Aerospace Science and Technology 107 (2020) 106306 Contents lists available at ScienceDirect Aerospace Science and Technology www.elsevier.com/locate/aescte Wind-tunnel and CFD investigations of UAV landing gears and turrets – Improvements in empirical drag estimation Falk Götten a,b,∗ , Marc Havermann a , Carsten Braun a , Matthew Marino b , Cees Bil b a Department of Aerospace Engineering, FH Aachen University of Applied Sciences, Hohenstaufenallee 6, Aachen, 52064, Germany b School of Engineering, RMIT University, 264 Plenty Rd, Bundoora 3083, Australia a r t i c l e i n f o a b s t r a c t Article history: Received 5 August 2020 Received in revised form 12 October 2020 Accepted 16 October 2020 Available online 22 October 2020 Communicated by Cummings Russell Keywords: UAV Landing gear Turret Drag estimation Wind-tunnel CFD This paper analyzes the drag characteristics of several landing gear and turret configurations that are representative of unmanned aircraft tricycle landing gears and sensor turrets. A variety of these components were constructed via 3D-printing and analyzed in a wind-tunnel measurement campaign. Both turrets and landing gears were attached to a modular fuselage that supported both isolated components and multiple components at a time. Selected cases were numerically investigated with a Reynolds-averaged Navier-Stokes approach that showed good accuracy when compared to wind-tunnel data. The drag of main gear struts could be significantly reduced via streamlining their cross-sectional shape and keeping load carrying capabilities similar. The attachment of wheels introduced interference effects that increased strut drag moderately but significantly increased wheel drag compared to isolated cases. Very similar behavior was identified for front landing gears. The drag of an electro-optical and infrared sensor turret was found to be much higher than compared to available data of a clean hemisphere-cylinder combination. This turret drag was merely influenced by geometrical features like sensor surfaces and the rotational mechanism. The new data of this study is used to develop simple drag estimation recommendations for main and front landing gear struts and wheels as well as sensor turrets. These recommendations take geometrical considerations and interference effects into account.  2020 Elsevier Masson SAS. All rights reserved. 1. Introduction The relative parasitic drag of small-to-medium-sized fixed-wing unmanned aircraft (UAVs) is usually higher than larger aircraft categories like airliners or military transport aircraft [1]. This is mainly due to their specific mission scenarios and their compa- rably small size. Fixed-wing UAVs are often used on surveillance and reconnaissance missions and therefore equipped with gyro- stabilized electro-optical (EO/IR) sensor turrets. These turrets are externally attached to the lower airframe and can produce a con- siderable amount of drag. Most current fixed-wing surveillance and reconnaissance UAVs are also equipped with non-streamlined and fixed landing gears. Such landing gears can cause a substantial amount of parasitic drag [2]. Retractable landing gears might not result in any significant flight performance gains due to their in- creased weight and add a considerable level of complexity to the * Corresponding author at: School of Engineering, RMIT University, 264 Plenty Rd, Bundoora 3083, Australia. E-mail addresses: goetten@fh-aachen.de (F. Götten), havermann@fh-aachen.de (M. Havermann), c.braun@fh-aachen.de (C. Braun), matthew.marino@rmit.edu.au (M. Marino), cees.bil@rmit.edu.au (C. Bil). system [3]. Studies suggest that streamlining and fairing of UAV landing gears can offer drag savings and performance gains [3,4]. Recent research shows an increased interest in aerodynamic analyses of UAVs both in the context of aircraft design and para- sitic drag estimation [5–8]. An accurate parasitic drag estimation in UAV design is of utmost importance to provide reliable flight per- formance predictions. Both sensor turrets and landing gears play an outstanding role for UAVs, as they represent large external at- tachments protruding from the airframe. In general, the empirical drag estimation of bluff objects like landing gears and turrets re- lies on experience with comparable designs for which drag data is available. This technique does not directly account for the individ- ual shape and aerodynamic behavior of the specific components, which can result in significant errors in force approximation. The level of accuracy is usually accepted in early aircraft design stages. A substantial amount of drag data for large airliner landing gears is available due to the high interest in landing gear noise reduc- tion [9–12]. Such data is, however, not transferable to smaller UAVs as their landing gear configurations are vastly different from large airliners. Additionally, UAV landing gears operate at significantly lower Reynolds numbers. Recently available literature for aircraft and UAV design [13–17] refers directly (or indirectly via Hoerner https://doi.org/10.1016/j.ast.2020.106306 1270-9638/ 2020 Elsevier Masson SAS. All rights reserved.