@inproceedings{NeumannAdamBackesetal.2021, author = {Neumann, Hannah and Adam, Mario and Backes, Klaus and B{\"o}rner, Martin and Clees, Tanja and Doetsch, Christian and Glaeser, Susanne and Herrmann, Ulf and May, Johanna and Rosenthal, Florian and Sauer, Dirk Uwe and Stadler, Ingo}, title = {Development of open educational resources for renewable energy and the energy transition process}, series = {ISES SWC 2021}, booktitle = {ISES SWC 2021}, publisher = {International Solar Energy Society}, address = {Freiburg}, doi = {10.18086/swc.2021.47.03}, pages = {6 Seiten}, year = {2021}, abstract = {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.}, language = {en} } @inproceedings{SchopenKemperEsch2021, author = {Schopen, Oliver and Kemper, Hans and Esch, Thomas}, title = {Development of a comparison methodology and evaluation matrix for electrically driven compressors in ICE and FC}, series = {Proceedings of the 1st UNITED - Southeast Asia Automotive Interest Group (SAIG) International Conference}, booktitle = {Proceedings of the 1st UNITED - Southeast Asia Automotive Interest Group (SAIG) International Conference}, publisher = {FH Joanneum}, address = {Graz}, isbn = {978-3-902103-94-9}, pages = {45 -- 46}, year = {2021}, abstract = {In addition to electromobility and alternative drive systems, a focus is set on electrically driven compressors (EDC), with a high potential for increasing the efficiency of internal combustion engines (ICE) and fuel cells [01]. The primary objective is to increase the ICE torque, provided independently of the ICE speed by compressing the intake air and consequently the ICE filling level supported by the compressor. For operation independent from the ICE speed, the EDC compressor is decoupled from the turbine by using an electric compressor motor (CM) instead of the turbine. ICE performances can be increased by the use of EDC where individual compressor parameters are adapted to the respective application area [02] [03]. This task contains great challenges, increased by demands with regard to pollutant reduction while maintaining constant performance and reduced fuel consumption. The FH-Aachen is equipped with an EDC test bench which enables EDC-investigations in various configurations and operating modes. Characteristic properties of different compressors can be determined, which build the basis for a comparison methodology. Subject of this project is the development of a comparison methodology for EDC with an associated evaluation method and a defined overall evaluation method. For the application of this comparison methodology, corresponding series of measurements are carried out on the EDC test bench using an appropriate test device.}, language = {en} } @inproceedings{DeyElsenFerreinetal.2021, author = {Dey, Thomas and Elsen, Ingo and Ferrein, Alexander and Frauenrath, Tobias and Reke, Michael and Schiffer, Stefan}, title = {CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom}, series = {PETRA 2021: The 14th PErvasive Technologies Related to Assistive Environments Conference}, booktitle = {PETRA 2021: The 14th PErvasive Technologies Related to Assistive Environments Conference}, editor = {Makedon, Fillia}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {9781450387927}, doi = {10.1145/3453892.3462697}, pages = {292 -- 299}, year = {2021}, abstract = {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.}, language = {en} } @inproceedings{FiedlerGottschlichMuellerMelcher2021, author = {Fiedler, Gerda and Gottschlich-M{\"u}ller, Birgit and Melcher, Karin}, title = {Online-Pr{\"u}fungen mit STACK Aufgaben}, series = {Tagungsband ASIM Workshop STS/GMMS/EDU 2021}, booktitle = {Tagungsband ASIM Workshop STS/GMMS/EDU 2021}, editor = {Liu-Henke, Xiaobo and Durak, Umut}, publisher = {ARGESIM Verlag}, address = {Wien}, isbn = {978-3-901608-69-8}, doi = {10.11128/arep.45}, pages = {6 Seiten}, year = {2021}, abstract = {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 f{\"u}r eine Open-Book Online Pr{\"u}fung geeignet, da eine faire Pr{\"u}fungssituation gew{\"a}hrleistet werden kann.}, language = {de} } @techreport{HebelMerkensFeyerletal.2021, author = {Hebel, Christoph and Merkens, Torsten and Feyerl, G{\"u}nter and Kemper, Hans and Busse, Daniel}, title = {Elektromobilit{\"a}t - 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}, publisher = {Fachhochschule Aachen}, address = {Aachen}, pages = {219 Seiten}, year = {2021}, language = {de} } @inproceedings{NikolovskiRekeElsenetal.2021, author = {Nikolovski, Gjorgji and Reke, Michael and Elsen, Ingo and Schiffer, Stefan}, title = {Machine learning based 3D object detection for navigation in unstructured environments}, series = {2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)}, booktitle = {2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)}, publisher = {IEEE}, isbn = {978-1-6654-7921-9}, doi = {10.1109/IVWorkshops54471.2021.9669218}, pages = {236 -- 242}, year = {2021}, abstract = {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.}, language = {en} } @inproceedings{MerkensHebel2021, author = {Merkens, Torsten and Hebel, Christoph}, title = {Sharing mobility concepts - flexible, sustainable, smart}, series = {Proceedings of the 1st UNITED - Southeast Asia Automotive Interest Group (SAIG)}, booktitle = {Proceedings of the 1st UNITED - Southeast Asia Automotive Interest Group (SAIG)}, isbn = {978-3-902103-94-9}, pages = {43 -- 44}, year = {2021}, language = {en} } @article{GoettenFingerHavermannetal.2021, author = {G{\"o}tten, Falk and Finger, Felix and Havermann, Marc and Braun, Carsten and Marino, M. and Bil, C.}, title = {Full configuration drag estimation of short-to-medium range fixed-wing UAVs and its impact on initial sizing optimization}, series = {CEAS Aeronautical Journal}, volume = {12}, journal = {CEAS Aeronautical Journal}, publisher = {Springer}, address = {Berlin}, issn = {1869-5590 (Online)}, doi = {10.1007/s13272-021-00522-w}, pages = {589 -- 603}, year = {2021}, abstract = {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.}, language = {en} } @article{SerrorHackHenzeetal.2021, author = {Serror, Martin and Hack, Sacha and Henze, Martin and Schuba, Marko and Wehrle, Klaus}, title = {Challenges and Opportunities in Securing the Industrial Internet of Things}, series = {IEEE Transactions on Industrial Informatics}, volume = {17}, journal = {IEEE Transactions on Industrial Informatics}, number = {5}, publisher = {IEEE}, address = {New York}, issn = {1941-0050}, doi = {10.1109/TII.2020.3023507}, pages = {2985 -- 2996}, year = {2021}, language = {en} }