One of these critical models is responsible for estimating the new aircraft's parasitic drag. The accuracy of such underlying models is of critical importance as their outcomes drive the design to convergence. The design routine is divided into several sub-models that are responsible for estimating the new aircraft’s properties, including weight, propulsion, cost, or aerodynamics. The improved parasitic drag estimation yields a much heavier unmanned aircraft when compared to the sizing results using available drag data of manned aircraft.Ĭonceptual aircraft design is a multidisciplinary optimization problem. It is used to initially size an unmanned aircraft for a typical reconnaissance mission. The new equivalent skin friction coefficient accounts for these effects and is significantly higher compared to other aircraft categories. These components are responsible for almost half of an unmanned aircraft’s total parasitic drag. The UAV’s parasitic drag is significantly influenced by the presence of miscellaneous components like fixed landing gears or electro-optical sensor turrets. The aircraft is simulated using a validated unsteady Reynolds-averaged Navier Stokes approach. The new coefficient is derived from an aerodynamic analysis of ten different unmanned aircraft used for surveillance, reconnaissance, and search and rescue missions. 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.
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