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Empirical Correlations for Geometry Build-Up of Fixed Wing Unmanned Air Vehicles

  • 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.

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Metadaten
Author:Falk GöttenORCiD, Felix FingerORCiD, Carsten BraunORCiD, Marc Havermann, C. Bil, F. Gomez
DOI:https://doi.org/10.1007/978-981-13-3305-7_109
ISBN:978-981-13-3305-7
Parent Title (English):APISAT 2018: The Proceedings of the 2018 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2018)
Publisher:Springer
Place of publication:Singapore
Document Type:Conference Proceeding
Language:English
Year of Completion:2019
Date of the Publication (Server):2020/11/18
Tag:Correlations; Drag; Geometry; Statistics; Unmanned Air Vehicle
First Page:1365
Last Page:1381
Note:
APISAT 2018 - Asia-Pacific International Symposium on Aerospace Technology. 16-18 October 2018. Chengdu, China.


Lecture Notes in Electrical Engineering (LNEE, volume 459)
Link:https://doi.org/10.1007/978-981-13-3305-7_109
Zugriffsart:campus
Institutes:FH Aachen / Fachbereich Luft- und Raumfahrttechnik
FH Aachen / ECSM European Center for Sustainable Mobility