# Introduction nmanned aerial vehicles (UAV) have a great application in military services [1]; further, their usage in civilian missions has been increasing incredibly [2,3]. The higher locomotion and maneuverability of UAVs have made aerial vehicles the common way to approach a goal to get data from ground or even to accomplish some actions such as the deployment of instrumentation. Aerial robotics seems an applied instrument to perform duties such as information and image detection of areas inaccessible using ground means, artistically photography, tracking, map building, and others. UAVs have been widely used for military applications, but, recently, they have been extended to civilian applications such as natural and human-made disasters scenarios, search and rescue, law enforcement, aerial mapping, traffic surveillance, inspection [4,5,6,7]. Their typical tasks include the reconnaissance of hazardous areas, commercial missions, traffic-controlling, and even in agricultural industry and so on [8,9,10]. Interest in aerobatic aircraft flight dynamic has also been fueled in recent years by the rapid growth in UAVs because of their mission capabilities [11] like approaching to birds landing maneuver that involves high angle-of-attack [12] in order to reduce the landing distance. Flight outside the normal envelop like this can be encountered in airplane stall situations or more generally upset scenarios, which demands a deep and wide research on the aerodynamics of two-dimensional airfoils and threedimensional wings and tails. It is obvious that many significant aerodynamics problems occur in low Reynolds numbers. Compared with high Reynolds numbers, low Reynolds number aerodynamics is quite different. Also characteristics of laminar separation at low Reynolds numbers have been widely studied by analytical, experimental and computational methods for decades. From analytical and experimental aspects, Horton [13] studied both theoretical and experimental method to recognize the short type of bubble in flow field around wing at low Reynolds number. Pauley et al. [14] simulated the flow around a two-dimensional airfoil and observed periodic vortex shedding. Phillips et al. [15] showed the effect of tail dihedral on the static stability and the usage of negative and positive tail dihedral. Dynamic stall occurs when unsteady angle of attack motion delays stall. This phenomenon is associated with leading edge vortex (LEV) formation. As the low pressure LEV grows, lift and drag coefficient rise until the stall point and then they drop dramatically. During the stage of dynamic stall beginning the concentrated vortex starts to develop and lifts off the upper surface thereafter. This procedure is influenced by different flow phenomena: In a low Reynolds number, flow transition from laminar to turbulent plays an important part in the development of the flow close to the airfoil leading edge [16][17][18][19]. Because of this significant load variation, understanding dynamic stall phenomena is critical for designing and controlling system operating under these conditions [20] # Specifications of Simulated Cases a) Aircraft Model The aircraft model considered in this study is based on a remote-control unmanned airplane FARID5 which is designed in Babol University of Technology. It has fixed-wing configuration with composite structure. There are three control surfaces; one of them in wing: aileron and the others in tail: elevator and rudder. The motor and propeller are mounted at the back of fuselage which makes the plane safer to operate [21]. The mentioned UAV presented in Fig. 1 and its essential properties are given in Table 1. # Computation Scheme a) Governing Equation We consider that the governing equations are the RANS equations where the two-dimensional, unsteady and incompressible assumed for flow specifications. Also gravity and the body force items in Cartesian tensor form are neglected: 0 i i u x ? = ? (1) 2 1 i j i i i j j i i j j u u u u p u u t x x x x x ? ? ? ? ? ? ? ? ? + = ? + ? ? ? ? ? ? ? (2) Where? is the kinematic viscosity of the air, u i is the velocity, ? and p are the density and pressure respectively and i j u u ? ? ? is the Reynolds stress. [22,23] # b) Turbulence Model For adverse pressure gradient flows and airfoil flows prediction, we should choose a proper turbulence model. For this reason, the shear stress transport (SST) k-? turbulence model [24] can precisely conduct this simulation. The SST model is written [25]: Numerical Study on Dynamic Stall of Low Reynolds Number Flow Around Boom Mounted U-Tail of FARIDUAV ( ) ( ) i k k k i j j k k k u G D t x x x ? ? ? ? ? ? ? ? ? + = + ? ? ? ? ? ? ? ? ? ? ?(3) The tail specifications are necessary requirements for aerodynamic modelling. The boom mounted U-tail type, shown in Fig. 1, which is used on the mentioned UAV, has three control surfaces. Two vertical components (rudder) obtain yawing stability and the horizontal one (elevator) generate pitching moment to control air craft rotation around the side-to-side axis. Tail configuration simulated is shown in Fig. 2 ( ) i w w w w i j j w w w u G D C t x x x ? ? ? ? ? ? ? ? ? + = + ? + ? ? ? ? ? ? ? ? ? ?(4) where # Result and Discussion # a) Horizontal tail results The elevator effectiveness is a measure of how effective the elevator deflection is in producing the desired pitching moment. There is a constraint on the elevator design which must be considered and checked. The elevator deflection must not cause the horizontal tail to stall but the results show, shown in Fig. 6, when elevator is deflected more than 13-15 degrees, flow separation over the tail tends to occur and lift coefficient decrease dramatically. Thus, the elevator will lose its effectiveness. Furthermore, close to horizontal tail, even a small downward elevator deflection can produce flow separation and lose of pitch control effectiveness. To prevent pitch control effectiveness, it is recommended to consider the elevator maximum deflection to be less than 15 degrees. This strategy can prevent the first stall which is the result of increasing angle of elevator deflection. It is obvious that stall phenomenon will occur with horizontal tail angle of attack increasing, even without elevator deflection, but it is important to know when it will show itself with elevator deflection. The results show that elevator deflection will decrease the tail stall angle; furthermore, the lift coefficient curve, shown in Fig. 6, presents that each angle of deflection decreases almost 0.35 degree of tail stall angle. At last, the lift and drag forces, shown in Table 3, which are generated by horizontal tail at 0 -degree angle of attack and 1 to 15 degree angle of deflection are provided. The rudder control power must be sufficient to accomplish directional trim and control requirement. The maximum allowable angle of rudder deflection should be found which will guarantee the high effectiveness of rudder and prevent the flow separation over the vertical tail. As shown in Fig. 12, the lift coefficient decrease at 17 degree dramatically; furthermore; drag coefficient will plunge from this angle of deflection, shown in Fig. 13. Finally, the lift and drag forces, shown in Table 3, are provided which are generated by horizontal tail at 0-degree angle of attack and 1 to 20 degree angle of deflection. # Conclusions Stall phenomenon and separation of horizontal and vertical tail were simulated numerically using Navier-Stokes equations to understand the angle of dynamic stall to preserve the effectiveness of tails at low Reynolds number. At low Reynolds number, turbulence occurs on both horizontal and vertical tail of UAV even with small angle of control surface deflection. As it increases, laminar separation emerges on upper trailing edge of tail; furthermore; its influence on lift and drag coefficient will be appeared. In horizontal tail, elevator deflection causes the stall phenomenon even at 0 degree AOA (angle of attack). Approaching the angle of deflection which reduces by enhancing of AOA, help us to find the maximum allowable angle of deflection which will prevent stall occurrence of horizontal tail, and also it will preserve tail's maximum effectiveness. The results show that mentioned angle of deflection is about 13 degree. Elevator deflection should be decreased 0.35 degree in front of every 1 degree growing of AOA in order to prevent stall. In vertical tail, the maximum allowable angle of rudder's deflection is investigated without AOA consideration. According to explanation in horizontal tail section, the mentioned degree is estimated about 17 degree which will guarantee the vertical tail highest efficiency. 12![Fig. 1: FARID5 UAVTable 1: Aircraft mass and geometry properties Quantity Mass m 8 kg Chord c 0.25 m Span 3.1 m Wing surface area S wing 0.775 m 2 b) Tail Model](image-2.png "Fig. 1 :Fig. 2 :") ![k ? and w ? indicate the effective diffusivity of k and w, k G and w G indicate generation of turbulence kinetic energy and generation of w respectively, D k and D w show the dissipation of k and w in turbulence, C w represents the cross-diffusion factor.c) Grid and boundary conditionsFor horizontal tail, an O-type layout, Fig.3, has been generated by elliptical method. The external computational boundaries are fixed at 40c from the surface, Fig.4. The location of the first row of cells bounding the surface kept y + <1.](image-3.png "") 3![Fig. 3: 2D mesh grid around horizontal tail](image-4.png "Fig. 3 :") 4![Fig. 4: Unstructured mesh topology with boundary conditions For vertical tail, an unstructured grid, Fig.5 and Fig.6, has been generated. These kinds of grid are identified by irregular connectivity and employ triangles in 2D and tetrahedral in 3D commonly [26].](image-5.png "Fig. 4 :") 5![Fig. 5: 3D mesh grid around vertical tail IV.](image-6.png "Fig. 5 :") 67![Fig. 6: Lift coefficient of horizontal tail section over the 0-deg angle of attack for elevator deflection of 0 to 15-deg](image-7.png "Fig. 6 :Fig. 7 :") 891011![Fig. 8: Pathline colored by velocity magnitude at 0 degree angle of elevator deflection](image-8.png "Fig. 8 :Fig. 9 :Fig. 10 :Fig. 11 :") 121314![Fig. 12: Lift coefficient over the ±45-deg angle of attack range for elevator deflection of 0, +15 and + 30](image-9.png "Fig. 12 :Fig. 13 :Fig. 14 :") 1516![Fig. 15: Lift force generated by horizontal tail over 1 to 15 degree of elevator deflection](image-10.png "Fig. 15 :Fig. 16 :") 1718![Fig. 17: Lift coefficient of vertical tail section over the 0 -deg angle of attack for rudder deflection of 0 to 20 -deg](image-11.png "Fig. 17 :Fig. 18 :") 19202122![Fig. 19: Pathlines colored by velocity magnitude at 0-deg angle of rudder deflection](image-12.png "Fig. 19 :Fig. 20 :Fig. 21 :Fig. 22 :") 2324![Fig. 23: Lift force generated by vertical tail over 1 to 20 degree of rudder deflection](image-13.png "Fig. 23 :Fig. 24 :") 2QuantityValueHorizontal tail surface area0.825 m 2Vertical tail surface area0.040 m 2Elevator surface area0.0275 m 2Rudder surface area0.020 m 2III. ( ) Volume XVII Issue VII VersionJournal of Researches in EngineeringGlobal( ) © 2017 Global Journals Inc. (US) * Unmanned Aircraft Systems Roadmap, 2005-2030, office of the secretary of defense DWeatherington 2005 USA * IAI's Micro/Mini UAV Systems-Development Approach, Infotech@ Aerospace AAbershitz DPenn ALevy AShapira ZShavit STsach 2005 AIAA Arlington, Virginia * Development of experimental small UAV equipped with cellular phone data link system DKubo SSuzuki TKagami Proceedings of 25th Congress of International Council of Aeronautical Sciences, International Council of the Aeronautical Sciences(ICAS) 25th Congress of International Council of Aeronautical Sciences, International Council of the Aeronautical Sciences(ICAS)Hamburg, Germany 2006 * Motion compensation and object detection for autonomous helicopter visual navigation in the COMETS system, Robotics and Automation AOllero JFerruz FCaballero SHurtado LMerino Proceedings. ICRA '04. 2004 IEEE International Conference on ICRA '04. 2004 IEEE International Conference on 2004. 2004 1 * Very high spatial resolution imagery for channel bathymetry and topography from an unmanned mapping controlled platform JLejot CDelacourt HPiégay TFournier MLTrémélo PAllemand Earth Surface Processes and Landforms 2007 32 * Geomorphological mapping with a small unmanned aircraft system (sUAS): feature detection and accuracy assessment of a photo grammetrically-derived digital terrain model CHHugenholtz KWhitehead OWBrown TEBarchyn BJMoorman ALeclair KRiddell THamilton Geomorphology 194 2013 * A Survey on Technologies for Automatic Forest Fire Monitoring, Detection and Fighting Using UAVs and Remote Sensing Techniques CYuan YZhang ZLiu Canadian Journal of Forest Research 7 2015. 2015 * Unmanned Aircraft Systems in the Civil Airworthiness Regulatory System: A Case Study CCuerno-Rejado RMartínez-Val Journal of Aircraft 48 4 2011 * An automatic object-based method for optimal thresholding in UAV images: Application for vegetation detection in herbaceous crops JTorres-Sánchez FLópez-Granados JM)Peña Computers and Electronics in Agriculture 114 2015 * Urban traffic analysis through an UAV GSalvo LCaruso AScordo Procedia-Social and Behavioral Sciences 111 2014 * Estimating angle of attack and sideslip under high dynamics on small UAVs JPerry AMohamed BJohnson RLind Proceedings of the 21st International Technical Meeting of the Satellite Division, the Institute of Navigation ION the 21st International Technical Meeting of the Satellite Division, the Institute of Navigation IONGeorgia, USA 2008 * A parametric study of fixed-wing aircraft perching maneuvers DVRao HTang THGo Aerospace Science and Technology 42 2015 * The structure of twodimensional separation HPHorton LLPauley PMoin WCReynolds Laminar separation bubbles in two and three dimensional incompressible flow 1968. 1990 220 University of London PhD Thesis * Effects of tail dihedral on static stability WFPhillips ABHansen WMNelson Journal of aircraft 6 2006 * Heat-flux gauge studies of compressible dynamic stall MSChandrasekhara MCWilder AIAA journal 41 5 2003 * Computation of oscillating airfoil flows with one-and two-equation turbulence models JAEkaterinaris FRMenter AIAA journal 32 12 1994 * AIAA 24th Fluid Dynamic Conference Orlando, FL AIAA 1993 transiently pitching airfoils * Numerical investigation of deep dynamic stall of a plunging airfoil MRVisbal AIAA journal 10 2011 * The phenomenon of dynamic stall, NASA TM-81264 WJMccroskey 1981 * Actuator fault-tolerant control based on gain-scheduled PID with application to fixed-wing unmanned aerial vehicle ISadeghzadeh YZhang 2nd International Conference on Control and Fault-Tolerant Systems 2013 * RANS computational fluid dynamics predictions of pitch and heave ship motions in head seas GDWeymouth RVWilson FStern Journal of Ship Research 49 2 2005 * Simulation of incompressible viscous flow around a ducted propeller using a RANS equation solver ASanchez-Caja PRautaheimo TSiikonen Proceedings of the 23rd Symposium on Naval Hydrodynamics the 23rd Symposium on Naval HydrodynamicsVal de Reuil, France 2000 * Two-equation eddy-viscosity turbulence models for engineering applications FRMenter AIAA journal 32 8 1994 * Compressibility Considerations for kw Turbulence Models in Hypersonic Boundary-Layer Applications CLRumsey Journal of Spacecraft and Rockets 47 1 2010 * Mesh generation MWBern PEPlassmann 2000 Elsevier Amsterdam