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.
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Abbreviations
- AR:
-
= aspect ratio
- bref:
-
= reference wing span
- CD0:
-
= zero-lift drag coefficient
- Cfe:
-
= equivalent skin friction coefficient
- cref:
-
= reference chord length
- cross:
-
= cross sectional
- D:
-
= diameter
- EO/IR:
-
= electro-optical and infrared
- FR:
-
= fineness ratio
- fus:
-
= fuselage
- HT:
-
= horizontal tail
- L,l:
-
= length
- LG:
-
= landing gear
- MTOM:
-
= maximum take-off mass
- Ref:
-
= reference
- S:
-
= area
- TB:
-
= tail boom
- UAV:
-
= unmanned air vehicle
- V:
-
= tail volume coefficient
- VT:
-
= vertical tail
- W:
-
= width
- wet:
-
= wetted
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Götten, F., Finger, D.F., Braun, C., Havermann, M., Bil, C., Gómez, F. (2019). Empirical Correlations for Geometry Build-Up of Fixed Wing Unmanned Air Vehicles. In: Zhang, X. (eds) The Proceedings of the 2018 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2018). APISAT 2018. Lecture Notes in Electrical Engineering, vol 459. Springer, Singapore. https://doi.org/10.1007/978-981-13-3305-7_109
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