@inproceedings{DinghoferHartung2020, author = {Dinghofer, Kai and Hartung, Frank}, title = {Analysis of Criteria for the Selection of Machine Learning Frameworks}, series = {2020 International Conference on Computing, Networking and Communications (ICNC)}, booktitle = {2020 International Conference on Computing, Networking and Communications (ICNC)}, publisher = {IEEE}, address = {New York, NY}, doi = {10.1109/ICNC47757.2020.9049650}, pages = {373 -- 377}, year = {2020}, abstract = {With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.}, language = {en} } @phdthesis{Elsen2000, author = {Elsen, Ingo}, title = {Ansichtenbasierte 3D-Objekterkennung mit erweiterten selbstorganisierenden Merkmalskarten}, publisher = {VDI-Verlag}, address = {D{\"u}sseldorf}, isbn = {978-3-18-363110-0}, issn = {0341-1796}, pages = {VIII, 140 S. : Ill., graph. Darst.}, year = {2000}, language = {de} } @article{FunkeEschRoosen2022, author = {Funke, Harald and Esch, Thomas and Roosen, Petra}, title = {Antriebssystemanpassungen zur Verwendung von LPG als Flugkraftstoff}, series = {Motortechnische Zeitschrift (MTZ)}, volume = {2022}, journal = {Motortechnische Zeitschrift (MTZ)}, number = {83}, publisher = {Springer Nature}, address = {Basel}, doi = {10.1007/s35146-021-0778-2}, pages = {58 -- 62}, year = {2022}, abstract = {Auch in der allgemeinen Luftfahrt w{\"a}re es w{\"u}nschenswert, die bereits vorhandenen Verbrennungsmotoren mit weniger CO₂-tr{\"a}chtigen Kraftstoffen als dem heute weit verbreiteten Avgas 100LL betreiben zu k{\"o}nnen. Es ist anzunehmen, dass im Vergleich die unter Normalbedingungen gasf{\"o}rmigen Kraftstoffe CNG, LPG oder LNG deutlich weniger Emissionen produzieren. Erforderliche Antriebssystemanpassungen wurden im Rahmen eines Forschungsprojekts an der FH Aachen untersucht.}, language = {de} } @article{SaretzkiBergmannDahmannetal.2021, author = {Saretzki, Charlotte and Bergmann, Ole and Dahmann, Peter and Janser, Frank and Keimer, Jona and Machado, Patricia and Morrison, Audry and Page, Henry and Pluta, Emil and St{\"u}bing, Felix and K{\"u}pper, Thomas}, title = {Are small airplanes safe with regards to COVID-19 transmission?}, series = {Journal of Travel Medicine}, volume = {28}, journal = {Journal of Travel Medicine}, number = {7}, publisher = {Oxford University Press}, address = {Oxford}, issn = {1708-8305}, doi = {10.1093/jtm/taab105}, year = {2021}, language = {en} } @article{FayyaziSardarThomasetal.2023, author = {Fayyazi, Mojgan and Sardar, Paramjotsingh and Thomas, Sumit Infent and Daghigh, Roonak and Jamali, Ali and Esch, Thomas and Kemper, Hans and Langari, Reza and Khayyam, Hamid}, title = {Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles}, volume = {15}, number = {6}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/su15065249}, pages = {38}, year = {2023}, abstract = {Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed.}, language = {en} } @article{MoehrenBergmannJanseretal.2024, author = {M{\"o}hren, Felix and Bergmann, Ole and Janser, Frank and Braun, Carsten}, title = {Assessment of structural mechanical effects related to torsional deformations of propellers}, series = {CEAS Aeronautical Journal}, journal = {CEAS Aeronautical Journal}, publisher = {Springer}, address = {Wien}, issn = {1869-5590 (eISSN)}, doi = {10.1007/s13272-024-00737-7}, pages = {22 Seiten}, year = {2024}, abstract = {Lifting propellers are of increasing interest for Advanced Air Mobility. All propellers and rotors are initially twisted beams, showing significant extension-twist coupling and centrifugal twisting. Torsional deformations severely impact aerodynamic performance. This paper presents a novel approach to assess different reasons for torsional deformations. A reduced-order model runs large parameter sweeps with algebraic formulations and numerical solution procedures. Generic beams represent three different propeller types for General Aviation, Commercial Aviation, and Advanced Air Mobility. Simulations include solid and hollow cross-sections made of aluminum, steel, and carbon fiber-reinforced polymer. The investigation shows that centrifugal twisting moments depend on both the elastic and initial twist. The determination of the centrifugal twisting moment solely based on the initial twist suffers from errors exceeding 5\% in some cases. The nonlinear parts of the torsional rigidity do not significantly impact the overall torsional rigidity for the investigated propeller types. The extension-twist coupling related to the initial and elastic twist in combination with tension forces significantly impacts the net cross-sectional torsional loads. While the increase in torsional stiffness due to initial twist contributes to the overall stiffness for General and Commercial Aviation propellers, its contribution to the lift propeller's stiffness is limited. The paper closes with the presentation of approximations for each effect identified as significant. Numerical evaluations are necessary to determine each effect for inhomogeneous cross-sections made of anisotropic material.}, language = {en} } @misc{SchmitzSchebitzEsch1997, author = {Schmitz, G{\"u}nter and Schebitz, Michael and Esch, Thomas}, title = {Aus der Ruhelage selbstanziehender elektromagnetischer Aktuator}, year = {1997}, abstract = {Elektromagnetischer Aktuator zur Bet{\"a}tigung eines Stellgliedes (2), mit wenigstens einem Elektromagneten (4) und einem mit dem Stellglied (2) verbundenen Anker (3), der gegen die Kraft einer R{\"u}ckstellfeder (6) aus seiner Ruhelage in Richtung auf den Elektromagneten (4) bewegbar ist, mit einer R{\"u}ckstellfeder (6), die eine nicht lineare, bezogen auf die Ruhelage des Ankers (3) progressiv ansteigende Kennlinie aufweist.}, language = {de} } @inproceedings{VeettilRakshitSchopenetal.2022, author = {Veettil, Yadu Krishna Morassery and Rakshit, Shantam and Schopen, Oliver and Kemper, Hans and Esch, Thomas and Shabani, Bahman}, title = {Automated Control System Strategies to Ensure Safety of PEM Fuel Cells Using Kalman Filters}, series = {Proceedings of the 7th International Conference and Exhibition on Sustainable Energy and Advanced Materials (ICE-SEAM 2021), Melaka, Malaysia}, booktitle = {Proceedings of the 7th International Conference and Exhibition on Sustainable Energy and Advanced Materials (ICE-SEAM 2021), Melaka, Malaysia}, editor = {Bin Abdollah, Mohd Fadzli and Amiruddin, Hilmi and Singh, Amrik Singh Phuman and Munir, Fudhail Abdul and Ibrahim, Asriana}, publisher = {Springer Nature}, address = {Singapore}, isbn = {978-981-19-3178-9}, issn = {2195-4356}, doi = {10.1007/978-981-19-3179-6_55}, pages = {296 -- 299}, year = {2022}, abstract = {Having well-defined control strategies for fuel cells, that can efficiently detect errors and take corrective action is critically important for safety in all applications, and especially so in aviation. The algorithms not only ensure operator safety by monitoring the fuel cell and connected components, but also contribute to extending the health of the fuel cell, its durability and safe operation over its lifetime. While sensors are used to provide peripheral data surrounding the fuel cell, the internal states of the fuel cell cannot be directly measured. To overcome this restriction, Kalman Filter has been implemented as an internal state observer. Other safety conditions are evaluated using real-time data from every connected sensor and corrective actions automatically take place to ensure safety. The algorithms discussed in this paper have been validated thorough Model-in-the-Loop (MiL) tests as well as practical validation at a dedicated test bench.}, language = {en} } @article{NeuJanserKhatibietal.2016, author = {Neu, Eugen and Janser, Frank and Khatibi, Akbar A. and Orifici, Adrian C.}, title = {Automated modal parameter-based anomaly detection under varying wind excitation}, series = {Structural Health Monitoring}, volume = {15}, journal = {Structural Health Monitoring}, number = {6}, publisher = {Sage}, address = {London}, issn = {1475-9217}, doi = {10.1177/1475921716665803}, pages = {1 -- 20}, year = {2016}, abstract = {Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions.}, language = {en} } @article{LaarmannThomaMischetal.2023, author = {Laarmann, Lukas and Thoma, Andreas and Misch, Philipp and R{\"o}th, Thilo and Braun, Carsten and Watkins, Simon and Fard, Mohammad}, title = {Automotive safety approach for future eVTOL vehicles}, series = {CEAS Aeronautical Journal}, journal = {CEAS Aeronautical Journal}, publisher = {Springer Nature}, issn = {1869-5590 (Online)}, doi = {10.1007/s13272-023-00655-0}, pages = {11 Seiten}, year = {2023}, abstract = {The eVTOL industry is a rapidly growing mass market expected to start in 2024. eVTOL compete, caused by their predicted missions, with ground-based transportation modes, including mainly passenger cars. Therefore, the automotive and classical aircraft design process is reviewed and compared to highlight advantages for eVTOL development. A special focus is on ergonomic comfort and safety. The need for further investigation of eVTOL's crashworthiness is outlined by, first, specifying the relevance of passive safety via accident statistics and customer perception analysis; second, comparing the current state of regulation and certification; and third, discussing the advantages of integral safety and applying the automotive safety approach for eVTOL development. Integral safety links active and passive safety, while the automotive safety approach means implementing standardized mandatory full-vehicle crash tests for future eVTOL. Subsequently, possible crash impact conditions are analyzed, and three full-vehicle crash load cases are presented.}, language = {en} }