@article{GoettenHavermannBraunetal.2020,
  author    = {G{\"o}tten, Falk and Havermann, Marc and Braun, Carsten and Marino, Matthew and Bil, Cees},
  title     = {Improved Form Factor for Drag Estimation of Fuselages with Various Cross Sections},
  series = {Journal of Aircraft},
  journal   = {Journal of Aircraft},
  publisher = {AIAA},
  address   = {Reston, Va.},
  issn      = {1533-3868},
  doi       = {10.2514/1.C036032},
  pages     = {1 -- 13},
  year      = {2020},
  abstract  = {The paper presents an aerodynamic investigation of 70 different streamlined bodies with fineness ratios ranging from 2 to 10. The bodies are chosen to idealize both unmanned and small manned aircraft fuselages and feature cross-sectional shapes that vary from circular to quadratic. The study focuses on friction and pressure drag in dependency of the individual body's fineness ratio and cross section. The drag forces are normalized with the respective body's wetted area to comply with an empirical drag estimation procedure. Although the friction drag coefficient then stays rather constant for all bodies, their pressure drag coefficients decrease with an increase in fineness ratio. Referring the pressure drag coefficient to the bodies' cross-sectional areas shows a distinct pressure drag minimum at a fineness ratio of about three. The pressure drag of bodies with a quadratic cross section is generally higher than for bodies of revolution. The results are used to derive an improved form factor that can be employed in a classic empirical drag estimation method. The improved formulation takes both the fineness ratio and cross-sectional shape into account. It shows superior accuracy in estimating streamlined body drag when compared with experimental data and other form factor formulations of the literature.},
  language  = {en}
}
@inproceedings{GoettenFingerBraunetal.2019,
  author    = {G{\"o}tten, Falk and Finger, Felix and Braun, Carsten and Havermann, Marc and Bil, C. and Gomez, F.},
  title     = {Empirical Correlations for Geometry Build-Up of Fixed Wing Unmanned Air Vehicles},
  series = {APISAT 2018: The Proceedings of the 2018 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2018)},
  booktitle = {APISAT 2018: The Proceedings of the 2018 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2018)},
  publisher = {Springer},
  address   = {Singapore},
  isbn      = {978-981-13-3305-7},
  doi       = {10.1007/978-981-13-3305-7_109},
  pages     = {1365 -- 1381},
  year      = {2019},
  abstract  = {The results of a statistical investigation of 42 fixed-wing, small to medium sized (20 kg-1000 kg) reconnaissance unmanned air vehicles (UAVs) are presented. Regression analyses are used to identify correlations of the most relevant geometry dimensions with the UAV's maximum take-off mass. The findings allow an empirical based geometry-build up for a complete unmanned aircraft by referring to its take-off mass only. This provides a bridge between very early design stages (initial sizing) and the later determination of shapes and dimensions. The correlations might be integrated into a UAV sizing environment and allow designers to implement more sophisticated drag and weight estimation methods in this process. Additional information on correlation factors for a rough drag estimation methodology indicate how this technique can significantly enhance the accuracy of early design iterations.},
  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}
}
@book{JanserHavermannHoeveleretal.2023,
  author    = {Janser, Frank and Havermann, Marc and Hoeveler, Bastian and Hertz, Cyril and Bergmann, Ole},
  title     = {Str{\"o}mungslehre und Aerodynamik : inkompressible Profile und Tragfl{\"u}gelaerodynamik, Band 2},
  edition   = {4. Auflage},
  publisher = {Mainz},
  address   = {Aachen},
  isbn      = {978-3-8107-0261-6},
  pages     = {XIII, 211 Seiten},
  year      = {2023},
  abstract  = {Das vorliegende Buch dient als Grundlage f{\"u}r die Bachelor- und Master-Ausbildung von Studierenden im Fachgebiet Str{\"o}mungslehre und Aerodynamik. Im hier behandelten Teilbereich der inkompressiblen Profile und Tragfl{\"u}gelaerodynamik werden schwerpunktm{\"a}ßig die folgenden Themen besprochen: - Profilaerodynamik - Tragfl{\"u}gelaerodynamik - Flugzeugpolare - Methoden zur Flugbereichserweiterung - Schwebeschub und Schwebeleistung - Propellerblattaerodynamik - Numerische Methoden zur Tragfl{\"u}gelberechnung},
  language  = {de}
}