering environments. All studies are conducted in laboratory conditions and
focus on flow depth and velocity measurements. Investigated flows cover a wide
range of complexity, e.g. propagation of waves, dam-break flows, slightly and fully
aerated spillway flows as well as highly turbulent hydraulic jumps.
Newimagingmethods are compared to different types of sensorswhich are frequently
employed in contemporary laboratory studies. This classical instrumentation as well
as the general concept of hydraulic modeling is introduced to give an overview on
experimental methods.
Flow depths are commonly measured by means of ultrasonic sensors, also known as
acoustic displacement sensors. These sensors may provide accurate data with high
sample rates in case of simple flow conditions, e.g. low-turbulent clear water flows.
However, with increasing turbulence, higher uncertainty must be considered.
Moreover, ultrasonic sensors can provide point data only, while the relatively large
acoustic beam footprint may lead to another source of uncertainty in case of
relatively short, highly turbulent surface fluctuations (ripples) or free-surface
air-water flows. Analysis of turbulent length and time scales of surface fluctuations
from point measurements is also difficult. Imaging techniques with different
dimensionality, however, may close this gap. It is shown in this thesis that edge
detection methods (known from computer vision) may be used for two-dimensional
free-surface extraction (i.e. from images taken through transparant sidewalls in
laboratory flumes). Another opportunity in hydraulic laboratory studies comes with
the application of stereo vision. Low-cost RGB-D sensors can be used to gather
instantaneous, three-dimensional free-surface elevations, even in flows with very
high complexity (e.g. aerated hydraulic jumps). It will be shown that the uncertainty
of these methods is of similar order as for classical instruments.
Particle Image Velocimetry (PIV) is a well-accepted and widespread imaging
technique for velocity determination in laboratory conditions. In combination with
high-speed cameras, PIV can give time-resolved velocity fields in 2D/3D or even as
volumetric flow fields. PIV is based on a cross-correlation technique applied to small
subimages of seeded flows. The minimum size of these subimages defines the
maximum spatial resolution of resulting velocity fields. A derivative of PIV for
aerated flows is also available, i.e. the so-called Bubble Image Velocimetry (BIV). This
thesis emphasizes the capacities and limitations of both methods, using relatively
simple setups with halogen and LED illuminations. It will be demonstrated that
PIV/BIV images may also be processed by means of Optical Flow (OF) techniques.
OF is another method originating from the computer vision discipline, based on the
assumption of image brightness conservation within a sequence of images. The
Horn-Schunck approach, which has been first employed to hydraulic engineering
problems in the studies presented herein, yields dense velocity fields, i.e. pixelwise
velocity data. As discussed hereinafter, the accuracy of OF competes well with PIV
for clear-water flows and even improves results (compared to BIV) for aerated flow
conditions. In order to independently benchmark the OF approach, synthetic images
with defined turbulence intensitiy are used.
Computer vision offers new opportunities that may help to improve the
understanding of fluid mechanics and fluid-structure interactions in laboratory
investigations. In prototype environments, it can be employed for obstacle detection
(e.g. identification of potential fish migration corridors) and recognition (e.g. fish
species for monitoring in a fishway) or surface reconstruction (e.g. inspection of
hydraulic structures). It can thus be expected that applications to hydraulic
engineering problems will develop rapidly in near future. Current methods have not
been developed for fluids in motion. Systematic future developments are needed to
improve the results in such difficult conditions.
Die potenziellen Auswirkungen der Digitalisierung auf die Lehre sind seit langem Gegenstand ausführlicher Diskussionen innerhalb der Wirtschaftsinformatik (WI) (z. B. in Auth et al. 2021, Barton et al. 2019, Klotz et al. 2019). Nicht zuletzt der in nahezu allen Wirtschaftszweigen bestehende Mangel an qualifizierten Fachkräften lenkt den Diskurs auf einen verbesserten Zugang zu Bildung und gleichen Bildungschancen. Aus dieser Vision heraus und dem Schub der Digitalisierung entstehen Bildungskonzepte wie Open Educational Resources (OER), die gesellschaftlichen Problemen, wie dem des Fachkräftemangels, entgegenwirken sollen. Im Rahmen dieses Kurzbeitrags wird das Projekt WiLMo - "Wirtschaftsinformatik Lehr- und Lernmodule" vorgestellt. WiLMo wird im Rahmen von OERContent.nrw unter Beteiligung von sechs Hochschulen entwickelt und gefördert. Alle Projektbeteiligten arbeiten gemeinsam daran, einheitliche digitale Lehr- und Lernmaterialien im OER-Format für die Kernmodule der Wirtschaftsinformatik zu entwickeln und in garantiert hoher Qualität zur Verfügung zu stellen.
Reducing poverty, protecting the planet, and improving life on earth for everyone are the essential goals of the "2030 Agenda for Sustainable Development"committed by the United Nations (UN). Achieving those goals will require technological innovation as well as their implementation in almost all areas of our business and day-to-day life. This paper proposes a high-level framework that collects and structures different uses cases addressing the goals defined by the UN. Hence, it contributes to the discussion by proposing technical innovations that can be used to achieve those goals. As an example, the goal "Climate Actionïs discussed in detail by describing use cases related to tackling biodiversity loss in order to conservate ecosystems.
The management of knowledge in organizations considers both established long-term processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
Im Verfahren gegen die Österreichische Post AG (Rs. C-300/21) befasste sich der EuGH erstmals mit dem in Art. 82 DS-GVO geregelten datenschutzrechtlichen Schadensersatzanspruch. Mit den Klarstellungen des EuGH verschieben sich die Probleme nun stärker zu den „klassischen“ Fragen des Schadensersatzrechts im Zivilprozess. Relevant sind dabei vor allem Aspekte der Darlegungs- und Beweislast und deren Besonderheiten mit Blick auf den Ersatz immaterieller Schäden. Der Beitrag fokussiert sich auf die Voraussetzungen und den dabei zu führenden Tatsachenbeweis bei der Klage des Betroffenen gegen den Verantwortlichen auf Ersatz immaterieller Schäden.
Kartellrecht vs. Datenschutzrecht: Rechtsgrundlagen für die Datenverarbeitung in sozialen Netzwerken
(2023)
The concept of energy conversion into platform chemicals using bioelectrochemical systems (BES) has gained increasing attention in recent years, as the technology simultaneously provides an opportunity for sustainable chemical production and tackles the challenge of Power-to-X technologies. There are many approaches to realize the industrial scale of BES. One concept is to equip standard bioreactors with static electrodes. However, large installations resulted in a negative influence on various reactor parameters. In this study, we present a new single-chamber BES based on a stirred tank reactor in which the stirrer was replaced by a carbon fiber brush, performing the functions of the working electrode and the stirrer. The reactor is characterized in abiotic studies and electro-fermentations with Clostridium acetobutylicum. Compared to standard reactors an increase in butanol production of 20.14±3.66 % shows that the new BES can be efficiently used for bioelectrochemical processes.
Today’s society is undergoing a paradigm shift driven by the megatrend of sustainability. This undeniably affects all areas of Western life. This paper aims to find out how the luxury industry is dealing with this change and what adjustments are made by the companies. For this purpose, interviews were conducted with managers from the luxury industry, in which they were asked about specific measures taken by their companies as well as trends in the industry. In a subsequent evaluation, the trends in the luxury industry were summarized for the areas of ecological, social, and economic sustainability. It was found that the area of environmental sustainability is significantly more focused than the other sub-areas. Furthermore, the need for a customer survey to validate the industry-based measures was identified.
This work presents the Multi-Bees-Tracker (MBT3D) algorithm, a Python framework implementing a deep association tracker for Tracking-By-Detection, to address the challenging task of tracking flight paths of bumblebees in a social group. While tracking algorithms for bumblebees exist, they often come with intensive restrictions, such as the need for sufficient lighting, high contrast between the animal and background, absence of occlusion, significant user input, etc. Tracking flight paths of bumblebees in a social group is challenging. They suddenly adjust movements and change their appearance during different wing beat states while exhibiting significant similarities in their individual appearance. The MBT3D tracker, developed in this research, is an adaptation of an existing ant tracking algorithm for bumblebee tracking. It incorporates an offline trained appearance descriptor along with a Kalman Filter for appearance and motion matching. Different detector architectures for upstream detections (You Only Look Once (YOLOv5), Faster Region Proposal Convolutional Neural Network (Faster R-CNN), and RetinaNet) are investigated in a comparative study to optimize performance. The detection models were trained on a dataset containing 11359 labeled bumblebee images. YOLOv5 reaches an Average Precision of AP = 53, 8%, Faster R-CNN achieves AP = 45, 3% and RetinaNet AP = 38, 4% on the bumblebee validation dataset, which consists of 1323 labeled bumblebee images. The tracker’s appearance model is trained on 144 samples. The tracker (with Faster R-CNN detections) reaches a Multiple Object Tracking Accuracy MOTA = 93, 5% and a Multiple Object Tracking Precision MOTP = 75, 6% on a validation dataset containing 2000 images, competing with state-of-the-art computer vision methods. The framework allows reliable tracking of different bumblebees in the same video stream with rarely occurring identity switches (IDS). MBT3D has much lower IDS than other commonly used algorithms, with one of the lowest false positive rates, competing with state-of-the-art animal tracking algorithms. The developed framework reconstructs the 3-dimensional (3D) flight paths of the bumblebees by triangulation. It also handles and compares two alternative stereo camera pairs if desired.
06| Warum es gemeinsam besser geht
10| Interview
14| Wer ist hier der Boss?
18| Schnittstelle zwischen Mensch und Technik
22| Zweite Heimat Jülich
28| Zwischen Angst und Hoffnung
32| Eine Sternstunde für die FH Aachen
36| Gegen alle Widerstände
38| Ein Ort, der bleibt
42| Der Aufblühende
46| Der Computer sitzt am Steuer
52| Da geht das Herz auf
54| Hoch hinaus
58| Beratungsangebote
60| Das alte Schätzchen
Despite the challenges of pioneering molten salt towers (MST), it remains the leading technology in central receiver power plants today, thanks to cost effective storage integration and high cost reduction potential. The limited controllability in volatile solar conditions can cause significant losses, which are difficult to estimate without comprehensive modeling [1]. This paper presents a Methodology to generate predictions of the dynamic behavior of the receiver system as part of an operating assistance system (OAS). Based on this, it delivers proposals if and when to drain and refill the receiver during a cloudy period in order maximize the net yield and quantifies the amount of net electricity gained by this. After prior analysis with a detailed dynamic two-phase model of the entire receiver system, two different reduced modeling approaches where developed and implemented in the OAS. A tailored decision algorithm utilizes both models to deliver the desired predictions efficiently and with appropriate accuracy.
The integration of high temperature thermal energy storages into existing conventional power plants can help to reduce the CO2 emissions of those plants and lead to lower capital expenditures for building energy storage systems, due to the use of synergy effects [1]. One possibility to implement that, is a molten salt storage system with a powerful power-to-heat unit. This paper presents two possible control concepts for the startup of the charging system of such a facility. The procedures are implemented in a detailed dynamic process model. The performance and safety regarding the film temperatures at heat transmitting surfaces are investigated in the process simulations. To improve the accuracy in predicting the film temperatures, CFD simulations of the electrical heater are carried out and the results are merged with the dynamic model. The results show that both investigated control concepts are safe regarding the temperature limits. The gradient controlled startup performed better than the temperature-controlled startup. Nevertheless, there are several uncertainties that need to be investigated further.
Residential and commercial buildings account for more than one-third of global energy-related greenhouse gas emissions. Integrated multi-energy systems at the district level are a promising way to reduce greenhouse gas emissions by exploiting economies of scale and synergies between energy sources. Planning district energy systems comes with many challenges in an ever-changing environment. Computational modelling established itself as the state-of-the-art method for district energy system planning. Unfortunately, it is still cumbersome to combine standalone models to generate insights that surpass their original purpose. Ideally, planning processes could be solved by using modular tools that easily incorporate the variety of competing and complementing computational models. Our contribution is a vision for a collaborative development and application platform for multi-energy system planning tools at the district level. We present challenges of district energy system planning identified in the literature and evaluate whether this platform can help to overcome these challenges. Further, we propose a toolkit that represents the core technical elements of the platform. Lastly, we discuss community management and its relevance for the success of projects with collaboration and knowledge sharing at their core.
The feasibility study presents results of a hydrogen combustor integration for a Medium-Range aircraft engine using the Dry-Low-NOₓ Micromix combustion principle. Based on a simplified Airbus A320-type flight mission, a thermodynamic performance model of a kerosene and a hydrogen-powered V2530-A5 engine is used to derive the thermodynamic combustor boundary conditions. A new combustor design using the Dry-Low NOx Micromix principle is investigated by slice model CFD simulations of a single Micromix injector for design and off-design operation of the engine. Combustion characteristics show typical Micromix flame shapes and good combustion efficiencies for all flight mission operating points. Nitric oxide emissions are significant below ICAO CAEP/8 limits. For comparison of the Emission Index (EI) for NOₓ emissions between kerosene and hydrogen operation, an energy (kerosene) equivalent Emission Index is used.
A full 15° sector model CFD simulation of the combustion chamber with multiple Micromix injectors including inflow homogenization and dilution and cooling air flows investigates the combustor integration effects, resulting NOₓ emission and radial temperature distributions at the combustor outlet. The results show that the integration of a Micromix hydrogen combustor in actual aircraft engines is feasible and offers, besides CO₂ free combustion, a significant reduction of NOₓ emissions compared to kerosene operation.
Die Erfindung betrifft eine Vorrichtung zur Bestimmung einer Relativlage zwischen einem feststehenden Teil und einem zu demselben in eine Bewegungsrichtung bewegbaren beweglichen Teil, wobei der feststehende Teil mit einem Wiegandsensor versehen ist, wobei der Wiegandsensor zwischen zwei gegenpolig zueinander ausgebildeten Permanentmagneten angeordnet ist und dass der bewegliche Teil eine Mehrzahl von beabstandet zueinander angeordneten Magnetisierungsstegen aus einem magnetisch leitenden Material aufweist, die in der Bewegungsrichtung zumindest eine gleich große Erstreckung aufweisen wie der Permanentmagnet, dass ein Abstand zwischen benachbarten Magnetisierungsstegen derart gewählt ist, dass in einer ersten Relativlage ein erster Permanentmagnet von einem der Magnetisierungsstege überdeckt ist und ein zweiter Permanentmagnet nicht von einem der Magnetisierungsstege überdeckt ist.
In order to reduce energy consumption of homes, it is important to make transparent which devices consume how much energy. However, power consumption is often only monitored aggregated at the house energy meter. Disaggregating this power consumption into the contributions of individual devices can be achieved using Machine Learning. Our work aims at making state of the art disaggregation algorithms accessibe for users of the open source home automation platform Home Assistant.
Ein neues tragendes, lagenweise aufgebautes Holzbau-Wandsystem und seine ökonomische und statische Entwicklung werden vorgestellt. Randbedingungen wie Nachhaltigkeit, Ressourceneffizienz und eine beanspruchungsadaptive Konstruktionsweise sind für diese innovative Bauteilentwicklung von zentraler Bedeutung. Eine wesentliche Herausforderung ist die Herstellung der Verbindung der Lagen untereinander zu einem bauphysikalisch und statisch leistungsfähigen Wandsystem. Die Tragfähigkeit und Steifigkeit verschiedener Verbindungsvarianten wurden ebenso wie die Eigenschaften der Wandelemente analytisch, numerisch und experimentell untersucht.