This paper analyses the lateral stability of tailless CAMAR-3 Unmanned Aerial Vehicle (UAV) when its tail fin (i.e. V-tail) is reconfigured to the wingtips. A tailless UAV may have longer endurance time, compared to the present configuration of V-tail. Nevertheless, a tailless UAV may experience reduction in lateral stability due to loss of yaw control surfaces. In the preliminary design of tailless-winglets UAV, semi-empirical method is applied to estimate the aerodynamic lateral stability derivatives, in order to investigate the stability of both configurations of UAV. ThenThen, a dynamic test rig based on pure yawing motion is built, to measure the lateral stability derivatives of C_(n_β ) and C_(n_r ) in transient conditions. The time response data of pure yawing oscillation give the natural frequency and damping ratio that describe the aerodynamic derivatives as a result from wind-on and wind-off tunnel tests. The result indicates that UAV with either configurations are laterally stable. However, the tailless-winglets CAMAR has a 13.86% reduction in aerodynamic yawing-moment-due-to-sideslip derivative C_(n_β ), compared to CAMAR-3 with V-tail; whereas the aerodynamic yawing-moment-due-to-yaw-rate derivative C_(n_r ) of tailless-winglets CAMAR is 5.55% lesser than that of the CAMAR-3 with V-tail. The lateral stability degrades, as expected, caused by tail stabilizer removal. In conclusion, the idea of tail removal and using winglets as the directional controllers is feasible

Koo, Hwai Yeng Koo

Mansor, Shuhaimi

Mohd. Nasir, Mohd. Nazri

English

Universiti Teknologi Malaysia Institutional Repository

Journal of Transport System Engineering 6:1 (2019) 33–39 6:1 (2019) 33–39 | www.jtse.utm.my | eISSN 2289–9790 |  THE ANALYSIS OF LATERAL STABILITY OF TAILLESS CAMAR-3 WITH WINGLETS  Koo Hwai Yeng Koo, Dr. –Ing. Mohd Nazri bin Mohd Nasir, Prof. Ir. Dr. Shuhaimi bin Mansor*  School of Mechanical Engineering,  Faculty of Engineering Universiti Teknologi Malaysia 81310 UTM Johor Bahru, Johor, Malaysia  Article history Received  27 November 2019 Received in revised form  24 December 2019 Accepted  29 December 2019 Published  Online 29 December 2019  *Corresponding author shuhaimi@utm.my   GRAPHICAL ABSTRACT       KEYWORDS  Tailless UAV; dynamic wind tunnel test;  aerodynamic stability derivatives; lateral stability; winglets        ABSTRACT This paper analyses the lateral stability of tailless CAMAR-3 Unmanned Aerial Vehicle (UAV) when its tail fin (i.e. V-tail) is reconfigured to the wingtips. A tailless UAV may have longer endurance time, compared to the present configuration of V-tail. Nevertheless, a tailless UAV may experience reduction in lateral stability due to loss of yaw control surfaces. In the preliminary design of tailless-winglets UAV, semi-empirical method is applied to estimate the aerodynamic lateral stability derivatives, in order to investigate the stability of both configurations of UAV. ThenThen, a dynamic test rig based on pure yawing motion is built, to measure the lateral stability derivatives of C_(n_β ) and C_(n_r ) in transient conditions. The time response data of pure yawing oscillation give the natural frequency and damping ratio that describe the aerodynamic derivatives as a result from wind-on and wind-off tunnel tests. The result indicates that UAV with either configurations are laterally stable. However, the tailless-winglets CAMAR has a 13.86% reduction in aerodynamic yawing-moment-due-to-sideslip derivative C_(n_β ), compared to  CAMAR-3 with V-tail; whereas the aerodynamic yawing-moment-due-to-yaw-rate derivative C_(n_r ) of tailless-winglets CAMAR is 5.55% lesser than that of the CAMAR-3 with V-tail. The lateral stability degrades, as expected, caused by tail stabilizer removal. In conclusion, the idea of tail removal and using winglets as the directional controllers is feasible.. Journal of Transport System Engineering 6:1 (2019) 33–39  6:1 (2019) 33–39 | www.jtse.utm.my | eISSN 2289–9790 | 1.0 INTRODUCTION  The use of Unmanned Aerial Vehicles (UAVs) is growing exponentially across many civil and military applications due to their versality, ease of deployment, high-mobility and ability to hover [1]. Since demands for the use of UAV systems are increasing, enhancement of stability, performance and efficiency of the UAV is a vital and continuous research topic, in order to increase their safety and reliability during flight.  CAMAR is a medium size autonomous unmanned aircraft designed by UTM researchers to support the advancement of local UAV industries. The main goal of CAMAR is to be a high endurance autonomous unmanned aerial system, tailored for aerial observation and flight research facility. In order to achieve the missions, the CAMAR is required to have high endurance capability. Endurance depends mainly on aerodynamic design of the UAV. Conceptually, the main aerodynamic advantage of a tailless aircraft is its lower wetted area to volume ratio and lower interference drag, as compared to aircraft with conventional configuration. By removing the tail of CAMAR, weight and drag on CAMAR will be reduced and may result in longer endurance time [2] [3].  Nevertheless, a tailless configuration presents a unique challenge from the perspective of stability and control, when the main source of yaw control is lost [4]. In addition, Okonkwo and Smith [5] explained that a tailless aircraft has low yaw control authority due to its shorter moment arm, compared to aircrafts with conventional tail configuration. In brief, the downside of a tailless aircraft configuration is the reduction in directional stability and manoeuvrability due to the unavailability of vertical tail and traditional rudder for yaw control [6] [7]. As a result, a tailless CAMAR might lose its stability, especially in lateral direction. Hence, there is a compromisation between the performance and stability.   According to the research done by the Flight Control Division of Soviet Union Department of Defence, it was stated by Bowlus, et al. [8] that one of the most effective devices in generating yaw control power for a tailless fighter was an all moving wingtip. This view is shared by Liebeck [9], who proposed in using winglet rudders as primary directional stability and control surface. Baig, et al. [10] also suggested that winglets mounted at the wingtips can be used in place of the vertical tail to control yawing motion and reduce the strength of wingtip vortices. Therefore, for tailless aircraft that has swept-back wing (i.e. CAMAR-3), the winglets should be placed at the wingtip extremities to take advantage of the longest moment arm available, to enhance yaw stability.  Aerodynamic derivative determination is essential in analysing aircraft stability. Nonetheless, as pointed out by Musa [11], a new design of aircraft configuration will initially suffer the lack of aerodynamic derivatives. Most of the aircraft modelling were rely on steady-state measurements either through semi-empirical method or traditional static wind tunnel tests to attain the aircraft responses [4] [12] [13]. In preliminary design phase, it was suggested by Ciliberti, et al. [13] to assess the aircraft stability with semi-empirical method by estimating the aerodynamic stability derivatives. To evaluate aircraft lateral stability more accurately for unconventional aircraft configurations especially during transient conditions, a dynamic test rig based on pure yawing motion is required to measure the lateral stability derivatives of 𝐶𝑛𝛽  and 𝐶𝑛𝑟 . In accordance to the method developed by Mansor and Passmore [14], the transient aerodynamic derivatives of CAMAR-3 are estimated using the classical logarithmic decay method and comparing the wind-on and wind-off damping ratio and oscillatory frequency from dynamic wind tunnel test.     Journal of Transport System Engineering 6:1 (2019) 33–39  6:1 (2019) 33–39 | www.jtse.utm.my | eISSN 2289–9790 | 2.0 MODEL AND TEST SET-UP  2.1 Preliminary Design of Winglets With the same aspect ratio and taper ratio of the ruddervator of CAMAR-3 (Figure 1(a)), it was reconfigured to the wingtip of the tailless CAMAR (Figure 1(b)). In order to fit the winglet to the wingtip of CAMAR-3, without changing its major configuration including the wing dimension, the root chord of the winglet is as the same as the wingtip chord length, 0.16 m. The parameters of ruddervator and winglet are tabulated in Table 1.            (a)        (b) Figure 1: (a) Ruddervator of CAMAR-3 (b) Winglet of tailless CAMAR-3  Table 1: Parameters of ruddervator and winglet for CAMAR Parameters ruddervator Values for Ruddervator Values for Winglets  Root chord 0.200 𝑚 0.160 𝑚 Tip chord 0.110 𝑚 0.088 𝑚 Mean chord length 0.155 𝑚 0.124 𝑚 Span  0.310 𝑚 0.248 𝑚 Area 0.04805 𝑚2 0.03075 𝑚2 Taper Ratio 0.55 0.55 Aspect Ratio 2 2  2.2 Dynamic Wind Tunnel Test For dynamic wind-tunnel test, the clean configuration model of CAMARs are 3D-printed in scale 1:8 and a dynamic test rig is built as shown in Figure 2. The dynamic test rig is developed in such a way that the model is constrained for pure yawing motion. When the model is given an initial displacement in yaw angle  𝛽𝑜  and released, the motion will be recorded and analysed. The dynamic wind tunnel test was conducted using blower tunnel with a 0.46 m x 0.46 m test section, at Aero-Lab UTM. The test set-up is as shown in Figure 3. The oscillations of the models are obtained under two different freestream velocities of approximately 9.91 m/s and 14.15 m/s.  Journal of Transport System Engineering 6:1 (2019) 33–39  6:1 (2019) 33–39 | www.jtse.utm.my | eISSN 2289–9790 |    (a)        (b) Figure 2: (a) Side view and (b) Plan View of Dynamic Test Rig   Figure 3: Experimental setup for dynamic wind tunnel test   3.0 ESTIMATION OF AERODYNAMIC DERIVATIVES  For semi-empirical method, the aerodynamic lateral stability derivatives 𝐶𝑛𝑟  and 𝐶𝑛𝛽 , are estimated in accordance to Roskam [15]. For the purposes of this study, the aerodynamic loads are considered to act as stiffness and damping to the model motion. Generally, the aerodynamic stability derivatives are given by Nelson [16]:  𝐶𝑛𝛽 =𝑁𝛽 𝐼𝑧𝑧𝑄𝑆𝑏       (1) Journal of Transport System Engineering 6:1 (2019) 33–39  6:1 (2019) 33–39 | www.jtse.utm.my | eISSN 2289–9790 |  𝐶𝑛𝑟 =2𝑁𝑟 𝐼𝑧𝑧𝑢𝑜𝑄𝑆𝑏2      (2)  By comparing the standard second order characteristic equation (Eq.3) and the characteristic equation of pure yawing motion (Eq.4), the aerodynamic stiffness (Eq.5) and aerodynamic damping (Eq. 6) of oscillation can be determined.  𝑠2 + 2𝜁𝜔𝑛𝑠 + 𝜔𝑛2 = 0      (3)  𝑠2 − 𝑁𝑟𝑠 +𝑁𝛽 = 0      (4)  𝑁𝛽 = 𝜔𝑛2       (5)  𝑁𝑟 = −2𝜁𝜔𝑛       (6)  The damping ratio, 𝜁 and natural frequency, 𝜔𝑛  can be obtained from time response plot (as shown in Figure 4), along with the following equations:  𝜁 = 𝑐𝑜𝑠 𝑡𝑎𝑛−1𝜔𝑑𝜉𝜔𝑛       (7)  𝜔𝑛 =𝜔𝑑 1−𝜉2        (8)   Figure 4: Time response graph of CAMAR-3 with V-tail at 0 m/s and 9.91 m/s wind tunnel test. Journal of Transport System Engineering 6:1 (2019) 33–39  6:1 (2019) 33–39 | www.jtse.utm.my | eISSN 2289–9790 |  In accordance to Mansor and Passmore [14], the aerodynamic derivatives can be measured by comparing the wind-on and wind-off oscillatory frequency and damping ratio from time response resulted by dynamic wind tunnel test. Hence, the aerodynamic derivatives from wind tunnel test can be obtained from:  𝑁𝛽 =  𝜔𝑛2 𝑤𝑖𝑛𝑑 −𝑜𝑛 −  𝜔𝑛2 𝑤𝑖𝑛𝑑 −𝑜𝑓𝑓     (9)  𝑁𝑟 =  −2𝜁𝜔𝑛 𝑤𝑖𝑛𝑑 −𝑜𝑛 −  −2𝜁𝜔𝑛 𝑤𝑖𝑛𝑑 −𝑜𝑓𝑓     (10)   4.0 RESULTS AND DISCUSSION  The dynamic test rig must have low damping ratio and stiffness in order to detect the relatively small aerodynamic stiffness and damping. It is shown in Figure 5 that the test rig has sufficient sensitivity to detect the aerodynamic behaviour of the model. As airspeed increases, the aerodynamic effect becoming more obvious to show the difference between wind-on and wind-off conditions. It is indicated that greater airspeed results in shorter period of oscillation, hence increase in oscillatory frequency and greater aerodynamic stiffness, 𝑁𝛽 . For aerodynamic damping, 𝑁𝑟  at 9.91 m/s, no clear aerodynamic damping exists; but surprisingly the aerodynamic damping becoming less at 14.15m/s.  Figure 5: Time response graph of dynamic wind tunnel test at 0 m/s, 9.91m/s and 14.15 m/s.   Results have been obtained from time response data of dynamic wind-tunnel test at airspeed 9.91 m/s, which are similar to values estimated from semi-empirical method (as listed in Table 2 and Table 3). From Table 2, experimental result shows that tailless-winglets CAMAR has a 13.86% reduction in 𝐶𝑛𝛽 , compared to CAMAR-3 with V-tail; whereas 𝐶𝑛𝑟  of tailless-winglets CAMAR is 5.55% lesser than that of the CAMAR-3 with V-tail. The result indicates the tailless CAMAR with winglets is less effective in lateral stability, as expected due to tail removal.     Journal of Transport System Engineering 6:1 (2019) 33–39  6:1 (2019) 33–39 | www.jtse.utm.my | eISSN 2289–9790 |   Table 2: Computed result of 𝐶𝑛𝛽  from wind tunnel test and semi-empirical method at 9.91 m/s. Dynamic Wind Tunnel Test Semi-Empirical Method   Dimensional Aerodynamic Derivatives 𝑵𝜷 = 𝝎𝒏𝟐    (𝒓𝒂𝒅/𝒔)𝟐 Non-Dimensional Aerodynamic Derivatives, 𝑪𝒏𝜷 Non-Dimensional Aerodynamic Derivatives, 𝑪𝒏𝜷 Wind-Off Condition Wind-On Condition (Wind-On − Wind-Off) Condition CAMAR-3 with V-tail 99.8825 124.2968 24.4143 0.05398 0.05754 Tailless CAMAR 87.0309 108.3881 21.3572 0.04650 0.04468   Table 3: Computed result of 𝐶𝑛𝑟  from wind tunnel test and semi-empirical method at 9.91 m/s. Dynamic Wind Tunnel Test Semi-Empirical Method   Dimensional Aerodynamic Derivatives 𝑵𝒓 = −𝟐𝜻𝝎𝒏    𝒓𝒂𝒅/𝒔  Non-Dimensional Aerodynamic Derivatives, 𝑪𝒏𝒓 Non-Dimensional Aerodynamic Derivatives, 𝑪𝒏𝒓 Wind-Off Condition Wind-On Condition (Wind-On − Wind-Off) Condition CAMAR-3 with V-tail −1.2893 −1.5840 −0.2947 −0.04305 −0.03670 Tailless CAMAR −1.6005 −1.8832 −0.2827 −0.04066 −0.02047   5.0  CONCLUSION  The result of both dynamic wind-tunnel test and semi-empirical method has shown degradation in lateral stability when the tail is removed and winglets are used as directional controllers. However, the reduction in effectiveness is relatively small. Thus, the idea of tail removal and using winglets to act as yaw control surfaces is considered feasible.  REFERENCES   [1] S. Hayat, E. Yanmaz, and R. Muzaffar, "Survey on Unmanned Aerial Vehicle Networks for Civil Applications: A Communications Viewpoint," IEEE Communications Surveys and Tutorials, vol. 18, no. 4, pp. 2624-2661, 2016. [2] H. Karakas, E. Koyuncu, and G. Inalhan, "ITU Tailless UAV Design," Journal of Intelligent & Robotic Systems, vol. 69, no. 1-4, pp. 131-146, 2013. [3] J. Weierman and J. Jacob, "Winglet Design and Optimization for UAVs," in 28th AIAA Applied Aerodynamics Conference, 2010, p. 4224. [4] J. Park, J.-Y. Choi, Y. Jo, and S. Choi, "Stability Derivative Computation of Tailless Aircraft Using Variable-Fidelity Aerodynamic Analysis for Control Performance Analysis," in 54th AIAA Aerospace Sciences Meeting, 2016, p. 2024. Journal of Transport System Engineering 6:1 (2019) 33–39  6:1 (2019) 33–39 | www.jtse.utm.my | eISSN 2289–9790 | [5] P. Okonkwo and H. Smith, "Review of Revolving Trends in Blended-Wing-Body Aircraft Design," Progress in Aerospace Sciences, vol. 82, pp. 1-23, 2016. [6] G. Larkin and G. Coates, "A Design Analysis of Vertical Stabilisers for Blended-Wing-Body Aircraft," Aerospace science and technology, vol. 64, pp. 237-252, 2017. [7] X. Qu, W. Zhang, J. Shi, and Y. 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The analysis of lateral stability of tailless CAMAR-3 with winglets

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The analysis of lateral stability of tailless CAMAR-3 with winglets

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