TY - GEN A1 - Feldmann, Marco A1 - Francke, Gero A1 - Espe, Clemes A1 - Chen, Qian A1 - Baader, Fabian A1 - Boxberg, Marc S. A1 - Sustrate, Anna-Marie A1 - Kowalski, Julia A1 - Dachwald, Bernd T1 - Performance data of an ice-melting probe from field tests in two different ice environments N2 - This dataset was acquired at field tests of the steerable ice-melting probe "EnEx-IceMole" (Dachwald et al., 2014). A field test in summer 2014 was used to test the melting probe's system, before the probe was shipped to Antarctica, where, in international cooperation with the MIDGE project, the objective of a sampling mission in the southern hemisphere summer 2014/2015 was to return a clean englacial sample from the subglacial brine reservoir supplying the Blood Falls at Taylor Glacier (Badgeley et al., 2017, German et al., 2021). The standardized log-files generated by the IceMole during melting operation include more than 100 operational parameters, housekeeping information, and error states, which are reported to the base station in intervals of 4 s. Occasional packet loss in data transmission resulted in a sparse number of increased sampling intervals, which where compensated for by linear interpolation during post processing. The presented dataset is based on a subset of this data: The penetration distance is calculated based on the ice screw drive encoder signal, providing the rate of rotation, and the screw's thread pitch. The melting speed is calculated from the same data, assuming the rate of rotation to be constant over one sampling interval. The contact force is calculated from the longitudinal screw force, which es measured by strain gauges. The used heating power is calculated from binary states of all heating elements, which can only be either switched on or off. Temperatures are measured at each heating element and averaged for three zones (melting head, side-wall heaters and back-plate heaters). KW - Ocean Worlds KW - Icy Moons KW - Cryobot KW - Analogue Environments KW - Melting Efficiency KW - Melting Performance KW - Melting Probe KW - Ice Melting Y1 - 2022 U6 - https://doi.org/10.5281/zenodo.6094866 N1 - Forschungsdaten zu "Field-test performance of an ice-melting probe in a terrestrial analogue environment" (https://opus.bibliothek.fh-aachen.de/opus4/frontdoor/index/index/docId/10889) ER - TY - CHAP A1 - Mayntz, Joscha A1 - Keimer, Jona A1 - Dahmann, Peter A1 - Hille, Sebastian A1 - Stumpf, Eike A1 - Fisher, Alex A1 - Dorrington, Graham T1 - Electrical Drive and Regeneration in General Aviation Flight with Propellers T2 - Deutscher Luft- und Raumfahrtkongress 2020 N2 - Electric flight has the potential for a more sustainable and energy-saving way of aviation compared to fossil fuel aviation. The electric motor can be used as a generator inflight to regenerate energy during descent. Three different approaches to regenerating with electric propeller powertrains are proposed in this paper. The powertrain is to be set up in a wind tunnel to determine the propeller efficiency in both working modes as well as the noise emissions. Furthermore, the planned flight tests are discussed. In preparation for these tests, a yaw stability analysis is performed with the result that the aeroplane is controllable during flight and in the most critical failure case. The paper shows the potential for inflight regeneration and addresses the research gaps in the dual role of electric powertrains for propulsion and regeneration of general aviation aircraft. KW - Propeller Aerodynamics KW - Flight Tests KW - Flight Mechanics KW - Electrical Flight KW - Inflight Regeneration, Recuperation Y1 - 2022 U6 - https://doi.org/10.25967/530100 N1 - Deutscher Luft- und Raumfahrtkongress 2020, 1. - 3. September 2020, Online PB - DGLR CY - Bonn ER - TY - CHAP A1 - Wahle, Michael ED - Reimerdes, Hans-G. T1 - Strukturmechanische Auslegung von Elastomer-Bauteilen in der Schwingungstechnik T2 - Kolloquium anläßlich des 70. Geburtstags von H. Öry : [29.09.1997 - 30.09.1997, Kármán-Auditorium, Hörsaal FO5, RWTH Aachen] Y1 - 1997 SP - 175 EP - 188 PB - Inst. für Leichtbau CY - Aachen ER - TY - PAT A1 - Wahle, Michael T1 - Gestaltung von plattenförmigen Hohlprofilen oder wellblechartigen Profilen : Offenlegungsschrift / Europäische Patentschrift T1 - Configuration of panel-shaped hollow profiles : patent of invention Y1 - 1989 PB - Deutsches Patent- und Markenamt / Europäisches Patentamt CY - München / Den Hague ER - TY - JOUR A1 - Fayyazi, Mojgan A1 - Sardar, Paramjotsingh A1 - Thomas, Sumit Infent A1 - Daghigh, Roonak A1 - Jamali, Ali A1 - Esch, Thomas A1 - Kemper, Hans A1 - Langari, Reza A1 - Khayyam, Hamid T1 - Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles N2 - 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. KW - optimization system KW - intelligent control KW - fuel cell vehicle KW - machine learning KW - artificial intelligence KW - intelligent energy management Y1 - 2023 U6 - https://doi.org/10.3390/su15065249 N1 - This article belongs to the Special Issue "Circular Economy and Artificial Intelligence" VL - 15 IS - 6 SP - 38 PB - MDPI CY - Basel ER - TY - PAT A1 - Wahle, Michael A1 - Peter, Roland T1 - Bismaleinimidharze : Offenlegungsschrift / Europäische Patentanmeldung T1 - Bio-maleimide resins Y1 - 1992 PB - Deutsches Patent- und Markenamt / Europäisches Patentamt CY - München / Den Hague ER - TY - CHAP A1 - Finger, Felix T1 - Comparative Performance and Benefit Assessment of VTOL and CTOL UAVs T2 - Deutscher Luft- und Raumfahrtkongress (DLRK) 2016, 13.-15.9.2016 Y1 - 2016 ER - TY - CHAP A1 - Peeken, Heinz A1 - Troeder, Christoph A1 - Schmidt, J. A1 - Rosenkranz, Josef T1 - Principles of machine noise reduction T2 - Inter-noise 85 : proceedings ; 1985 international conference on noise control engineering ; Munich, Sept. 18 - 20, 1985. - (Schriftenreihe der Bundesanstalt für Arbeitsschutz : Tagungsbericht ; 39) Y1 - 1985 SN - 3-88314-417-7 SP - 23 EP - 36 PB - Bundesanstalt für Arbeitsschutz [u.a.] CY - Dortmund [u.a.] ER - TY - JOUR A1 - Henn, Gudrun A1 - Polaczek, Christa T1 - Studienerfolg in den Ingenieurwissenschaften JF - Das Hochschulwesen : HSW ; Forum für Hochschulforschung, -praxis und -politik Y1 - 2007 SN - 0018-2974 VL - 55 IS - 5 SP - 144 EP - 147 ER - TY - JOUR A1 - Esch, Thomas T1 - Trends in commercial vehicle powertrains JF - ATZautotechnology N2 - Low emission zones and truck bans, the rising price of diesel and increases in road tolls: all of these factors are putting serious pressure on the transport industry. Commercial vehicle manufacturers and their suppliers are in the process of identifying new solutions to these challenges as part of their efforts to meet the EEV (enhanced environmentally friendly vehicle) limits, which are currently the most robust European exhaust and emissions standards for trucks and buses. KW - European Transient Cycle KW - Common Rail Injection System KW - Commercial Vehicle KW - Selective Catalytic Reduction KW - Diesel Engine Y1 - 2010 U6 - https://doi.org/10.1007/BF03247185 SN - 2192-886X VL - 2010 IS - 10 SP - 26 EP - 31 PB - Vieweg & Sohn CY - Wiesbaden ER -