Design, Development and Testing of Shape Shifting Wing Model

Transcription

1 aerospace Article Design, Development Testing Shape Shifting Wing Model Dean Ninian Sam M. Dakka *, Department Engineering Math, Sheffield Hallam University, Howard Street, Sheffield S1 1WB, UK; * Correspondence: Tel.: These authors contributed equally to this work. Received: 19 August 2017; Accepted: 30 October 2017; Published: 1 November 2017 Abstract: The design development morphing (shape shifting) aircraft s an innovative technology that has potential to increase aerodynamic efficiency reduce noise signatures aircrafts was carried out. This research was focused on reducing lift-induced drag at flaps aeroil to improve design to achieve optimum aerodynamic efficiency. Simulation revealed a 10.8% lift increase for initial morphing 15.4% for optimized morphing as compared to design. At angles attack 0, 5, degrees, optimized has an increase in lift-to-drag ratio 18.3%, 10.5%, 10.6% 4% respectively when compared with. Simulations also showed that re is a significant improvement on distribution over lower surface morphing aeroil. The increase in flow smoothness reduction in vortex size reduced drag along trailing edge as a result an increase in on lower surface was experienced. A morphing reduced size vortices refore noise levels measured were reduced by up to 50%. Keywords: shape shifting s; morphing ; aerodynamics enhancements; experimental aerodynamics; computational fluid dynamics; NACA Introduction The aircraft industries are constantly looking for newer more innovative ways to increase aerodynamic efficiency to reduce fuel consumption. In recent years, this has become more challenging as aircraft configurations have been pushed to very limit aerodynamic efficiency. This implies that non- technology design needs to be developed [1] to have a substantial effect increasing aerodynamic efficiency. In recent years morphing has received great interest [2 5]. Morphing implies change shape aircraft structures tailored to optimize aircraft performance. This is because aircraft design is a compromise to meet various flight conditions for example a design to optimize take-f is not necessarily compatible with optimal design for cruise mission. The definition morphing is continuous smooth flexible change shape in order to maximize aerodynamic efficiency. A comprehensive review on morphing technologies was conducted by Rodriguez [4]. Two morphing aircraft structure concepts were developed through DARPA funding. The first concept was developed by Lockheed Martin in which structure has ability to reduce area while transitioning from loiter to high speed Mach number [6] second concept NextGen MFX-1 aircraft is based on flexible skin [7], which provides capability for s to change shapes tailored to specific mission prile. Wing morphing can be accomplished in multitude directions, one direction is changing spar this has been demonstrated by university Maryl development pneumatic telescopic spar for a UAV [8]. The or direction is Aerospace 2017, 4, 52; doi: /aerospace

2 Aerospace 2017, 4, change camber, this could improve flying performance aircraft including lift drag capabilities mainly during take-f ling manoeuver [9 14]. In past, a number approaches have been proposed for sealing gaps between high lift devices a brief overview se approaches is provided in order to demonstrate complexities proposed designs challenges associated with ir implementations, which highlights urgent need for innovative solutions to address this problem. Kunz [15] patented a mechanical device consisting additional flap connected to main flap via a sliding interface. Diller Miller [16] later on, patented mechanical/compliant transition to cover span-wise end-chord partial dislocations between flap. Their design is somehow cumbersome due to compliant Silicone elastomer skins that are reinforced by sliding mechanical rod acting to support variable length skin transitions. Caton et al. [17] patented a similar design two short rods sliding into elastomer skin as compared to mechanical one rod mechanism Diller Miller. This design change meant addition a component to cover joints which makes design even more complicated. In 2013, Boeing [18] introduced concept multiple ribs that slide in out a spanwise rod embedded within main feature covered elastomer skin sliding ribs is to cover changing transition length dislocations between flap. The patented design introduced ribs rotating tip concept to extend rib trailing edge length. Anor concept was introduced by NASA Langley in 2012 [19], wedge elastomer skin to bridge span-wise gap between flap. This concept was tested [20] noise reduction 3 db or higher for deflected flap was measured aerodynamic efficiency enhancement were verified but not quantified in wind tunnel tests. Furrmore, recent advances in designing proposing solutions based on an active camber morphing Fish Bone Active Camber (FishBAC) [21] concept showed promising results in wind tunnel tests [22] increased lift-to-drag ratio, making it a good cidate for pairing with or end transition morphing concepts. The FishBAC concept was extended [23] to introduce material structures to seal gaps created at end an active control morphing surface. A Morphing Elastically LteD (MELD) transition was introduced [23], which is capable bending twisting to perform smooth continuous deformation between connection ends active morphing camber surface fixed structure. Initially morphing structures were implemented on military aircrafts, however in recent years focus has shifted towards small aircrafts such as UAVs [24], this is due to lower aerodynamic loads which makes development implementation processes more efficient diverse. Also, time line for new product introduction is shorter, due to less rigor certification procedures fewer testing. A review study [24] discussed actuation systems categorized by actuation method implemented on airoil morphing using (lumped) actuators, SMA-like actuators PZT actuators to induce camber change thus provide lift augmentation. This paper explores design development a new type technology called shape shifting or morphing aircraft s. Morphing aircraft s are based on dynamics a bird, fundamentally ensuring that flow remains smooth disruption is minimized. This is accomplished by eliminating surface dislocations between flaps, reducing delaying formation vortices caused by lift-induced drag. These benefits will furr increase aircraft performance by reducing take-f distances, ling distances, increasing climb rates, increasing stability reducing overall noise generated by airframe. In addition, increase in lift can also lead to a reduction in size, which implies a reduction in overall weight a furr reduction in fuel consumption. 2. Current Sophisticated Morphing Wing Technology Morphing technology had received renewed attention during recent years due to material actuation systems rapid development. Few papers published primarily focused on mechanical structures dielectric smart polymers. These are experimental have a predicted timeline 50 years until integration currently only company in testing phase is Flexsys ir

3 Aerospace 2017, 4, compliant control surfaces are designed in conjunction with NASA US Air Force, however, ir research is not published publicly. Currently only competition for morphing technology is a company called Flexsys, y are developing a compliant control surface. Flexsys compliant control surfaces works with a combination monolithic joint-less mechanisms flexible material to achieve a flap which changes camber rar than a mechanical flap. Flexsys claim ir compliant control surface can achieve a 2% reduction in drag when retritted up to 12% with a complete trailing edge redesign, as well as an increase in lift by 14% [25] Mechanical Monolithic Joint-Less Mechanism Monolithic joint-less structures for morphing s are designs [26,27] that uses materials elastic properties to create a function, such as actuation or deflection. A monolithic joint-less mechanism [3] are designed so that structure doesn t have any joints loads are equally distributed throughout entire structure [26]. This load distribution ensures that no single joint experiences excessive loading, which leads to failure. This structure allows large deflections while minimizing strain. The main advantages to this type structure are, minimal assembly required, high reliability on repeated action, no joints, refore no need for lubrication no friction, can be designed using any resilient material, cyclic fatigue resistant [26]. Issues that can arise with this technology are improper design external loads. Should structure not be designed correctly loading may not be distributed equally across entire structure leading to failure from excessive loading or fatigue. The structure also needs to be designed to ensure it can withst external loads experienced throughout flight; se can be considerably high which might lead to sudden unexpected failure [27] Rib Based Morphing Trailing Edge The rib based morphing trailing edge design is a complex multi-component structural addition to ribs already installed in an aircraft. It consists four blocks connected to each or by a rotating joint along camber line; each block is also attached to a link rod. The blocks are capable rotating upwards downward, this allows blocks to act as a flap control surface [28]. When blocks are assembled attached onto s ribs an elastomer skin is attached along entire trailing edge, covering blocks. This achieves a smooth surface allows structure to deform without causing any breaks in surface [28]. The advantages this design are that each rib has a degree freedom, refore any block that is stopped from moving causes trailing edge to not change shape. Should actuator move n all blocks will move, causing a change in shape. In addition, this design also solves external loading issues as block assembly is directly attached onto s internal main structure, which means loads, will be transferred to Dielectric Smart Polymer Morphing Wing Smart polymer, specifically dielectric smart polymer, is a material that changes shape. These are also known as electroactive smart polymers y work by passing an electric current though m, this creates an actuation force in form material deformation [29]. The advantages using dielectric smart polymers is that y are very light weight can have relatively large strains during actuation, y also have very fast response times large actuation forces [29]. The disadvantage dielectric smart polymers is that y act as a capacitor when a current is run through m; refore, y need to be properly insulated to ensure safe operation [29] Transition Regions To ensure morphing s aerodynamic performance, transition regions are implemented between flap to ensure smooth flow. Transition regions designs ensure no gaps are created when flap moves, preventing high air flow towards a low- region. In addition to creating a smoor flow over, transition regions also reduce size, delay formation, vortices on flaps, which reduces noise, drag increases lift.

4 Aerospace 2017, 4, Concept Analysis Both design concepts shown in Table 1, are excellent choices for a morphing, each fer ir own advantages disadvantages but neir m are equal. The decision on which, is chosen is based on which has highest score for each different subcategories. Table 1. Concept design analysis. Concept Feature Dielectric Smart Polymer Elastomer Skin Cost 2 5 Maintainability 5 5 Performance 5 3 Installation Ease 2 5 Ease assembly 2 3 Weight 5 4 Environment Resistance 5 3 Safety 3 3 TOTAL The dielectric smart polymer design fers a lot benefits but its primary disadvantage is relatively more complex to assemble install. This implies that it would require a long installation time as well as special training to install maintain properly, this increases costs related to its operation. Anor issue with dielectric smart polymers is, related to safety concerns which require strict proper fuel storage insulation. The main advantage this design is reduction aircraft weight by eliminating requirement for mechanical flaps actuators. The elastomer skin design is simple but can achieve same effects as dielectric smart polymer design. The elastomer skin design would be slightly heavier than smart polymer design because it would still require mechanical flap structure. This is counteracted by low costs, ease maintenance, ease installation overall safety. Installing an elastomer design only requires to be covered in an elastomer skin which is attached using an adhesive. Maintenance would be as simple as visual inspections for cracking n complete replacement skin when material has reached its fatigue limit. When considering safety, elastomer skin design is superior because if failure occurs n re is still a working flap to generate lift. If smart polymer fails due to damage or loss an electric current n aircraft won t have any working high lift devices. Based on above discussion elastomer skin design had been pursued. 4. Initial Experimental Analysis 4.1. Wind Tunnel Testing Wind tunnel testing was carried out on two three models, NACA 009 optimized morphing. All s have same span chord as well as same flap dimensions: Wing Span 0.3 m, Aeroil Chord 0.15 m, Flap Span m, Flap Chord m, Flap Angle 25 (remains same throughout testing), Wing rotated at a point 26.7% chord (thickest point along chord) to accommodate fixture bar. This was also applied to CFD simulation. AF100 low speed open loop wind tunnel (TecQuipment Ltd., equipped with 3 components balance connected to a separate display unit to measure forces acting on model was utilized. The wind tunnel test section dimensions, Length = 0.6 m, Width = 0.3 m Height = 0.3 m. Aeroil NACA 009 was selected primarily to reduce prile drag as much as possible, as this study is concentrating on vortices being generated by deployment flaps. There were also costing simulation issues to consider, being self-funded cost had to be kept down for 3D printing

5 Aerospace 2017, 4, models. Aerospace The 2017, simulation 4, 52 was carried out on Ansys academic, refore re was a limitation ,000 cells for meshing. It was noted that cambered aeroils required a higher cell count, which Aerospace limited 512, , mesh cells 4, refinement. for 52 meshing. It was noted that cambered aeroils required a higher cell count, which 5 24 limited The models mesh refinement. were 3D printed using University printing facility rapid prototyping machine 512,000 The cells models for meshing. were 3D It printed was noted using that cambered University aeroils printing required facility rapid a higher prototyping cell count, machine which limited n sed down to remove rough surface created during 3D printing process. Once n mesh sed refinement. down to remove rough surface created during 3D printing process. Once model is finished, a 12 mm steel bar is installed at aerodynamic centre, 40 mm from leading model The is models finished, were a 12 3D mm printed steel bar using is installed University at aerodynamic printing facility centre, rapid 40 prototyping mm from machine leading edge. The finished models are shown in 1. Strict fabrication procedures where implemented to edge. n The sed finished down models to remove are shown rough in surface 1. Strict created fabrication during procedures 3D printing where process. implemented Once ensure model to ensure productions is finished, productions did a 12 meet did mm meet steel print bar print is specifications installed specifications shown aerodynamic shown in in centre, A1. A1. 40 mm from leading edge. The finished models are shown in 1. Strict fabrication procedures where implemented to ensure productions did meet print specifications shown in A1. 1. The finished 3D printed aeroil model; The finished 3D printed 1. The finished 3D printed aeroil model; The finished 3D printed optimized morphing aeroil model. optimized 1. morphing The finished aeroil 3D model. printed aeroil model; The finished 3D printed optimized Each model morphing was installed aeroil in model. wind tunnel test section tested at 0, 5, 10, degrees angle Each model attack was with installed a wind speed in wind 25 m/s. tunnel The data test was section collected tested at set intervals at 0, 5, 10, every s 20for degrees 20 angle s at all Each attack degrees model with was aangles wind installed speed attack, in this 25wind m/s. provides tunnel The data a test large section was amount collected tested data set at which 0, intervals 5, 10, can 15 n every be 20 analysed 0.5 degrees s for 20 s angle to ensure attack accurate with results. a wind Lift speed drag 25 m/s. data The was data at all degrees angles attack, this provides a large n was amount used collected to derive at set data which intervals every can n lift 0.5 be s for analysed drag. 20 to s ensure at all degrees accurate 2 shows results. angles difference attack, Lift drag in this provides data was n lift a large used between amount to derive optimized data which morphing can n lift be analysed drag. 2 to shows ensure accurate difference. results. inthe optimized Lift morphing drag data lift between was has n optimized an used increase to derive morphing lift by lift 14.8%, drag. 8.4%, 4% 22.6% shows at 0, 5, difference degrees in angle attack lift between respectively. optimized morphing. The optimized. morphing The optimized morphing has an increase has in an increase in lift by 14.8%, lift 8.4%, by 14.8%, 4% 8.4%, 2.6% at 0, 4% 5, % 15at degrees 0, 5, 10 angle 15 degrees attackangle respectively. attack respectively. 2. The lift on optimized morphing as angle attack increases. 2. The lift on optimized morphing as angle 2. The lift on optimized morphing as angle 4.2. Wind attack Tunnel increases. attack increases. Results Discussion 4.2. Wind Wind Tunnel tunnel Results tests showed Discussion that both initial morphing optimized have 4.2. significant Wind Tunnel improvements Results Discussion over. Although furr improvement from initial morphing Wind tunnel is tests minor showed would that cause both an increase initial morphing overall cost complexity optimized for design. have significant Wind tunnel The wind improvements tests showed tunnel data over that confirmed both that. initial morphing Although morphing design furr has improvement optimized potential from to increase initial have significant morphing lift generated, improvements by is up minor to 14.8% over would at 0 degrees cause angle. increase attack. Although in overall furr cost improvement complexity for from design. initial morphing The wind istunnel minordata confirmed would cause that an increase morphing in overall design cost has complexity potential to for increase design. lift generated, by up to 14.8% at 0 degrees angle attack.

6 Aerospace 2017, 4, Aerospace 2017, 4, 52 Aerospace 2017, 4, The s wind3 6 tunnel show data stard confirmed deviation that for morphing all design lift has drag potential data collected to increase during lift generated, s 3 6 byshow up tostard 14.8% at 0deviation degrees angle for all attack. lift drag data collected during tests wind tunnel, including interquartile range (indicated by green brown). The tests s at 3 6wind showtunnel, stard including deviation forinterquartile all range (indicated lift drag by data green collected brown). duringthe green brown boxes indicate difference between 75th 25th percentile or middle tests green at brown wind tunnel, boxes including indicate difference interquartile between range (indicated 75th by25th greenpercentile brown). or Themiddle 50% data s stard deviation, maximum minimum is also shown by upper green 50% brown boxes data s indicate stard deviation, difference between maximum 75th minimum 25th percentile is also shown or middle by upper 50% lower whiskers respectively. The experimental data was compared to NACA 009 prile with data s lower stard whiskers deviation, respectively. The maximum experimental minimum data was is also compared shown by to NACA upper 009 prile lower whiskers with no flap above results (with 25 degrees flap deflection) look reasonable see A2 in respectively. no flap The above experimental results (with data 25 was degrees compared flap deflection) to NACA 009 look prile reasonable with see no flap A2 in Appendix A. above Appendix results A. (with 25 degrees flap deflection) look reasonable see A2 in Appendix A. 3. Conventional lift wind tunnel tunnel data data stard stard deviation. deviation. 4. Conventional drag wind tunnel data stard deviation. 4. Conventional drag wind tunnel data stard deviation.

7 Aerospace 2017, 4, Aerospace 2017, 4, 52 Aerospace 2017, 4, Aerospace 2017, 4, Optimized 5. Optimized lift lift wind tunnel tunneldata datastard deviation. deviation. 5. Optimized lift wind tunnel data stard deviation. 6. Optimized drag wind tunnel data stard deviation. 6. Optimized 6. Optimized drag drag wind wind tunnel tunnel data data stard stard deviation. deviation. 6. Optimized drag wind tunnel data stard deviation. s s illustrates illustrates wind wind tunnel tunnel data data error error bar bar charts charts sho sho stard stard deviation deviation uncertainty uncertainty s s 7 10 for for 7 10 each each illustrates angle angle attack. wind attack. tunnel data error bar charts sho stard deviation deviation uncertainty for for each each angle angle attack Conventional Conventional lift lift wind wind tunnel tunnel error error bars. bars Conventional lift wind windtunnel tunnel error error bars. bars.

8 Aerospace 2017, 4, Aerospace 2017, 4, Aerospace 2017, 4, Aerospace 2017, 4, Conventional drag wind tunnel error bars Conventional Conventional drag drag wind wind tunnel tunnel error error error bars. bars. bars Morphing lift lift wind tunnel tunnel error error error bars. bars. bars. 9. Morphing lift wind tunnel error bars. 10. Morphing drag wind tunnel error bars Morphing Morphing drag drag wind wind tunnel tunnel error error bars. bars. 10. Morphing drag wind tunnel error bars Ansys-Fluent Ansys-Fluent Numerical Numerical Experimental Experimental Analysis Analysis 5. Ansys-Fluent Numerical Experimental Analysis 5. Ansys-Fluent Ansys-Fluent Ansys-Fluent Numerical simulation simulation was was Experimental carried carried out out at at Analysis 0, 0, 5, 5, degrees degrees angle angle attack, attack, at at m/s. m/s. Ansys-Fluent simulation was carried out at 0, 5, degrees angle attack, at 25 m/s. Ansys-Fluent simulation was carried out at 0, 5, degrees angle attack, at 25 m/s.

9 Aerospace 2017, 4, Aerospace 2017, 4, Ansys Solver Set-Up 5.1. Aerospace Ansys 2017, Solver 4, 52 Set-Up 9 24 Solver Each was used in Ansys fluent with based, steady state simulations. Flow 5.1. Solver Each Ansys Domain The Set-Up flow was domains used Ansys geometry fluent with is shown in based, steady 11, at state leading simulations. edge Flow Domain The flow domains geometry is shown in 11, at leading edge aeroil issolver Each a 1 m radius circle was which used in isansys revolved, fluent n with extruded based, 1.5 m. steady Thisstate allows simulations. formation aeroil is a 1 m radius circle which is revolved, n extruded 1.5 m. This allows formation vortices while Flow staying Domain The withinflow domains stware s geometry cell limit. is shown Thein flow domains 11, at details leading aredge highlighted in vortices while staying within stware s cell limit. The flow domains details are highlighted in aeroil 12. is a 1 m radius circle which is revolved, n extruded 1.5 m. This allows formation 12. vortices while staying within stware s cell limit. The flow domains details are highlighted in The flow domains geometry. 11. The flow domains geometry. 11. The flow domains geometry. 12. Details flow domains sketch. 12. Details flow domains sketch. Turbulence Models The turbulence 12. Details models & flow boundary domains conditions sketch. for all simulations are as follows: Turbulence Models The turbulence models & boundary conditions for all simulations are as Turbulence follows: Models The turbulence models & boundary conditions for all simulations are Energy On. as follows: Viscous K-epsilon, Energy On. Realizable & Non-equilibrium Wall Functions. Boundary Viscous K-epsilon, Conditions Turbulent Realizable & Non-equilibrium Intensity 5% & Turbulent Wall Functions. Energy On. viscosity ratio 10. Boundary Conditions Turbulent Intensity 5% & Turbulent viscosity ratio 10. Viscous K-epsilon, The turbulence models Realizable for & Non-equilibrium sections were selected Wall Functions. based information collected from The turbulence models for sections were selected based on information collected from Boundary (Ansys, 2006, Conditions Turbulent ANSYS Inc., Canonsburg, Intensity PA, USA). 5% Realizable & Turbulent k-epsilon viscosity was ratio selected 10. because (Ansys, 2006, ANSYS Inc., Canonsburg, PA, USA). Realizable k-epsilon was selected because possibility increased accuracy on RNG k-epsilon. It was also selected because its high accuracy The possibility for high turbulence increased boundary models accuracy on RNG k-epsilon. It was also selected because its high accuracy layer separation for large sections vortices. were selected based on information collected from (Ansys, for 2006, high boundary ANSYS Inc., layer Canonsburg, separation PA, large USA). vortices. Realizable k-epsilon was selected because possibility 5.1. Conventional increased Wing accuracy Ansys Simulation RNG k-epsilon. It was also selected because its high accuracy 5.1. Conventional Wing Ansys Simulation for high boundary 13 shows layer separation s large vortices. flow over aeroil, 13 shows s flow over aeroil, flow around flap, vortices in vortices wake is slightly lower than rest 5.2. Conventional flow around Wing Ansys flap, Simulation vortices in vortices wake is slightly lower than rest 13 shows s flow over aeroil, flow around flap, vortices in vortices wake is slightly lower than rest

10 Aerospace 2017, 4, Aerospace 2017, 4, saerospace wake.2017, The4,lift-induced drag reduced causing an increase in drag; this can be seen in 13 as re is a significant difference between vortices s 2017, wake. The lift-induced drag reduced causing an increase in Aerospace 4, s wake. The lift-induced drag reduced causing increase in generated rest in s in an centre vortices drag; this can be seen 13wake. as rethe is a significant difference between vortices is drag; thislower can be seen in 13reduced as wake. re isthe a significant difference between vortices s wake. The lift-induced causing increase in considerably than drag wake, shown in 14. This drag onis generated restrest s increates an centre vortices generated rest s wake. in centre is drag; this can be seen indownward 13 re isthe a significant difference vortices considerably lower than rest as wake, shown inoverall 14. creates drag onvortices,, by pushing flap reducing liftthis production. Inbetween addition, as angle considerably lower than rest wake, shown in 14. This creates drag on, generated rest s wake. The in centre vortices is by pushing flap downward reducing overall lift production. In addition, as angle attack attack is increased vortex size intensity were furr increased. This was corroborated by by pushing flap downward reducing overall lift production. In addition, as angle attack considerably lower than rest vortices wake, shown infor 14. This This creates on, is15. increased vortex size intensity were furr increased. was corroborated by , illustrates generated with rag angle attack 0 is increased vortex size intensity were furr increased. This was corroborated by 15. by pushing flap downward reducing overall lift production. In addition, as angle attack 15, illustrates vortices generated for with an angle attack degrees respectively, sho a larger vortex being generated by flap. This had 15,respectively, illustrates for This with an corroborated angle attack This 0 5 is increased vortex vortices size generated intensity furr increased. by 15. degrees sho a largerwere vortex being generated bywas flap. had demonstrated that Ansys is simulating correctly flow field refore ensuring accurate results degrees sho a largercorrectly vortex being generated by flapensuring. had 15,respectively, illustrates vortices generated for with an angle attack This 0 5 demonstrated that Ansys is simulating flow field refore accurate results are being produced for furr simulation. demonstrated that Ansys is simulating correctly flow field refore ensuring accurate results C p (-) CpC (-)p (-) degrees respectively, sho larger vortex being generated by flap. This had are being produced for furrasimulation. are being produced for furr simulation. demonstrated that Ansys is simulating correctly flow field refore ensuring accurate results are being produced for furr simulation. C p (-) CpC (-)p (-) (c) (c) 13. The s flow over a aeroil, vortices indicated 13. The s flow over (c)a aeroil, vortices indicated in 13. The0-degree angle s Side flowview; over a in red circle, attack Top view; (c) Rear aeroil, View. vortices indicated red circle, 0-degree angle attack Side view; Top view; (c) Rear View. in red 13. circle, attack Top view; (c) Rearaeroil, View. vortices indicated The0-degree angle s Side flowview; over a C p (-) CpC (-)p (-) in red circle, 0-degree angle attack Side view; Top view; (c) Rear View. 14. The low- at centre vortices at 0-degree angle attack. 14. The low- at centre vortices at 0-degree angle attack. 14. The low- at centre vortices at 0-degree angle attack. 14. The low- at centre vortices at 0-degree angle attack. 15. Images sho vortex size for at 0 degrees angle attack Imagesangle sho vortex size for at 0 degrees angle attack at 515. degrees attack. at 515. degrees attack. Imagesangle sho vortex size for at 0 degrees angle attack 15. Images sho vortex size for at 0 degrees angle attack at 5 degrees angle attack. at 5 degrees angle attack.

11 Aerospace 2017, 4, Aerospace 2017, 4, Initial Initial Morphing Morphing Wing Wing Ansys Ansys Simulation Aerospace 2017, 4, shows 16 shows lift data lift generated data generated by Ansys, by Ansys, a significant a significant increase increase in 5.2. Initial Morphing Wing Ansys Simulation lift when comparing lift when comparing initial morphing initial morphing.. 16 shows lift data generated by Ansys, a significant increase in lift when comparing initial morphing. 16. A graph sho lift results generated from Ansys for 16. A graph sho lift results generated from Ansys for initial morphing. initial morphing. 16. A graph sho lift results generated from Ansys for The simulation initial morphing data shows. that at 0, 5, degrees angle attack, re is an increase in lift The by simulation 10.8%, 4.3%, data 3.4% shows 1% that respectively. at 0, 5, degrees is a Cd versus anglecl graph. attack, The re data isshows an increase that in lift by 10.8%, initial The simulation morphing 4.3%, 3.4% data shows is 1% more respectively. that aerodynamically at 0, 5, efficient 17 degrees is a Cd than angle versus attack, Cl graph. re The. is an data increase The shows initial that lift morphing initial by 10.8%, morphing 4.3%, at 0, 3.4% 5, 10 is more 1% 15 respectively. aerodynamically degrees angle attack efficient 17 is a produces Cd than versus 10.8%, Cl graph. 4.3%, The 3.4% data. shows 1% The more that initial lift respectively, initial morphing as well as is a more maximum aerodynamically 2.5% reduction efficient in than drag. 18 shows. lift-to-drag The initial morphing at 0, 5, degrees angle attack produces 10.8%, 4.3%, 3.4% 1% more lift morphing ratio, glide ratio, 0, this 5, graph 10 shows 15 degrees a s angle ability attack respectively, as well as a maximum 2.5% reduction to glide produces in drag. during flight. 10.8%, 18A 4.3%, shows higher 3.4% glide lift-to-drag ratio 1% means more ratio, lift respectively, aircraft will be as able well to as travel a maximum furr distance 2.5% reduction without losing drag. as much altitude. 18 shows lift-to-drag or glide ratio, this graph shows a s ability to glide during flight. A higher glide ratio means ratio, The or glide initial ratio, morphing this graph shows has a s significantly ability to higher glide glide during ratio flight. than A higher glide ratio means, aircraft will be able to travel furr distance without losing as much altitude. especially aircraft at will low be angles able to travel attack. furr This distance implies less without engine losing power as much will be altitude. required during flight to The initial morphing has glide ratio than, maintain The initial altitude morphing refore less has fuel a significantly consumption. higher At 0, glide 5, 10 ratio 15 than degrees angle attack, especially especially initial morphing at low at low angles angles has an attack. increase This in implies glide ratio less engine 13.6%, power 5.3%, 5.8% will will be be required 3.1% required respectively. during during flight flight to to maintain maintain altitude refore less fuel consumption. At At0, 0, 5, 5, degrees angle angle attack attack initial initial morphing has has an an increase in glide ratio 13.6%, 5.3%, 5.8% 3.1% 3.1% respectively. 17. A graph sho Coefficient drag versus lift for initial morphing A graph A graph sho Coefficient drag versus lift lift for for initial initial morphing morphing..

12 Aerospace 2017, 4, Aerospace 2017, 4, Aerospace 2017, 4, A graph sho Lift/drag orwise known as glide ratio for 18. A graph sho Lift/drag orwise known as glide ratio for initial morphing. initial 18. morphing A graph sho. Lift/drag orwise known as glide ratio for initial morphing. 19 shows s over lower side initial morphing 19 shows respectively. The s overs lower side at flap is slightly lower initial 19 shows s over lower side initial morphing became morphing suddenly respectively. lower respectively. at The flap The dislocation s from s surface. at at flap This is is flap slightly because is slightly lower lift-induced lower became suddenly drag, became which lower suddenly results at lower in flapsudden dislocation flap dislocation from drop from refore surface. increases surface. This isthis in because is because drag lift-induced as lift-induced well as drag, which reduction drag, results which inlift sudden results production. in sudden drop refore drop increases refore inincreases in drag as well drag as reduction as well as in lift production. reduction The initial in lift morphing production. in 19 doesn t suffer from this, because re is no gap between flap surface, distribution is enhanced along lower surface The initial The initial morphing in doesn t suffer from this, because re is isno nogap gapbetween. The on lower surface initial morphing is also slightly higher as flap flap surface, surface, distribution distribution enhanced is enhanced along along lower lower surface surface. compared to. The elimination gaps between flap surface The. The on lower on surface lower surface initial morphing initial morphing is also slightly is also higher slightly as compared higher as to caused along bottom morphing to increase distribution compared to enhancement. was experienced The elimination. over The s gaps elimination surface. between Therefore, flap gaps between aerodynamic surface flap caused performance surface caused along bottom morphing to increase distribution as along compared bottom to morphing was enhanced to increase due to lift increase distribution a reduction in enhancement drag was enhancement was experienced over s surface. Therefore, aerodynamic performance as experienced along over. s surface. Therefore, aerodynamic performance as compared to compared to was enhanced due to lift increase a reduction in drag was enhanced due to lift increase a reduction in drag along. along. C p (-) C p (-) 19. Cont.

13 Aerospace 2017, 4, Aerospace 2017, 4, Aerospace 2017, 4, (c) (d) 19. The (c) Conventional upper (d) surface; Initial morphing Wing 19. The Conventional upper surface; Initial morphing Wing Upper Surface; (c) Conventional lower surface; (d) Initial morphing Wing lower Surface. Upper Surface; 19. The (c) Conventional lower Conventional surface; (d) Initial upper morphing surface; Wing Initial lower morphing Surface. Wing Upper Surface; (c) Conventional lower surface; (d) Initial morphing Wing lower Surface Optimized Morphing Wing Simulation 5.4. Optimized Morphing Wing Simulation 5.3. Optimized 20 Morphing shows Wing s Simulation lift for all s, each design has a significant increase in 20 shows lift, highest s being lift optimized for all morphing s,. each design Overall has at 0, a5, significant degrees increase in 20 shows s lift for all s, each design has a significant increase in angle attack lift, highest optimized being morphing optimized have morphing an increase. lift Overall by 15.4%, at 0, 7.5%, 5, 105% 151.8% degrees lift, highest being optimized morphing. Overall at 0, 5, degrees angle respectively attack when optimized compared morphing to have. anat increase 0, 5, 10 in lift 15 degrees by 15.4%, 7.5%, optimized 5% angle attack optimized morphing have an increase in lift by 15.4%, 7.5%, 5% 1.8% 1.8% respectively has an increase when compared 4.6%, 3.2%, to1.7% 0.9% respectively,. when At 0, compared 5, 10 to 15 degrees initial shape shifting respectively when compared. At 0, 5, degrees optimized optimized. has has an an increase increase 4.6%, 4.6%, 3.2%, 3.2%, 1.7% 1.7% 0.9% respectively, 0.9% respectively, when compared when compared to initial toshape initial shifting shape shifting A graph sho lift for, initial morphing optimized morphing. 20. A 20. graph A graph sho sho lift lift for for,, initial initial morphing morphing optimized morphing. optimized morphing 21 shows. an efficiency graph for all three designs, using drag over lift. Lift production for each morphing s was enhanced compared with 21 shows an efficiency graph for all three designs, using drag over, while producing less drag. Conventional to optimized morphing 21 shows lift. Lift an production efficiency graph for each for all three morphing designs, s was using enhanced compared drag with over comparison revealed up to 5% drag reduction was experienced by optimized morphing lift., Liftwhile production producing forless eachdrag. Conventional morphing s to was optimized enhanced morphing compared with dependent on angle attack. The optimized morphing to initial shape shifting comparison, revealed while up producing to 5% drag reduction less drag. was Conventional experienced by optimized to optimized morphing morphing comparison showed drag reduction by up to 2.7%. 22 illustrates lift-to-drag ratio or glide ratio dependent comparison on angle revealed attack. up to 5% The drag optimized reduction morphing was experienced to initial by shape optimized shifting morphing highest magnitude increase is evident for optimized morphing. At angles attack 0, 5, comparison 10 dependent showed 15 degrees on angle drag optimized reduction attack. by The up to has an optimized 2.7%. increase in morphing 22 illustrates lift-to-drag lift-to-drag ratio or glide ratio ratio to 18.3%, initial 10.5%, shape 10.6% shifting highest magnitude increase is evident for optimized morphing. At angles attack 0, 5, 4% comparison respectively, showed compared drag with reduction by up to. 2.7%. While optimized 22 illustrates lift-to-drag compared with ratio or degrees optimized has an increase in lift-to-drag ratio 18.3%, 10.5%, 10.6% glide ratio initial highest morphing magnitude has increase an increase is evident 4.7%, for 5.3%, 4.8% optimized 0.9% morphing at 0, 5, At degrees angles 4% respectively, compared with. While optimized compared with attack respectively. 0, 5, degrees optimized has an increase in lift-to-drag ratio 18.3%, initial morphing has an increase 4.7%, 5.3%, 4.8% 0.9% at 0, 5, degrees 10.5%, 10.6% 23 4% shows respectively, evolution compared withdistribution along. lower While surface optimized each respectively. compared configurations. Each has a different maximum on its lower surface, with23 shows initial morphing evolution has an increase distribution 4.7%, along 5.3%, lower 4.8% surface 0.9% each at 0, 5, degrees 0.75 for, for initial morphing for optimized configurations. respectively. Each has a different maximum on its lower surface, 0.75 for 23 shows evolution, for distribution initial morphing along lower surface for each optimized configurations. Each has a different maximum on its lower surface, 0.75 for

14 Aerospace 2017, 4, Aerospace 2017, 4, , for initial morphing for optimized morphing. Aerospace 2017, 4, Thismorphing shows that optimized experienced a much higher along its lower surface Aerospace 2017, 4, 52This shows that optimized experienced a much higher along 14 its than 24. morphing. This shows that optimized experienced a much higher along its initial morphing. lower surface than initial morphing. lower surface. than This initialexperienced morphing. morphing shows that optimized a much higher along its lower surface than initial morphing. 21. A graph sho efficiency using drag over lift for 21. A graph sho efficiency using graph sho efficiency using drag dragover over lift liftfor foreach each 21. A s. s. each 21.s. A graph sho efficiency using drag over lift for each s. 22. A graph sho lift-to-drag ratios or glide ratios for all three s. 22. A graph sho lift-to-drag ratios or glide ratios for all three s. 22. A graph sho lift-to-drag ratios or glide ratios for all three s. C pc(-) p (-) C p (-) 22. A graph sho lift-to-drag ratios or glide ratios for all three s. 23. Cont.

15 Aerospace 2017, 4, Aerospace 2017, 4, (c) (d) (e) (f) 23. The distribution along upper surface ; 23. The distribution along upper surface ; along upper surface initial morphing ; (c) along upper surface optimized along upper surface initial morphing ; (c) along upper surface optimized morphing ; (d) along lower surface ; (e) along lower surface morphing ; (d) along lower surface ; (e) along lower surface initial morphing ; (f) along lower surface optimized morphing. initial morphing ; (f) along lower surface optimized morphing. Comparison evaluation lower surface optimized with initial Comparison indicated evaluation significant differences lowerin surface overall optimized distribution. At with trailing initial edge (left indicated side), low significant areas differences are significantly in overall reduced, as well distribution. as much higher At trailing edgeat leading (left edge side), (right low side). The increase areas in are significantly created reduced, higher lift aswhich well as was much experienced by optimized, as well as increase in flow smoothness due to curvature higher at leading edge (right side). The increase in created higher lift which was transition regions. Furrmore, drag is significantly reduced on optimized experienced by optimized, as well as increase in flow smoothness due to curvature because regions with extremely low on are almost eliminated. transition regions. Furrmore, drag is significantly reduced on optimized Upper surfaces comparison, initial morphing optimized morphing because s are regions illustrated with in extremely 24. low The along on trailing edge are almost (left side) eliminated. increased significantly, Upper surfaces due comparison to vortex size reduction, as well as initial a delay morphing vortex optimized formation. morphing This effect s are illustrated reduced in drag 24. The caused significant along changes trailing to edge in wake (left side) increased. significantly, The due to vortex (top size left, reduction 24a) asis well compared as a delay to a morphing vortex (top formation. right This bottom effect reduced middle, 24b,c), drag morphing causeds significant experienced changes less tochaotic behaviour in wake is. The more equalized resulting (top in left, less drag. 24a) One is compared major benefits to a morphing optimized (top right is that bottom middle, increased curvatures 24b,c), on morphing flap transition s experienced regions allowed less chaotic smoor behaviour flow to occur, which reduced is more equalized resulting drag, invortex less drag. size Onecaused a major delayed benefits formation optimized vortices on is. that increased 25 shows s above below surface s, red circles indicate curvatures on flap transition regions allowed smoor flow to occur, which reduced vortex which is being generated by flaps. The s vortex (top left, drag, vortex size caused a delayed formation vortices on. 25 shows 25a) is significantly lower in much larger in size than morphing s (top s above below surface s, red circles indicate vortex which is being generated by flaps. The s vortex (top left, 25a) is significantly lower in much larger in size than morphing s (top right

16 Aerospace 2017, 4, Aerospace 2017, 4, bottom centre, 25b,c), optimized shape shifting has highest- vortex Aerospace 2017, 4, refore right an overall bottom higher centre, wake 25b,c), optimized reduced shape shifting drag. has highest- vortex right 26 shows bottom refore centre, an overall distribution higher 25b,c), optimized wake along shape upper shifting reduced lower surface has drag. highest- each at location vortex where vortices refore 26 shows are an overall generated higher distribution flap. wake along The upper reduced lower surface experienced drag. each a significant at drop location in where 26 on shows vortices both are top generated istribution bottom surface flap. along The upper lower as flow surface experienced approached each a significant at trailing edge drop (chord location in length where = vortices on 0.04 both toare 0.11 generated top m). This bottom on is due surface flap. to The large vortex as flow that approached is generated experienced at trailing a this significant location, edge it resulted (chord drop in length = 0.04 on toboth drop 0.11 which m). top This consequently bottom is due surface to increased large vortex as that flow is drag. generated approached Comparison at this trailing location, between edge it resulted (chord length = to0.04 to initial 0.11 drop m). which This optimized consequently is due to morphing increased large, vortex revealed that drag. is generated a Comparison major difference at this between location, between it to initial optimized morphing, revealed a major difference between upper resulted lower surface to drop s. which consequently With morphing increased s, as drag. flow Comparison approached between trailing upper lower surface s. With s, as flow approached trailing it increased instead, thisto is because initial optimized reduction morphing vortex, sizerevealed delay a major in formation. difference between it increased upper instead, lower this surface is because s. With reduction morphing vortex s, size as delay flow in approached formation. trailing it increased instead, this is because reduction in vortex size delay in formation. C p (-) C p (-) C p (-) C p (-) (c) 24. Images sho for (c) flow over ; Initial morphing 24. Images ; sho (c) optimized morphing for all at 5 flow degrees over angle attack. ; Initial 24. Images sho for flow over ; Initial morphing ; (c) optimized morphing all at 5 degrees angle attack. morphing ; (c) optimized morphing all at 5 degrees angle attack. C p (-) C p (-) 25. Cont.

17 Aerospace 2017, 4, Aerospace 2017, 4, Aerospace 2017, 4, C p (-) C p (-) (c) 25. Images sho cut plots at location where vortices are generated on each 25. Images sho cut plots at location (c) where vortices are generated on each s s flap at 5 degrees angle attack ; Initial morphing ; (c) flap at 5 degrees optimized 25. Images angle morphing sho attack. cut plots at ; location where Initial vortices morphing are generated ; (c) on optimized each morphing s. flap at 5 degrees angle attack ; Initial morphing ; (c) optimized From morphing 26 re. is a clear evidence differences in behaviour, From is much 26 more re chaotic is a than clear evidence morphing s differences which in furr support behaviour, main explanation for From is much efficiency moreincrease. 26 re is a clear evidence differences in behaviour, chaotic than morphing s which furr support main explanation for is much more chaotic than morphing s which furr support main explanation for efficiency increase. efficiency increase. 26. A graph sho distribution along each at location where vortices are generated on flap at 5 degrees angle attack. 26. A graph sho distribution along each at location where vortices 26. A graph sho distribution along each at location where vortices 5.4. are Wind generated Tunnel on Testing flap at Simulation 5 degrees angle Comparison attack. (Validation) are generated on flap at 5 degrees angle attack Wind Tunnel 27, illustrates Testing Simulation Comparison lift versus (Validation) angle attack for wind tunnel simulation 5.5. Wind data. Tunnel It is observed Testing that Simulation results Comparison are very similar. (Validation) For at 0, 5, degrees Angle 27, illustrates Attack (AOA), percentage lift versus differences angle between attack for wind simulation tunnel wind simulation tunnel data. tests It are is 27, 1.87%, observed illustrates 0.04%, that 1.8% results 0.86% are respectively very lift versus similar. for angle For attack for lift. wind Therefore, tunnel at 0, results 5, 10 simulation obtained 15 data. degrees from It is observed Ansys Angle simulation that Attack results (AOA), are accurate are very percentage within similar. 1.87% differences For wind between tunnel tests. simulation For 0, 5, optimized 10wind 15 tunnel degrees Angle tests percentage are Attack 1.87%, (AOA), 0.04%, difference 1.8% percentage between 0.86% differences respectively simulation between for wind tunnel simulation tests lift. is Therefore, 1.3%, 0.8%, wind results 0.8% tunnel obtained tests 0.8% are 1.87%, from respectively. 0.04%, Ansys 1.8% simulation This implies 0.86% are respectively accurate optimized within for 1.87% is accurate wind lift. within Therefore, tunnel 1.3%. tests. results For obtained optimized from Ansys simulation percentage are accurate difference within between 1.87% simulation wind tunnel wind tests. tunnel For tests optimized is 1.3%, 0.8%, 0.8% percentage 0.8% respectively. This implies optimized is accurate within 1.3%. difference between simulation wind tunnel tests is 1.3%, 0.8%, 0.8% 0.8% respectively. This implies optimized is accurate within 1.3%.

18 Aerospace 2017, 4, Aerospace 2017, 4, Aerospace 2017, 4, A graph sho s lift for Ansys simulation wind tunnel testing. 27. A graph sho s lift for Ansys simulation wind tunnel testing shows A graph sho s drag data lift for Ansys both simulation wind experimental tunnel testing. data for 28 shows optimized morphing drag data. forat both 0, 5, simulation degrees experimental angle attack data for percentage 28 shows difference optimized between simulation morphing drag data. for both measured At 0, simulation data 5, 10 for 15 experimental degrees angle data for is attack 1.04%, optimized morphing. At 0, 5, degrees angle attack percentage 6.75%, 1.43% difference 4.19% between respectively. simulation For optimised measured data forpercentage difference is 0.49%, is 1.04%, percentage difference between simulation measured data for is 1.04%, 6.75%, 3.91%, 1.43% 1.24% 4.19% 2.08% respectively. For Based optimised on this, drag data percentage is accurate within difference 6.75%. is 0.49%, Based on 3.91%, 6.75%, 1.43% 4.19% respectively. For optimised percentage difference is 0.49%, 1.24% data 2.08% shown respectively. in s 18 Based on 19 this, it can be drag determined data is accurate that data within produced 6.75%. Based from Ansys on is data 3.91%, 1.24% 2.08% respectively. Based on this, drag data is accurate within 6.75%. Based on shown accurate in s to real 18 world conditions 19 can beby determined 1.87% for that data lift produced 6.75% from for Ansys is accurate drag. data shown in s it can be determined that data produced from Ansys to is real world accurate conditions to real by world 1.87% conditions for by 1.87% for lift 6.75% for lift 6.75% for drag. drag. 28. A graph sho drag for wind tunnel testing Ansys Simulation Ansys 28. Wind 28. A graph A graph Tunnel sho sho Results Discussion drag drag for for wind wind tunnel tunnel testing testing Ansys Ansys Simulation. Simulation Ansys The simulation Wind Tunnel results Results showed Discussion morphing s have a significant increase in aerodynamic 5.6. efficiency Ansys compared Wind Tunnel to Results Discussion. The most efficient design was optimized The simulation results showed morphing s have a significant increase in aerodynamic morphing, which because increased flow smoothness allowed for higher efficiency The simulation compared results to showed morphing. The s most have efficient a significant design increase was inoptimized aerodynamic distribution over a larger area lower surface. This resulted in higher lift production efficiency morphing compared, which to because increased. The flow most smoothness efficient allowed design for higher was optimized reduced drag. morphing distribution, over which a larger because area increased lower flow smoothness surface. This allowed resulted for in higherlift production distribution The initial optimized morphing also had effect reducing size delaying overreduced a larger area drag. lower surface. This resulted in higher lift production reduced formation vortices in wake, which reduced drag. This occurred The because drag. initial optimized morphing also had effect reducing size delaying vortices are no longer generated on flap drop at points where formation vortices in wake, which reduced drag. This occurred Theflaps initial would usually optimized dislocate morphing from also surface had is no effect longer reducing available; this size can be seen delaying formation because vortices are no longer generated on flap drop at points where 24. vortices in wake, which reduced drag. This occurred because flaps would usually dislocate from surface is no longer available; this can be seen in vortices The are no longer data provided generated in on s flap reinforced drop success at points morphing where flaps 24. would design. usually They dislocate showed no from significant surfacedrop is no along longer available; trailing edge this can morphing be seen ins 24. The data provided in s reinforced success morphing refore, The leading data to a provided reduction in s 25 drag as 26 well reinforced as a reduction success in vortex size. morphing design. They showed no significant drop along trailing edge morphing s design. refore, They leading showed to no a reduction significant in drop drag as along well as a trailing reduction edge in vortex size. morphing s refore, leading to a reduction in drag as well as a reduction in vortex size.

19 Aerospace 2017, 4, Noise One source aircraft noise is generated by turbulent flow over airframe. A considerable noise signature Aerospace is2017, generated 4, 52 when an aircraft flaps are deployed, this is due to violent disruption 19 airflow 24 creation turbulence. Therefore, if lift-induced drag vortices are reduced by morphing 6. Noise n noise is reduced. To test this, noise level readings were taken during wind tunnel tests to determine One anysource noise level aircraft reductions. noise is generated by turbulent flow over airframe. A considerable noise Eachsignature hasis agenerated noise level when reading an aircraft taken flaps at 0, 5, are 10, deployed, this degrees is due to angle violent attack. disruption Based on measured airflow data shown creation in Table turbulence. 2 Therefore, Equation (1) if lift-induced after performing drag vortices baseline are wind reduced tunnel by noise morphing n noise is reduced. To test this, noise level readings were taken during wind level correction, sound level produced by only was obtained. The actual noise tunnel tests to determine any noise level reductions. levels as a function AOA are shown in 29. Each has a noise level reading taken at 0, 5, 10, degrees angle attack. Based on measured data shown in Table 2 Equation (1) after performing P baseline wind tunnel noise Noise level(db) = 20 log 1 level correction, sound level produced by 10, (1) P only was obtained. The actual noise 0 levels as a function AOA are shown in 29. where: P 1 = Sound Pa (What microphone detects), P 0 = Reference Pressure (Threshold hearing Noise level db =20log Pa)., (1) where: P1 = Sound Pa (What microphone detects), P0 = Reference Pressure (Threshold Table 2. Noise levels produced by morphing at different angles hearing Pa). attack. Table 2. Noise levels produced by morphing at different angles attack. Angle Attack Conventional Wing Shape Shifting Angle (AOA) Attack Conventional NoiseWing Level Shape Wing Shifting Noise Wing Level (AOA) Noise Level Noise Level 0 68 db 63 db db 68 db db db db 69 db 6567 db db db 70 db db db db 71 db 6769 db db db 69 db Wind Tunnel Noise Wind Level Tunnel (All AOA) Noise Level (All AOA) 62 db 62 db 29 shows re is a significant drop in noise level for optimized, up to 40% 29 shows re is a significant drop in noise level for optimized, up to 40% dependent on angle attack. Although this data will not be 100% accurate because wind tunnel dependent on angle attack. Although this data will not be 100% accurate because wind tunnel never never maintains maintains at constant at constant speed speed so so noise noise level level varies. The Theactual noise noise reduction reduction value value will will be be between between 30% 30% 40% 40% less less than than value. 29. A graph sho difference in noise level between 29. A graph sho difference in noise level between optimised optimised morphing. morphing. The noise was measured f section using a sound level meter; it was placed inside wind The noise tunnel was 10 cm measured behind f s trailing section edge using a10 sound cm above. levelas meter; wind it wastunnel placedoes inside not windmaintain tunnel a 10set cmspeed, behind multiple s decibel trailing readings edge were taken 10 cm above. an average As wind data tunnel was used does for not maintain each angle a set speed, attack. multiple decibel readings were taken an average data was used for each angle The s attack show stard deviation error bar charts for data collected from noise. The wind tunnel does not maintain a set speed refore noise is not constant, five decibel readings were taken per angle attack shown to gain an average noise level.

20 Aerospace 2017, 4, Aerospace 2017, 4, Aerospace 2017, 4, Aerospace 2017, 4, The figures below show stard deviation for noise data collected during tests conducted at The wind The figures s tunnel, below including show stard interquartile deviation deviation range for (indicated noise data error by collected bar green charts during for brown). tests data The conducted collected green at from brown wind The figures boxes tunnel, below indicate including show difference stard interquartile deviation between range for 75th (indicated noise data 25th by collected percentile green during or brown). tests middle The conducted 50% green at noise. The wind tunnel does not maintain a set speed refore noise is not constant, five decibel data s brown wind stard boxes tunnel, indicate including deviation, difference interquartile maximum between range minimum 75th (indicated is 25th by also percentile green shown by or brown). middle The green upper 50% lower readings brown were taken per angle attack shown to gain average noise level. whiskers data s boxes stard indicate respectively. deviation, difference maximum between minimum 75th 25th is also percentile shown or by middle upper 50% lower data s whiskers stard respectively. deviation, maximum minimum is also shown by upper lower whiskers respectively. 30. A graph sho stard deviation noise level for A graph A graph sho sho stard stard deviation deviation noise noise level level for for A graph sho stard deviation noise level for. 31. A graph sho stard deviation noise level for shape shifting. 31. A graph sho stard deviation noise level for shape shifting AA graph graph sho stard deviation noise noise level level for for shape shape shifting shifting Conventional noise error bars. 32. Conventional noise error bars. 32. Conventional noise error bars. 32. Conventional noise error bars.

21 Aerospace 2017, 4, Aerospace 2017, 4, Shape shifting noise error bars. 7. Conclusions The figures below show stard deviation for noise data collected during tests conducted at The wind main tunnel, objective including this paper interquartile was to design range (indicated develop a morphing by green brown). technology Thebased green implementation brown boxes indicate transition difference regions between 75th 25thflap, percentile which was or simpler middle than 50% current data s sophisticated stard deviation, technology, ideally maximum reducing minimum timescale is also for operational shown by use. upper To achieve lower this, whiskers models respectively. were created tested through CFD simulation to determine aerodynamic performance. Also, wind tunnel tests were carried out to measure lift drag s 7. Conclusions to determine noise level reduction compared to. Simulation The main objective was carried this out paper on Ansys was Fluent to design for each develop models. a morphing Simulation technology revealed a 10.8% based on implementation lift increase transition for initial regions morphing between 15.4% for flap, optimized which was morphing simpler than as compared current sophisticated to technology, design. ideally At angles reducing attack timescale 0, 5, 10 for operational 15 degrees use. To optimized achieve this, has an models increase were in lift-to-drag created ratio tested 18.3%, through 10.5%, CFD10.6% simulation 4% torespectively determine when aerodynamic compared with performance.. Also, Simulations wind tunnelalso testsshowed were carried that re out tois measure a significant lift improvement drag s on to determine distribution noise over level reduction lower surface compared to morphing. aeroil. The increase in flow smoothness Simulation was reduction carriedin out vortex on Ansys size reduced Fluent for each drag models. along Simulation trailing edge revealed a 10.8% which caused lift an increase for in initialon morphing lower surface. 15.4% A morphing for optimized reduced morphing size as vortices compared torefore noise levels design. At angles morphing attack s based 0, 5, 10on data 15collected, degrees was optimized reduced by up has to 50%. an increase in lift-to-drag ratio 18.3%, 10.5%, 10.6% 4% respectively when compared with. Simulations also showed that re is a significant improvement on Acknowledgments: The research was self-funded. The authors would also like to thank ANSYS, Inc. for distribution over lower surface morphing aeroil. The increase in flow possibility to use ir stware. smoothness reduction in vortex size reduced drag along trailing edge Author which caused Contributions: an increase Dean inninian designed on lower experiments; surface. performed A morphing experiments; reduced analysed size data; vortices Dean Ninian refore Sam noise Dakka levels wrote paper. morphing The research s was based performed on data collected, in frame was work reduced Dean by Ninian s Engineering Degree under supervision direction Dr. Sam Dakka. up to 50%. Conflicts Interest: The authors declare no conflict interests. Acknowledgments: The research was self-funded. The authors would also like to thank ANSYS, Inc. for possibility to use ir stware. Abbreviations Author Contributions: Dean Ninian designed experiments; performed experiments; analysed data; The Dean follo Ninian abbreviations Sam Dakkaare wrote used in paper. this manuscript: The research was performed in frame work Dean Ninian s Engineering Degree under supervision direction Sam Dakka. P1 sound, Pa Conflicts Interest: The authors declare no conflict interests. P0 reference (threshold hearing Pa), Pa Cp Pressure Coefficient,- db Noise Level, decibels AOA Angle Attack NACA National Advisory Committee on Aeronautics DARPA The Defense Advanced Research Projects Agency UAV Unmanned Air Vehicle SMA Shape Memory Alloy PZT Piezoelectric Transducer

22 Aerospace 2017, 4, Abbreviations The follo abbreviations are used in this manuscript: P 1 P 0 C p db AOA NACA DARPA UAV SMA PZT CFD RNG sound, Pa reference (threshold hearing Pa), Pa Pressure Coefficient Noise Level, decibels Angle Attack National Advisory Committee on Aeronautics The Defense Advanced Research Projects Agency Unmanned Air Vehicle Shape Memory Alloy Piezoelectric Transducer Computational Fluid Dynamics CFD Re-Normalization Computational Group Fluid Dynamics RNG Re-Normalization Group Aerospace 2017, 4, Appendix A Appendix A A1. Conventional aeroil with flap, units in mm; Initial shape shifting design A1. with flap, Conventional units in mm. aeroil with flap, units in mm; Initial shape shifting design with flap, units in mm.

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