EXPERIMENTAL AND COMPUTATIONAL ANALYSIS OF A UAV …

EXPERIMENTAL AND COMPUTATIONAL ANALYSIS OF AUAV FOR SUPERFICIAL VOLCANO SURVEILLANCE

Pedro David Bravo-Mosquera∗, Laura Botero-Bolivar∗, Daniel Acevedo-Giraldo∗,Hernán Darío Cerón-Muñoz∗, Fernando Martini Catalano∗

∗ Department of Aeronautical Engineering, São Carlos Engineering School, University of SãoPaulo, Brazil

Keywords: UAV, Conceptual design, CFD, Wind tunnel, LSB.

Abstract

Nowadays, unmanned Aerial Vehicles (UAVs)technology has been improved considerably dueto their ideal characteristic to recognize areas ofdifficult access, performing missions that couldnot be made with traditional manned aircraft.This work presents the experimental and com-putational analysis of a UAV for superficial vol-cano monitoring. The aerial vehicle, calledURCUNINA-UAV aims to monitor the GalerasVolcano located in Colombia. The conceptualdesign of the aircraft is based on the design re-quirements established from a mission analysis.Computational Fluid Dynamics (CFD) simula-tions were done using Ansys-CFX. Experimentalanalysis was carried out in both open and closedwind tunnels in order to study all the possibleaerodynamic phenomena that could be presentedin the UAV mission. A Laminar Separation Bub-ble (LSB) was observed on the upper surfaceof the wing, which modify the aircraft perfor-mance considerably. However, the bubble for-mation was avoided using several transition pro-cesses. On the other hand, results showed that theentire design process was consistent because thenumerical and experimental results were greatlysimilar in the aerodynamic coefficients. This sug-gested that the URCUNINA-UAV is potentiallyable to perform the proposed mission.

1 General Introduction

In the last decades, the study about designand optimization of Unmanned Aerial Vehicles(UAVs) has increased due to wide variety ofapplications, such as observation and surveysof ozone layer, polar zones, hurricane genera-tion, tornado formation, power lines monitoring,among others [1]. However, in case of volcanicmonitoring, the information about UAVs to per-form this kind of mission is very limited. Usually,specialized research centers in volcanic eruptionshave developed different procedures for analyz-ing the behavior inside and outside the craters.One of these procedures involves performingcontinuous flights over the volcanic domes, withthe intervention of manned aircraft, i.e. the air-craft are equipped with instruments for in situanalysis the geographical, chemical and thermalchanges over the volcano surfaces. However, thehighly unfavourable flight conditions can affectthe aircraft performance, risking the lives of thecrew aboard [2-4]. Under these limitations, theremoval of the crew from the aircraft, combinedwith remote sensing technology of UAVs appearsas a viable solution to these issues.

In the present article is reported the de-sign methodology of a UAV named URCUNINA(meaning Fire Mountain), whose mission is toperform flights around volcanoes, as well as itsnumerical analysis and wind tunnel tests.

In-depth exploration of the operational fieldof the URCUNINA-UAV was performed, aiming

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BRAVO-MOSQUERA, P. D. BOTERO, L. ACEVEDO, D. CERÓN-MUÑOZ, H. D. CATALANO, F.

to identify the Design Requirements and Objec-tives (DRO) for the aerodynamic design of thisvehicle. The geographical features of the GalerasVolcano (4276 m a.s.l.), located in San Juan dePasto - Colombia (1o13

′31′′N,77o21

′68′′W ) were

selected [5, 6]. Hence, the URCUNINA-UAVmust be able to fly up to 4300 m a.s.l. i.e, itrequires a high service ceiling. At this great al-titude, the wing lift is reduced due to the rarefac-tion of the air. Therefore, the choice of the wingairfoil was emphasized to obtain a sufficientlyhigh lift coefficient (CL). A powerful propul-sion system is also required because of the massflow rate decrease at the operating altitude. Thus,the selected engine/propeller must reach this per-formance requirement, keeping sufficient Thrustto Weight Ratio (T/W) during each phase of themission profile. Fig. 1 shows the Galeras Vol-cano map risk, which has a radius of high threatzone (red zone) of 11 Km, a radius of mediumthreat zone (orange zone) of 40 km and a lowzone threat zone of 100 km (yellow zone) [6].

Fig. 1 Galeras Volcano risk map.

The URCUNINA-UAV is constituted by thelaunch and recovery systems, i.e. a catapult fortake-off and a parachute as a vertical landing de-vice. Likewise, the communications equipmentof flight control and the equipment to distributethe data obtained by the payload are included.The aboard systems includes: Auto-pilot, sev-eral gas sensors, including a miniature mass spec-trometer, GPS sensors, photo-video cameras withinfrared system and a data link, as communica-tion system to control the information obtained

from the payload [7].Due to the fact that real environmental con-

ditions of volcanoes are difficult to be repre-sented in wind tunnel experiments, the numeri-cal and experimental studies focused on assess-ing the Reynolds number similarity. In this way,a scale model of the URCUNINA-UAV was de-signed and manufactured. Specific characteris-tics were observed, analogous to the aerodynamicbehavior of the actual aerial vehicle, such as soft-stall at high angles of attack and high lift coeffi-cient.

As an additional support to this research,Bravo-Mosquera et al [8] presented more specificdetails of the URCUNINA-UAV design in thissort of specific mission.

2 Design procedure

The conceptual design of the URCUNINA-UAVwas conceived from potential opportunities in thefuture market. Having derived the mission re-quirements from these predicted opportunities,the search for the technology with respect to theimposed flight conditions initiated. This customdesign methodology was founded upon method-ological proposals developed by Roskam [9],Raymer [10], Nicolai [11] and Austin [12].

The URCUNINA-UAV design procedure wasdivided into three main stages (Fig. 2). Thefirst refers to the definition of design parame-ters, which include operational requirements re-lated to performance characteristics, and pay-load weight (W p). An extensive research wasconducted about photographic and environmen-tal UAVs, forming a database with 20 UAVs toanalyze their main design features. To this end,a multidisciplinary design optimization (MDO)tool was developed, which integrates the con-cepts of statistical entropy and quality functiondeployment (QFD). This tool is used to iden-tify the new design concepts that have been in-troduced in the market by each vehicle. Fur-thermore, even within the first stage, an initialweight estimation of the UAV was performed,ending with the constraints analysis to choosethe propulsion system. The second stage refers

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EXPERIMENTAL AND COMPUTATIONAL ANALYSIS OF A UAV FOR SUPERFICIAL VOLCANOSURVEILLANCE

Fig. 2 Design methodology flow chart [8].

to the preliminary estimations regarding the ba-sic aerodynamic, geometry, weight, stability andperformance parameters. Once the aerodynamicdesign is established, the final stage consists ofCFD simulations, and wind tunnel experimentsusing a scale model of the URCUNINA-UAV, inorder to determine the aerodynamic coefficientsto predict the vehicle behavior prior to manufac-turing. Figure 2 shows the logical process carriedout during the conceptual design phase.

2.1 Design requirements and objectives

The design process started defining the require-ments and objectives (DRO) of the URCUNINA-UAV based on the mission profile established.The following operational requirements were de-fined: take off altitude, service ceiling, opera-tional altitude, endurance and payload. Theseflight requirements are generals and describe theneeds of the aircraft. Each parameter showed intable 1 is based on parametric studies and themission of the URCUNINA-UAV.

The proposed mission profile to carry outsuperficial research of volcanic environments ispresented in Fig. 3.

Table 1 DRO of the URCUNINA-UAV [8].Requirement PerformanceTake-off altitude 2527 mOperational altitude 4500 mEndurance 4 hPayload 4 kgMTOW 15.64 kgMonitoring velocity ≈ 20 m/sCruise velocity ≈ 28 m/s

Fig. 3 Mission profile of the URCUNINA-UAV [8].

2.2 Final concept

After design iterations, the final concept is aninherently stable UAV with a total endurancegreater than 5 hours, MTOW = 15.5 Kg, serviceceiling = 5000 meters, stall speed = 12 m/s, oper-ational speed = 21 m/s, EPPLER 423 wing air-foil and NACA 0012 tail airfoil. The 3 viewsand isometric view of the final prototype of theURCUNINA-UAV are shown in Fig. 4.

Fig. 4 URCUNINA-UAV [8].

Further detailed information about the con-ceptual design, performance and stability analy-sis of the URCUNINA-UAV are reported in [8].

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3 CFD simulations

The CFD analysis was carried-out with the com-mercial code Ansys-CFX [13]. The analy-sis was based on resolving Reynolds-Averaged-Navier-Stokes (RANS) equations, coupled withthe Shear Stress Transport (k− ω SST) turbu-lence model. The Shear Stress Transport turbu-lence model was used since it models typical lowReynolds aerodynamic problems [14].

This section aims to compare numerical re-sults with the experimental results from wind tun-nel tests. The simulations were performed at thealtitude of the wind tunnels location, using a halfscaled model (1:2.4) of the URCUNINA-UAV.Then, the main dimensions of the scale modelare: MAC = 0.11 m, b/2 = 0.6 m and total length= 1.2 m as can be seen in fig. 5.

Fig. 5 Main dimensions of scale model.

3.1 Numerical approach

The dimensions of the computational domain andthe boundary conditions were adjusted to thecharacteristics and location of the closed windtunnel used for the experiments [15].

A grid independence study was carried out,to ensure that the grid refinement does not affectthe solution. This study gave the size of the ele-ments of the grid with the lowest computationalcost. As can be seen in Fig. 6, for zero angle ofattack, from 8×106 elements, the CL coefficientno longer changed their values considerably. Inthis way, the distance for the first layer of cellsaway from the wall was set in y = 1e−4, result-ing in a Y+ ≈ 1.

Number of Elements×10

6

4 5 6 7 8 9 10

CL

0.85

0.855

0.86

0.865

0.87

0.875

Fig. 6 Mesh independence [8].

Unstructured meshes with tetrahedral ele-ments were created for the whole domain, how-ever, structured meshes were created near thewall with the aim of capturing the boundary layereffects. Figure 7 shows the final grid configura-tion and some refinement parts on the UAV sur-face.

Fig. 7 Grid details of the simulations.

3.2 Boundary conditions

Pressure and temperature were calculated withthe ISA (International Standard Atmosphere) atan altitude of 856 MSL, which is the altitude ofthe Aircraft Laboratory of the São Carlos Engi-neering School, University of São Paulo, Brazil.Velocity inlet was set at 29 m/s, which repre-sents the project Reynolds number approximatelyequal to 2.15× 105 based on the MAC. Inletturbulence intensity equal to 1% and turbulenceeddy viscosity equal to 0.2 were also selected.Outlet velocity was set without pressure gradi-ent difference at outlet region. Symmetry con-dition was imposed in the half of the longitudi-nal plane of the model. The walls of the virtual

4


wind tunnel were treated as Free-slip wall (Idealwall), because wall corrections were consideredfor the experimental results. The UAV model wastreated as a No-slip wall. A wide range of angleof attack was examined, from α= -6o to α= 20o,revolving the model around the pitch axis.

3.3 Pressure contours

Figure 8 show the streamlines and pressure con-tours on the URCUNINA-UAV at α = 0o, 8o,14o (pre-Stall angle) and 20o (stall angle), respec-tively. As can be seen in fig. 8a and fig. 8b, thefluid does not present detachment. On the otherhand, in fig. 8c and fig. 8d are observed fluid sep-aration on the wing/fuselage junction and wing-tail boom junction, this occurs by the stall effectpresented at this angles of attack.

4 Wind tunnel experiments

The experiments were carried out in two stages.First, the acquisition of the aerodynamic forceswas conducted in a closed-circuit wind tunnelthat has a test section of 1.30 x 1.70 x 3.00 m[15]. The maximum velocity achieved is about40 m/s and the turbulence level is 0.21%. On theother hand, flow visualization experiments wereundertaken in a blower wind tunnel with an openworking section of 0.8 x 1.05 m. The operatingvelocity range is from 10 to 30 m/s. Both tun-nels are located at the laboratory of aerodynamics(LAE) of the São Carlos School of Engineering -University of São Paulo (EESC-USP), Brazil.

The Cliever CL2 pro plus 3D printer wasused to manufacture the scale model (1:2.4) ofthe URCUNINA-UAV (Fig. 5), which use Poly-lactic Acid (PLA) as building material. Eightpieces were printed to complete the model usingan internal structure of honeycomb type. The sizeof honeycomb in the wing is much denser thanthe fuselage, in order to the wing be stiffer. Fig-ure 9 shows the manufacturing process and thepieces of the model.

Fig. 8a. α = 0o.

Fig. 8b. α = 8o.

Fig. 8c. α = 14o.

Fig. 8d. α = 20o.

Fig. 8 Pressure contours and streamlines on theURCUNINA-UAV.

Fig. 9 3D printed Model [8].

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4.1 Balance experiments

The aerodynamic balance measures two keyforces on the model: lift and drag. The uncer-tainty of the forces measured with the aerody-namic balance was ± 0.01 N. It is connectedin a conditioner amplifier installed in a micro-computer. Data reading is through a compu-tational tool developed in the application "LabView" (National Instrument), which was set totake 5000 samples with a frequency sample of500 samples per second. Dynamic pressure wasmeasured with a micro manometer which has anuncertainty of ± 0.1 Pa. The uncertainty of mea-sure of the chord and the wing span was of ±0.001 m in each of them.

The total frontal projected area of the exper-imental model was 0.035 m2, which correspondsto 1.54% of the total area of the wind tunnel crosssection. Therefore, as this ratio is less than 8%,blockage phenomena can be neglected. Figure 10shows the final scale model of the URCUNINA-UAV at the wind tunnel test section.

Fig. 10 Wind tunnel test.

4.2 Flow visualization

The flow visualization technique used is knownas surface oil-flow (Fig. 11), which enables theobservation of the boundary layer flow in windtunnel easily and quickly. In this technique themodel surface is coated with a mixture of a veg-etable oil and fine pigment, indicating the patternof the flow on the surface. The technique allowsthe observation of the lines of separation and reat-

tachment of the flow.

Fig. 11 UAV in the blower wind tunnel.

5 Results

In this section, the experimental and numericalresults of the UAV are presented. First of all,the experimental results of the LSB phenomenaare discussed. Once obtained the correspondingboundary layer transition, results are compared tonumerical ones.

Figures 12 and 13 show the CL vs α and CD vsα curves obtained experimentally. There is a se-vere decrease of lift and increase of drag betweenα= 3o to α= 11o. This is due to the presence of alaminar bubble on the upper surface. On the otherhand, above α = 11o, the kinetic energy of thefluid increases and promotes the transition fromlaminar to turbulence flow prior to the separa-tion of the boundary layer and the aircraft behav-ior become back to the normal behavior. Indeed,through the visualization experiments, the pres-ence of a bubble in this range of angles of attackwas verified, e.g. at α = 0o, a bubble is formedapproximately at 25% of MAC with a length of3 cm approximately, (25% of MAC), as can beobserved in Fig. 11.

To avoid the formation of the bubble, two al-ternatives were considered. First, the free-streamvelocity was increased, raising the Reynoldsnumber. On the other hand, a roughness at 25%of MAC was set. Both of them avoided the LSBand there was no such abrupt decrease in CL val-ues in the range 3o ≤ α ≤ 11o, (see fig. 14 andfig. 15). This occurs on account of in both casesthe transition is before the separation point. Inthe first case, due to the increase of the flow ki-

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−10 −5 0 5 10 15 200

0.5

1

1.5

2

α [Deg]

CL

Experiment U=23m/s Free transition

Fig. 12 Lift coefficient with LSB.

−5 0 5 10 15 200

0.1

0.2

0.3

0.4

α [Deg]

CD

Experiment U=23m/s Free transition

Fig. 13 Drag coefficient with LSB.

netic energy, and on the second case, due to theforced transition before the separation.

To define the roughness, the bubble featureobserved in flow visualization at 11o was con-sidered. It was defined the separation point andthe roughness was located before to guaranteethe transition. Figure 16 shows XFOIL simula-tion at Re = 1.5 x 105, Ncrit = 9 and AoA = 0o

with free transition and forced transition at 25%of MAC, which represents the trip on the realmodel. With forced transition model, the pres-sure distributions does not present bubble phe-

−10 −5 0 5 10 15 200

0.5

1

1.5

2

α [Deg]

CL

Experiment U=29 m/sExperiment U=23 m/s Forced transitionExperiment U=23 m/s Free transition

Fig. 14 Lift coefficient with transition methods.

−5 0 5 10 15 200

0.1

0.2

0.3

0.4

α [Deg]

CD

Experiment U=29 m/sExperiment U=23 m/s Forced transitionExperiment U=23 m/s Free transition

Fig. 15 Drag coefficient with transition methods.

0 0.2 0.4 0.6 0.8 1

−1.5

−1

−0.5

0

0.5

1

x/cC

p

Free transitionForced transition

Fig. 16 Pressure distribution with free and forcedtransition.

nomena, however reduce the suction peak.According to the results of Fig. (17), from

α = 0o to α = 12o, on the linear behavior of thecurves, note that the slope (∂CL/∂α) of the twocurves are similar, in spite of obtaining variationsfor CL values at zero angle of attack. The nu-merical and experimental curves presented sim-ilar behavior for all angles of attack evaluated.However, the curves presented similar pre-stallangles, α = 13o for experimental and α = 14o forthe numerical curve. This represents a favorablebehavior in the proposed mission, because it al-lows recovering the UAV at high angles of attack,before reaching the strong stall. This typical be-havior is caused by the wing airfoil at high turbu-lent flow, which contributes to maintain a stableperformance in the long run.

Figure 18 shows the results of the drag coef-ficient. As it was expected, an excellent approx-imation of the numerical results with the exper-imental ones was obtained, where the CD valuesat zero angle of attack were 0.048 and 0.053 re-spectively.

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α [Deg]

-5 0 5 10 15 20

CL

0

0.5

1

1.5

2

Numerical

Experimental

Fig. 17 Lift coefficient.

α [Deg]

-5 0 5 10 15 20

CD

0

0.1

0.2

0.3

0.4Numerical

Experimental

Fig. 18 Drag coefficient.

For negative angles, the numerical and exper-imental curves presented an abrupt decrease ofCL, which produced an increase in the CD. Thisis caused by the great curvature of the wing air-foil. However, even in negative angles, the UAVgenerates sufficient CL to maintain its flight.

Figure 19 shows the aerodynamic efficiencycurves versus angle of attack. It was observedthat for the numerical curve the maximum valueof the lift-to-drag ratio were set at α = 0o, and forthe experimental curve at α = 5o. Both curvespresented the same value of aerodynamic effi-ciency, being L/D = 17.7. On the other hand,figure 20 relates the URCUNINA-UAV drag po-lar for the entire design process of the aircraft. Itwas observed that the numerical and experimen-tal values were close. For the sake of argument, itcan be concluded that all the aerodynamic anal-ysis for evaluating the conceptual design of the

α [Deg]

-10 -5 0 5 10 15 20

L/D

0

5

10

15

20

Numerical

Experimental

Fig. 19 Lift to Drag ratio.

CL

0 0.5 1 1.5 2 2.5

CD

0

0.1

0.2

0.3

0.4Numerical

Experimental

Fig. 20 Drag polar.

URCUNINA-UAV were performed successfully,because specific characteristics were adjusted tothe mission requirements, such as high aerody-namic efficiency and soft stall.

Finally, in Table 2, the main results of the to-tal aerodynamic design process are summarized.As a conclusion, the numerical and experimen-tal results were well developed, since the resultsmatch closely.

Table 2 Comparison of aerodynamic coefficients.

Aerodynamic parameters Numerical ExperimentalMaximum CL 2.09 1.92α for CLmax 15o 14o

CL at zero α 0.87 0.85CD at zero α 0.048 0.053∂CL/∂α 0.083 0.081Maximum L/D 17.7 17.7α for (L/D)max 0o 5o

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6 Concluding remarks

The conceptual design and its respective aerody-namic analysis of a new concept of low-cost UAVintended to be used in one of the many methodsfor monitoring an active volcano have been de-veloped.

The results obtained with computational, andexperimental methods enriched the research exer-cise during the design of the URCUNINA-UAV.In this way, it was possible to analyze and vali-date the main findings, which are summarized inthe following statements:

• The SST turbulence model was efficientin predicting the aerodynamic behavior ofURCUNINA-UAV with sufficient preci-sion, obtaining CL and CD values very closeto those found in wind tunnel testing.

• Wind tunnel tests corroborated data show-ing that the URCUNINA-UAV is a promis-ing design and would achieve the missionsuccessfully. The CL requirements for themission were accomplished and the dragvalues obtained were close to expected. Asa result, a stable and high lift, low dragUAV was obtained.

• High-lift low Reynolds number airfoilspresent grater advantages in both civil andmilitary applications, however they are li-able to present bubble phenomena due totheir laminar boundary layer, then it is im-portant to analyze completely the behav-ior of the wing or airfoil in order to knowin which conditions of angle of attack, ve-locity and turbulence intensity the aircraftcould operate. In conditions in which thebubble is formed, the aircraft could not beoperated.

• To improve the analysis of the actual-environmental conditions above a volcano,free disturbance and unsteady flow effectsmust be evaluated. However, the numer-ical and experimental results presented inthis research are promising to complete theURCUNINA-UAV mission.

• As for the resulting UAV, all the analy-sis was limited to the conceptual and aero-dynamic design phase, this UAV conceptcan serve as a base for future detailed de-sign studies, such as structural analysis,sizing of control surfaces, dynamic stabil-ity, among others.

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superficial research of volcanic environments.Aerosp. Sci. Technol. Vol. 70 (Supplement C)pp. 600-614. 2017.

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7 Contact Author Email Address

mailto: [email protected]

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The authors confirm that they, and/or their companyor organization, hold copyright on all of the origi-nal material included in this paper. The authors alsoconfirm that they have obtained permission, from thecopyright holder of any third party material includedin this paper, to publish it as part of their paper. Theauthors confirm that they give permission, or have ob-tained permission from the copyright holder of thispaper, for the publication and distribution of this pa-per as part of the ICAS proceedings or as individualoff-prints from the proceedings.

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