@article{KreyerMuellerEsch2020,
  author    = {Kreyer, J{\"o}rg and M{\"u}ller, Marvin and Esch, Thomas},
  title     = {A Calculation Methodology for Predicting Exhaust Mass Flows and Exhaust Temperature Profiles for Heavy-Duty Vehicles},
  series = {SAE International Journal of Commercial Vehicles},
  volume    = {13},
  journal   = {SAE International Journal of Commercial Vehicles},
  number    = {2},
  publisher = {SAE International},
  address   = {Warrendale, Pa.},
  issn      = {1946-3928},
  doi       = {10.4271/02-13-02-0009},
  pages     = {129 -- 143},
  year      = {2020},
  abstract  = {The predictive control of commercial vehicle energy management systems, such as vehicle thermal management or waste heat recovery (WHR) systems, are discussed on the basis of information sources from the field of environment recognition and in combination with the determination of the vehicle system condition. In this article, a mathematical method for predicting the exhaust gas mass flow and the exhaust gas temperature is presented based on driving data of a heavy-duty vehicle. The prediction refers to the conditions of the exhaust gas at the inlet of the exhaust gas recirculation (EGR) cooler and at the outlet of the exhaust gas aftertreatment system (EAT). The heavy-duty vehicle was operated on the motorway to investigate the characteristic operational profile. In addition to the use of road gradient profile data, an evaluation of the continuously recorded distance signal, which represents the distance between the test vehicle and the road user ahead, is included in the prediction model. Using a Fourier analysis, the trajectory of the vehicle speed is determined for a defined prediction horizon. To verify the method, a holistic simulation model consisting of several hierarchically structured submodels has been developed. A map-based submodel of a combustion engine is used to determine the EGR and EAT exhaust gas mass flows and exhaust gas temperature profiles. All simulation results are validated on the basis of the recorded vehicle and environmental data. Deviations from the predicted values are analyzed and discussed.},
  language  = {en}
}
@article{KowalskiMcElwaine2013,
  author    = {Kowalski, Julia and McElwaine, Jim N.},
  title     = {Shallow two-component gravity-driven flows with vertical variation},
  series = {Journal of Fluid Mechanics},
  volume    = {714},
  journal   = {Journal of Fluid Mechanics},
  publisher = {Cambridge Univ. Press},
  address   = {Cambridge},
  isbn      = {0022-1120},
  pages     = {434 -- 462},
  year      = {2013},
  language  = {en}
}
@article{KowalskiLinderZierkeetal.2016,
  author    = {Kowalski, Julia and Linder, Peter and Zierke, S. and Wulfen, B. van and Clemens, J. and Konstantinidis, K. and Ameres, G. and Hoffmann, R. and Mikucki, J. and Tulaczyk, S. and Funke, O. and Blandfort, D. 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, D. and Heinen, D. and Scholz, F. and Wiebusch, C. and Macht, S. and Bestmann, U. and Reineking, T. and Zetzsche, C. and Schill, K. and F{\"o}rstner, R. and Niedermeier, H. and Szumski, A. and Eissfeller, B. and Naumann, U. and Helbing, K.},
  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{JanThimoBauerBieleetal.2019,
  author    = {Jan Thimo, Grundmann and Bauer, Waldemar and Biele, Jens and Boden, Ralf and Ceriotti, Matteo and Cordero, Federico and Dachwald, Bernd and Dumont, Etienne and Grimm, Christian D. and Hercik, David},
  title     = {Capabilities of Gossamer-1 derived small spacecraft solar sails carrying Mascot-derived nanolanders for in-situ surveying of NEAs},
  series = {Acta Astronautica},
  volume    = {156},
  journal   = {Acta Astronautica},
  number    = {3},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0094-5765},
  doi       = {10.1016/j.actaastro.2018.03.019},
  pages     = {330 -- 362},
  year      = {2019},
  language  = {en}
}