@article{KowalskiLinderZierkeetal.2016,
  author    = {Kowalski, Julia and Linder, Peter and Zierke, Simon and von Wulfen, Benedikt and Clemens, Joachim and Konstantinidis, Konstantinos and Ameres, Gerald and Hoffmann, Ruth and Mikucki, Jill A. and Tulaczyk, Slawek M. and Funke, Oliver and Blandfort, Daniel and Espe, Clemens and Feldmann, Marco and Francke, Gero and Hiecker, S. and Plescher, Engelbert and Sch{\"o}ngarth, Sarah and Dachwald, Bernd and Digel, Ilya and Artmann, Gerhard and Eliseev, Dmitry and Heinen, Dirk and Scholz, Franziska and Wiebusch, Christopher H. and Macht, Sabine and Bestmann, Ulf and Reineking, Thomas and Zetzsche, Christoph and Schill, Kerstin and F{\"o}rstner, Roger and Niedermeier, Herbert and Szumski, Arkadiusz and Eissfeller, Bernd and Naumann, Uwe and Helbing, Klaus},
  title     = {Navigation technology for exploration of glacier ice with maneuverable melting probes},
  series = {Cold Regions Science and Technology},
  journal   = {Cold Regions Science and Technology},
  number    = {123},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0165-232X},
  doi       = {10.1016/j.coldregions.2015.11.006},
  pages     = {53 -- 70},
  year      = {2016},
  abstract  = {The Saturnian moon Enceladus with its extensive water bodies underneath a thick ice sheet cover is a potential candidate for extraterrestrial life. Direct exploration of such extraterrestrial aquatic ecosystems requires advanced access and sampling technologies with a high level of autonomy. A new technological approach has been developed as part of the collaborative research project Enceladus Explorer (EnEx). The concept is based upon a minimally invasive melting probe called the IceMole. The force-regulated, heater-controlled IceMole is able to travel along a curved trajectory as well as upwards. Hence, it allows maneuvers which may be necessary for obstacle avoidance or target selection. Maneuverability, however, necessitates a sophisticated on-board navigation system capable of autonomous operations. The development of such a navigational system has been the focal part of the EnEx project. The original IceMole has been further developed to include relative positioning based on in-ice attitude determination, acoustic positioning, ultrasonic obstacle and target detection integrated through a high-level sensor fusion. This paper describes the EnEx technology and discusses implications for an actual extraterrestrial mission concept.},
  language  = {en}
}
@article{Kowalski2008,
  author    = {Kowalski, Julia},
  title     = {Mathematische Murgangmodellierung},
  series = {Newsletter Naturgefahren},
  volume    = {2008},
  journal   = {Newsletter Naturgefahren},
  number    = {2},
  organization    = {Eidgen{\"o}ssisches Institut f{\"u}r Schnee-und Lawinenforschung SLF},
  pages     = {4 -- 5},
  year      = {2008},
  language  = {de}
}
@article{KonstantinidisFloresMartinezDachwaldetal.2015,
  author    = {Konstantinidis, Konstantinos and Flores Martinez, Claudio and Dachwald, Bernd and Ohndorf, Andreas and Dykta, Paul and Bowitz, Pascal and Rudolph, Martin and Digel, Ilya and Kowalski, Julia and Voigt, Konstantin and F{\"o}rstner, Roger},
  title     = {A lander mission to probe subglacial water on Saturn's moon enceladus for life},
  series = {Acta astronautica},
  volume    = {Vol. 106},
  journal   = {Acta astronautica},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {1879-2030 (E-Journal); 0094-5765 (Print)},
  pages     = {63 -- 89},
  year      = {2015},
  language  = {en}
}
@article{KochBoehnischVerdoncketal.2024,
  author    = {Koch, Christopher and B{\"o}hnisch, Nils and Verdonck, Hendrik and Hach, Oliver and Braun, Carsten},
  title     = {Comparison of unsteady low- and mid-fidelity propeller aerodynamic methods for whirl flutter applications},
  series = {Applied Sciences},
  volume    = {14},
  journal   = {Applied Sciences},
  number    = {2},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2076-3417},
  doi       = {10.3390/app14020850},
  pages     = {1 -- 28},
  year      = {2024},
  abstract  = {Aircraft configurations with propellers have been drawing more attention in recent times, partly due to new propulsion concepts based on hydrogen fuel cells and electric motors. These configurations are prone to whirl flutter, which is an aeroelastic instability affecting airframes with elastically supported propellers. It commonly needs to be mitigated already during the design phase of such configurations, requiring, among other things, unsteady aerodynamic transfer functions for the propeller. However, no comprehensive assessment of unsteady propeller aerodynamics for aeroelastic analysis is available in the literature. This paper provides a detailed comparison of nine different low- to mid-fidelity aerodynamic methods, demonstrating their impact on linear, unsteady aerodynamics, as well as whirl flutter stability prediction. Quasi-steady and unsteady methods for blade lift with or without coupling to blade element momentum theory are evaluated and compared to mid-fidelity potential flow solvers (UPM and DUST) and classical, derivative-based methods. Time-domain identification of frequency-domain transfer functions for the unsteady propeller hub loads is used to compare the different methods. Predictions of the minimum required pylon stiffness for stability show good agreement among the mid-fidelity methods. The differences in the stability predictions for the low-fidelity methods are higher. Most methods studied yield a more unstable system than classical, derivative-based whirl flutter analysis, indicating that the use of more sophisticated aerodynamic modeling techniques might be required for accurate whirl flutter prediction.},
  language  = {en}
}
@article{KhayyamJamaliBabHadiasharetal.2020,
  author    = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalili, Mahdi and Naebe, Minoo},
  title     = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0},
  series = {IEEE Access},
  volume    = {8},
  journal   = {IEEE Access},
  number    = {Art. 9108222},
  publisher = {IEEE},
  address   = {New York, NY},
  issn      = {2169-3536},
  doi       = {10.1109/ACCESS.2020.2999898},
  pages     = {111381 -- 111393},
  year      = {2020},
  abstract  = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.},
  language  = {en}
}
@article{KhayyamJamaliBabHadiasharetal.2020,
  author    = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalil, Mahdi and Naebe, Minoo},
  title     = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0},
  series = {IEEE Access},
  journal   = {IEEE Access},
  publisher = {IEEE},
  address   = {New York, NY},
  isbn      = {2169-3536},
  doi       = {10.1109/ACCESS.2020.2999898},
  pages     = {1 -- 12},
  year      = {2020},
  abstract  = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.},
  language  = {en}
}
@article{KezerashviliDachwald2021,
  author    = {Kezerashvili, Roman Ya and Dachwald, Bernd},
  title     = {Preface: Solar sailing: Concepts, technology, and missions II},
  series = {Advances in Space Research},
  volume    = {67},
  journal   = {Advances in Space Research},
  number    = {9},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0273-1177},
  doi       = {10.1016/j.asr.2021.01.037},
  pages     = {2559 -- 2560},
  year      = {2021},
  language  = {en}
}
@article{HoevelerJanserBindewaldetal.2015,
  author    = {Hoeveler, Bastian and Janser, Frank and Bindewald, Thorsten and Gebhardt, Andreas},
  title     = {Entwurf, Fertigung und Untersuchung eines Windkanalmodells eines innovativen, senkrechtstartenden Kleinflugzeuges},
  series = {RTejournal - Forum f{\"u}r Rapid Technologie},
  journal   = {RTejournal - Forum f{\"u}r Rapid Technologie},
  number    = {12},
  publisher = {Fachhochschule Aachen},
  address   = {Aachen},
  issn      = {1614-0923},
  url       = {http://nbn-resolving.de/urn:nbn:de:0009-2-42921},
  pages     = {1 -- 5},
  year      = {2015},
  language  = {de}
}
@article{HoevelerBauknechtWolfetal.2020,
  author    = {Hoeveler, B. and Bauknecht, Andr{\´e} and Wolf, C. Christian and Janser, Frank},
  title     = {Wind-Tunnel Study of a Wing-Embedded Lifting Fan Remaining Open in Cruise Flight},
  series = {Journal of Aircraft},
  volume    = {57},
  journal   = {Journal of Aircraft},
  number    = {4},
  publisher = {AIAA},
  address   = {Reston, Va.},
  issn      = {1533-3868},
  doi       = {10.2514/1.C035422},
  year      = {2020},
  abstract  = {It is investigated whether a nonrotating lifting fan remaining uncovered during cruise flight, as opposed to being covered by a shutter system, can be realized with limited additional drag and loss of lift during cruise flight. A wind-tunnel study of a wing-embedded lifting fan has been conducted at the Side Wind Test Facility G{\"o}ttingen of DLR, German Aerospace Center in G{\"o}ttingen using force, pressure, and stereoscopic particle image velocimetry techniques. The study showed that a step on the lower side of the wing in front of the lifting fan duct increases the lift-to-drag ratio of the whole model by up to 25\% for all positive angles of attack. Different sizes and inclinations of the step had limited influence on the surface pressure distribution. The data indicate that these parameters can be optimized to maximize the lift-to-drag ratio. A doubling of the curvature radius of the lifting fan duct inlet lip on the upper side of the wing affected the lift-to-drag ratio by less than 1\%. The lifting fan duct inlet curvature can therefore be optimized to maximize the vertical fan thrust of the rotating lifting fan during hovering without affecting the cruise flight performance with a nonrotating fan.},
  language  = {en}
}
@article{HennPolaczek2007,
  author    = {Henn, Gudrun and Polaczek, Christa},
  title     = {Studienerfolg in den Ingenieurwissenschaften},
  series = {Das Hochschulwesen : HSW ; Forum f{\"u}r Hochschulforschung, -praxis und -politik},
  volume    = {55},
  journal   = {Das Hochschulwesen : HSW ; Forum f{\"u}r Hochschulforschung, -praxis und -politik},
  number    = {5},
  issn      = {0018-2974},
  pages     = {144 -- 147},
  year      = {2007},
  language  = {de}
}