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This paper compares several blade element theory (BET) method-based propeller simulation tools, including an evaluation against static propeller ground tests and high-fidelity Reynolds-Average Navier Stokes (RANS) simulations. Two proprietary propeller geometries for paraglider applications are analysed in static and flight conditions. The RANS simulations are validated with the static test data and used as a reference for comparing the BET in flight conditions. The comparison includes the analysis of varying 2D aerodynamic airfoil parameters and different induced velocity calculation methods. The evaluation of the BET propeller simulation tools shows the strength of the BET tools compared to RANS simulations. The RANS simulations underpredict static experimental data within 10% relative error, while appropriate BET tools overpredict the RANS results by 15–20% relative error. A variation in 2D aerodynamic data depicts the need for highly accurate 2D data for accurate BET results. The nonlinear BET coupled with XFOIL for the 2D aerodynamic data matches best with RANS in static operation and flight conditions. The novel BET tool PropCODE combines both approaches and offers further correction models for highly accurate static and flight condition results.
A promising approach to reduce the system costs of molten salt solar receivers is to enable the irradiation of the absorber tubes on both sides. The star design is an innovative receiver design, pursuing this approach. The unconventional design leads to new challenges in controlling the system. This paper presents a control concept for a molten salt receiver system in star design. The control parameters are optimized in a defined test cycle by minimizing a cost function. The control concept is tested in realistic cloud passage scenarios based on real weather data. During these tests, the control system showed no sign of unstable behavior, but to perform sufficiently in every scenario further research and development like integrating Model Predictive Controls (MPCs) need to be done. The presented concept is a starting point to do so.
This paper covers the use of the magnetic Wiegand effect to design an innovative incremental encoder. First, a theoretical design is given, followed by an estimation of the achievable accuracy and an optimization in open-loop operation.
Finally, a successful experimental verification is presented. For this purpose, a permanent magnet synchronous machine is controlled in a field-oriented manner, using the angle information of the prototype.
The Solar-Institut Jülich (SIJ) and the companies Hilger GmbH and Heliokon GmbH from Germany have developed a small-scale cost-effective heliostat, called “micro heliostat”. Micro heliostats can be deployed in small-scale concentrated solar power (CSP) plants to concentrate the sun's radiation for electricity generation, space or domestic water heating or industrial process heat. In contrast to conventional heliostats, the special feature of a micro heliostat is that it consists of dozens of parallel-moving, interconnected, rotatable mirror facets. The mirror facets array is fixed inside a box-shaped module and is protected from weathering and wind forces by a transparent glass cover. The choice of the building materials for the box, tracking mechanism and mirrors is largely dependent on the selected production process and the intended application of the micro heliostat. Special attention was paid to the material of the tracking mechanism as this has a direct influence on the accuracy of the micro heliostat. The choice of materials for the mirror support structure and the tracking mechanism is made in favor of plastic molded parts. A qualification assessment method has been developed by the SIJ in which a 3D laser scanner is used in combination with a coordinate measuring machine (CMM). For the validation of this assessment method, a single mirror facet was scanned and the slope deviation was computed.
In this work, three patent pending calibration methods for heliostat fields of central receiver systems (CRS) developed by the Solar-Institut Jülich (SIJ) of the FH Aachen University of Applied Sciences are presented. The calibration methods can either operate in a combined mode or in stand-alone mode. The first calibration method, method A, foresees that a camera matrix is placed into the receiver plane where it is subjected to concentrated solar irradiance during a measurement process. The second calibration method, method B, uses an unmanned aerial vehicle (UAV) such as a quadrocopter to automatically fly into the reflected solar irradiance cross-section of one or more heliostats (two variants of method B were tested). The third calibration method, method C, foresees a stereo central camera or multiple stereo cameras installed e.g. on the solar tower whereby the orientations of the heliostats are calculated from the location detection of spherical red markers attached to the heliostats. The most accurate method is method A which has a mean accuracy of 0.17 mrad. The mean accuracy of method B variant 1 is 1.36 mrad and of variant 2 is 1.73 mrad. Method C has a mean accuracy of 15.07 mrad. For method B there is great potential regarding improving the measurement accuracy. For method C the collected data was not sufficient for determining whether or not there is potential for improving the accuracy.
The industrial revolution IR4.0 era have driven many states of the art technologies to be introduced especially in the automotive industry. The rapid development of automotive industries in Europe have created wide industry gap between European Union (EU) and developing countries such as in South-East Asia (SEA). Indulging this situation, FH Joanneum, Austria together with European partners from FH Aachen, Germany and Politecnico Di Torino, Italy is taking initiative to close the gap utilizing the Erasmus+ United grant from EU. A consortium was founded to engage with automotive technology transfer using the European ramework to Malaysian, Indonesian and Thailand Higher Education Institutions (HEI) as well as automotive industries. This could be achieved by establishing Engineering Knowledge Transfer Unit (EKTU) in respective SEA institutions guided by the industry partners in their respective countries. This EKTU could offer updated, innovative, and high-quality training courses to increase graduate’s employability in higher education institutions and strengthen relations between HEI and the wider economic and social environment by addressing Universityindustry cooperation which is the regional priority for Asia. It is expected that, the Capacity Building Initiative would improve the quality of higher education and enhancing its relevance for the labor market and society in the SEA partners. The outcome of this project would greatly benefit the partners in strong and complementary partnership targeting the automotive industry and enhanced larger scale international cooperation between the European and SEA partners. It would also prepare the SEA HEI in sustainable partnership with Automotive industry in the region as a mean of income generation in the future.
Digital twins are seen as one of the key technologies of Industry 4.0. Although many research groups focus on digital twins and create meaningful outputs, the technology has not yet reached a broad application in the industry. The main reasons for this imbalance are the complexity of the topic, the lack of specialists, and the unawareness of the twin opportunities. The project "Digital Twin Academy" aims to overcome these barriers by focusing on three actions: Building a digital twin community for discussion and exchange, offering multi-stage training for various knowledge levels, and implementing realworld use cases for deeper insights and guidance. In this work, we focus on creating a flexible learning platform that allows the user to select a training path adjusted to personal knowledge and needs. Therefore, a mix of basic and advanced modules is created and expanded by individual feedback options. The usage of personas supports the selection of the appropriate modules.
This work presents a basic forecast tool for predicting direct normal irradiance (DNI) in hourly resolution, which the Solar-Institut Jülich (SIJ) is developing within a research project. The DNI forecast data shall be used for a parabolic trough collector (PTC) system with a concrete thermal energy storage (C-TES) located at the company KEAN Soft Drinks Ltd in Limassol, Cyprus. On a daily basis, 24-hour DNI prediction data in hourly resolution shall be automatically produced using free or very low-cost weather forecast data as input. The purpose of the DNI forecast tool is to automatically transfer the DNI forecast data on a daily basis to a main control unit (MCU). The MCU automatically makes a smart decision on the operation mode of the PTC system such as steam production mode and/or C-TES charging mode. The DNI forecast tool was evaluated using historical data of measured DNI from an on-site weather station, which was compared to the DNI forecast data. The DNI forecast tool was tested using data from 56 days between January and March 2022, which included days with a strong variation in DNI due to cloud passages. For the evaluation of the DNI forecast reliability, three categories were created and the forecast data was sorted accordingly. The result was that the DNI forecast tool has a reliability of 71.4 % based on the tested days. The result fulfils SIJ’s aim to achieve a reliability of around 70 %, but SIJ aims to still improve the DNI forecast quality.
Masonry infill walls are the most traditional enclosure system that is still widely used in RC frame buildings all over the world, particularly in seismic active regions. Although infill walls are usually neglected in seismic design, during an earthquake event they are subjected to in-plane and out-of-plane forces that can act separately or simultaneously. Since observations of damage to buildings after recent earthquakes showed detrimental effects of in-plane and out-of-plane load interaction on infill walls, the number of studies that focus on influence of in-plane damage on out-of-plane response has significantly increased. However, most of the xperimental campaigns have considered only solid infills and there is a lack of combined in-plane and out-of-plane experimental tests on masonry infills with openings, although windows and doors strongly affect seismic performance. In this paper, two types of experimental tests on infills with window openings are presented. The first is a pure out-of-plane test and the second one is a sequential in-plane and out-of-plane test aimed at investigating the effects of existing in-plane damage on outof-plane response. Additionally, findings from two tests with similar load procedure that were carried out on fully infilled RC frames in the scope of the same project are used for comparison. Test results clearly show that window opening increased vulnerability of infills to combined seismic actions and that prevention of damage in infills with openings is of the utmost importance for seismic safety.
Messenger apps like WhatsApp or Telegram are an integral part of daily communication. Besides the various positive effects, those services extend the operating range of criminals. Open trading groups with many thousand participants emerged on Telegram. Law enforcement agencies monitor suspicious users in such chat rooms. This research shows that text analysis, based on natural language processing, facilitates this through a meaningful domain overview and detailed investigations. We crawled a corpus from such self-proclaimed black markets and annotated five attribute types products, money, payment methods, user names, and locations. Based on each message a user sends, we extract and group these attributes to build profiles. Then, we build features to cluster the profiles. Pretrained word vectors yield better unsupervised clustering results than current
state-of-the-art transformer models. The result is a semantically meaningful high-level overview of the user landscape of black market chatrooms. Additionally, the extracted structured information serves as a foundation for further data exploration, for example, the most active users or preferred payment methods.