TY - CHAP A1 - Sattler, Johannes Christoph A1 - Atti, Vikrama Naga Babu A1 - Alexopoulos, Spiros A1 - Teixeira Boura, Cristiano José A1 - Herrmann, Ulf A1 - Dutta, Siddharth A1 - Kioutsioukis, Ioannis T1 - DNI forecast tool for the smart operation of a parabolic trough collector system with concrete thermal energy storage: Theory, results and outlook T2 - SolarPACES 2022 conference proceedings N2 - 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. KW - Direct normal irradiance forecast KW - DNI forecast KW - Parabolic trough collector KW - PTC KW - Thermal Energy Storage Y1 - 2024 U6 - https://doi.org/10.52825/solarpaces.v1i.731 SN - 2751-9899 (online) N1 - SolarPACES 2022, 28th International Conference on Concentrating Solar Power and Chemical Energy Systems, 27-30 September, Albuquerque, NM, USA IS - 1 PB - TIB Open Publishing CY - Hannover ER - TY - CHAP A1 - Chico Caminos, Ricardo Alexander A1 - Schmitz, Pascal A1 - Atti, Vikrama Naga Babu A1 - Mahdi, Zahra A1 - Teixeira Boura, Cristiano José A1 - Sattler, Johannes Christoph A1 - Herrmann, Ulf A1 - Hilger, Patrick A1 - Dieckmann, Simon T1 - Development of a micro heliostat and optical qualification assessment with a 3D laser scanning method T2 - SOLARPACES 2020 N2 - 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. KW - Concentrated solar power KW - Electricity generation KW - Measuring instruments KW - Heliostats KW - Global change Y1 - 2022 SN - 978-0-7354-4195-8 U6 - https://doi.org/10.1063/5.0086262 SN - 1551-7616 (online) SN - 0094-243X (print) N1 - SOLARPACES 2020: 26th International Conference on Concentrating Solar Power and Chemical Energy Systems, 28 September–2 October 2020, Freiburg, Germany IS - 2445 / 1 PB - AIP conference proceedings / American Institute of Physics CY - Melville, NY ER - TY - RPRT A1 - Hebel, Christoph A1 - Merkens, Torsten A1 - Feyerl, Günter A1 - Kemper, Hans A1 - Busse, Daniel T1 - Elektromobilität - Verbundprojekt "COSTARTebus": Comprehensive strategy to accelerate the integration of electric-buses into existing public transport systems - Teilprojekt A : Berichtszeitraum: 01.01.2018-31.10.2020 Y1 - 2021 N1 - Förderkennzeichen BMVI 03EMEN10A Verbundnummer 01182550 PB - Fachhochschule Aachen CY - Aachen ER - TY - JOUR A1 - Götten, Falk A1 - Finger, Felix A1 - Havermann, Marc A1 - Braun, Carsten A1 - Marino, M. A1 - Bil, C. T1 - Full configuration drag estimation of short-to-medium range fixed-wing UAVs and its impact on initial sizing optimization JF - CEAS Aeronautical Journal N2 - The paper presents the derivation of a new equivalent skin friction coefficient for estimating the parasitic drag of short-to-medium range fixed-wing unmanned aircraft. The new coefficient is derived from an aerodynamic analysis of ten different unmanned aircraft used for surveillance, reconnaissance, and search and rescue missions. The aircraft is simulated using a validated unsteady Reynolds-averaged Navier Stokes approach. The UAV’s parasitic drag is significantly influenced by the presence of miscellaneous components like fixed landing gears or electro-optical sensor turrets. These components are responsible for almost half of an unmanned aircraft’s total parasitic drag. The new equivalent skin friction coefficient accounts for these effects and is significantly higher compared to other aircraft categories. It is used to initially size an unmanned aircraft for a typical reconnaissance mission. The improved parasitic drag estimation yields a much heavier unmanned aircraft when compared to the sizing results using available drag data of manned aircraft. KW - Parasitic drag KW - UAV KW - CFD KW - Aircraft sizing Y1 - 2021 U6 - https://doi.org/10.1007/s13272-021-00522-w SN - 1869-5590 (Online) SN - 1869-5582 (Print) N1 - Corresponding author: Falk Götten VL - 12 SP - 589 EP - 603 PB - Springer CY - Berlin ER - TY - CHAP A1 - Neumann, Hannah A1 - Adam, Mario A1 - Backes, Klaus A1 - Börner, Martin A1 - Clees, Tanja A1 - Doetsch, Christian A1 - Glaeser, Susanne A1 - Herrmann, Ulf A1 - May, Johanna A1 - Rosenthal, Florian A1 - Sauer, Dirk Uwe A1 - Stadler, Ingo T1 - Development of open educational resources for renewable energy and the energy transition process T2 - ISES SWC 2021 N2 - The dissemination of knowledge about renewable energies is understood as a social task with the highest topicality. The transfer of teaching content on renewable energies into digital open educational resources offers the opportunity to significantly accelerate the implementation of the energy transition. Thus, in the here presented project six German universities create open educational resources for the energy transition. These materials are available to the public on the internet under a free license. So far there has been no publicly accessible, editable media that cover entire learning units about renewable energies extensively and in high technical quality. Thus, in this project, the content that remains up-to-date for a longer period is appropriately prepared in terms of media didactics. The materials enable lecturers to provide students with in-depth training about technologies for the energy transition. In a particular way, the created material is also suitable for making the general public knowledgeable about the energy transition with scientifically based material. KW - energy transition KW - renewable energies KW - open educational resources KW - dissemination KW - digitalization Y1 - 2021 U6 - https://doi.org/10.18086/swc.2021.47.03 N1 - ISES Solar World Congress, virtual conference 25-29 October 2021 PB - International Solar Energy Society CY - Freiburg ER - TY - JOUR A1 - Serror, Martin A1 - Hack, Sacha A1 - Henze, Martin A1 - Schuba, Marko A1 - Wehrle, Klaus T1 - Challenges and Opportunities in Securing the Industrial Internet of Things JF - IEEE Transactions on Industrial Informatics Y1 - 2021 U6 - https://doi.org/10.1109/TII.2020.3023507 SN - 1941-0050 VL - 17 IS - 5 SP - 2985 EP - 2996 PB - IEEE CY - New York ER - TY - CHAP A1 - Merkens, Torsten A1 - Hebel, Christoph T1 - Sharing mobility concepts – flexible, sustainable, smart T2 - Proceedings of the 1st UNITED – Southeast Asia Automotive Interest Group (SAIG) International Conference KW - Sharing mobility KW - electro mobility KW - business models KW - mobility behaviour Y1 - 2021 SN - 978-3-902103-94-9 N1 - 1st UNITED-SAIG International Conference, 21-22 APR 2021, Chulalongkorn University, Thailand SP - 43 EP - 44 ER - TY - CHAP A1 - Nikolovski, Gjorgji A1 - Reke, Michael A1 - Elsen, Ingo A1 - Schiffer, Stefan T1 - Machine learning based 3D object detection for navigation in unstructured environments T2 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops) N2 - In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine. KW - 3D object detection KW - LiDAR KW - autonomous driving KW - Deep learning KW - Three-dimensional displays Y1 - 2021 SN - 978-1-6654-7921-9 U6 - https://doi.org/10.1109/IVWorkshops54471.2021.9669218 N1 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 11-17 July 2021, Nagoya, Japan. SP - 236 EP - 242 PB - IEEE ER - TY - CHAP A1 - Fiedler, Gerda A1 - Gottschlich-Müller, Birgit A1 - Melcher, Karin ED - Liu-Henke, Xiaobo ED - Durak, Umut T1 - Online-Prüfungen mit STACK Aufgaben T2 - Tagungsband ASIM Workshop STS/GMMS/EDU 2021 N2 - Wir stellen hier exemplarisch STACK Aufgaben vor, die frei von der Problematik sind, welche sich durch diverse Kommunikationswege und (webbasierte) Computer Algebra Systeme (CAS) ergibt. Daher sind sie insbesondere für eine Open-Book Online Prüfung geeignet, da eine faire Prüfungssituation gewährleistet werden kann. Y1 - 2021 SN - 978-3-901608-69-8 U6 - https://doi.org/10.11128/arep.45 N1 - Virtueller Workshop, ASIM STS/GMMS & EDU 2021, 11.-12. März 2021 SP - 173 EP - 178 PB - ARGESIM Verlag CY - Wien ER - TY - CHAP A1 - Dey, Thomas A1 - Elsen, Ingo A1 - Ferrein, Alexander A1 - Frauenrath, Tobias A1 - Reke, Michael A1 - Schiffer, Stefan ED - Makedon, Fillia T1 - CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom T2 - PETRA '21: Proceedings of the 14th Pervasive Technologies Related to Assistive Environments Conference N2 - In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway. KW - embedded hardware KW - sensor networks KW - information systems KW - education KW - do-it-yourself Y1 - 2021 SN - 9781450387927 U6 - https://doi.org/10.1145/3453892.3462697 N1 - PETRA '21: The 14th PErvasive Technologies Related to Assistive Environments Conference Corfu Greece 29 June 2021- 2 July 2021 SP - 292 EP - 299 PB - Association for Computing Machinery CY - New York ER -