uav dissertation

University Of Salford

School of Computing Science and Engineering

Balloon Bot UAV

Final Year Undergraduate Project

Final Report

6th of May 2014

Name: Elliot Newman @00320195

Course Title: BEng Aeronautical Engineering

Course Code: AE/F1

Supervisor: Dr Theo Theodoridis

Elliot Newman @00320195

University Of Salford

School of Computing Science and Engineering

Name of Student: Elliot Newman

Course Code: AE/F1

Title of Project: Balloon Bot UAV

I certify that this report is my own work. I have properly acknowledged all material that has been used from other sources, references etc.

Signature of Student: Date:

Official Stamp:

Submission Date (to be entered by relevant School Office staff):


Abstract

As more automated and artificially intelligent systems become operational, further

research and development is likely to be undertaken. In this project the design,

manufacture and testing of an omni directional balloon UAV is discussed,

focusing on the aerodynamic aspects of the venture. By initially deliberating the

theory to be applied to the product, an understanding of the forces and effects at

hand was attained. Practical tests and computational fluid dynamics have been

conducted to witness the theory in a visual light and generate results that can be

applied during the design process. These results will allow for conclusive

decisions to be made on the UAV’s aspect orientation in the pursuit of peak

performance, with the final product evaluated. As the UAV’s operational ability

became temperamental, certain advancements were unable to occur and have been

illustrated as potential future work.


Acknowledgements

First and foremost I would like to thank the other members of the group whose

dedication and attention to detail, coupled with hard work made the project

possible. Also there willingness to step beyond there project criteria to enable

constant progress to take place.

Also my supervisor, Dr. Theodoridis and the robotics technicians, most notably

Andy, whose patience and expertise was paramount to the advancements attained

during the project.

Finally, I would like to acknowledge my friends, family and girlfriend whose

constant support and advice helped maintain my focus and work ethic over the

course of the year.


Content


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s

1. Introduction............................................................................................................1

2. Literature Review...................................................................................................3

3. Model Description..................................................................................................9

3.1 Buoyancy.........................................................................................................10

3.1 Drag.................................................................................................................12

3.2 Propulsion........................................................................................................15

4 Theoretical/Experimental Calculations.................................................................17

4.1 Buoyancy Experiment......................................................................................17

4.2 CFD Simulations..............................................................................................20

4.2.1 Balloon Simulation...................................................................................21

4.2.2 Nacelle Simulation...................................................................................22

5. Data Analysis.......................................................................................................26

5.1 Buoyancy Experiment......................................................................................26

5.2 CFD Simulations..............................................................................................27

5.2.1 Balloon Simulation...................................................................................27

5.2.2 Nacelle Simulation...................................................................................28

6. Further Experiments.............................................................................................30

6.1 Drag Force Prediction......................................................................................30

7. Further Analysis...................................................................................................32

7.1 Drag Force Prediction......................................................................................32

8. Conclusions..........................................................................................................33

8.1 Discussion........................................................................................................33

8.1.1 Buoyancy Experiment..............................................................................33

8.1.2 CFD Simulations......................................................................................34

8.1.2.1 Balloon Simulation...............................................................................34

8.1.2.2 Nacelle Simulation...............................................................................35

8.1.3 Drag Force Prediction...............................................................................36

8.2 Outcomes.........................................................................................................37


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8.2.1 Rotational analysis...................................................................................38

8.3 Future Work.....................................................................................................39

8.3.1 Balloon Development...............................................................................39

8.3.2 Structural Advancements..........................................................................41

8.4 Conclusion.......................................................................................................42

9. References............................................................................................................44

10. Appendices...........................................................................................................46

10.1 Tables...............................................................................................................46

10.2 Figures..............................................................................................................51


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1. Introduction

As the world’s needs and desires advancement, so does the search for technology

to meet them. In the aerospace industry that need manifests itself as a vision for

greater accuracy, flexibility and most paramount, greater safety. With the

advancements in artificial intelligence the simplest way to achieve this directive is

to remove the human occupant from the situation completely, flying the aircraft

remotely from a ground based location. This dissertation is in line with these

views and as a result, during the course of this project, the aim is to produce an

Omni directional UAV (Unmanned Air Vehicle) capable of sustained indoor

flight. A venture such as this will require meticulous planning and design with

many areas from inception and manufacture coming together to produce a

successful outcome. To this end, by completing this project, an aptitude in

research, design and construction will have been displayed, as well as working

cohesively within a group.

In engineering circles, the design process is a practiced one and therefore has a

structured format and one which will aid the development of the Balloon UAV.

Initially beginning with the concept, in this case, the vision to produce a lighter

than air UAV capable of sustained indoor flight. Next on the agenda is the

research, which comes in the form of a literature review, investigating projects

with transferable lessons and functionalities to narrow the subject region. Then

using this research during the design, test and refine stage, taking the lessons to

formulate estimated designs and iterating them based on data analysis from

experimental procedures. Through these steps the final model can be portrayed

with the knowledge that each component has been subjected to stringent

examination to produce a successful prototype.


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As a paper of this magnitude requires significant personal work, specific areas of

the process will be allocated to an individual within the topic area, such as;

Aerodynamic, Mathematical modelling etc. This format will allow for the

demonstration of the specific skill sets needed to successfully navigate an

assignment such as this. This paper shall investigate the aerodynamic nature of the

UAV, testing and analysing the balloons interaction with the fluid around it, as

well as aiming to maximise the propulsion of the system.

The report is self-contained and shall begin with a view of the project as a whole,

moving forward, a review of the relevant literature obtained during preliminary

research will highlight the key topics and procedures that will be encountered and

have to be overcome. The literature will then be put to use to help make informed

decisions about the UAV’s directional progress, as well as enabling an efficient

design. Completing this, theory behind the review shall be investigated and

experimentally tested, through physical and computational means, thus generating

a greater noesis, leading to more apt design choices.

Finally, due to the congested nature of the product timeline, any future work to

further improve the UAV shall be postulated, including any improvements in

design selection process that have been made in hindsight that could be employed

in the future.


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2. Literature Review

In order for any object to attain flight many aspects must first be considered, modelled

and authenticated such as; power to weight, aerodynamics, its physical structure and

potential future applications. To achieve a successful operation, first the relevant

information must be sourced, collated and understood by investigating projects and

areas with similar fundamental characteristics and behaviours. As indoor balloon

robots are quite rare, adjacent fields will be examined, with the applicable material

extracted to shed light on the aerodynamic challenges that will be faced. In this

literature review research will be correlated to potential problems that may be faced

and then summarised in order to give a broader noesis of the topic at hand.

As with any body functioning in a fluid, its own aerodynamic profile will become its

most paramount feature as it directly impacts on potential performance, structural,

stability and the general feasibility of the rig. A sound profile will allow for more

flexibility in these areas as they will have room to manoeuvre and their structural

locations will not be dictated purely on stability.

Hydrostatics dictates that, any object immersed in a fluid will still experience a force

even if there is no relative movement (Anderson 1991: 27). This principle is known as

‘buoyancy’. The hydrostatic equation illustrates that the pressure on a body changes

with relation to height and only acts vertically:

dp=−gρ dy


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In theory, these vertical pressure forces all act through the objects centre of gravity and

due to the horizontal pressures being at the same height, these cancel out and therefore

apply no perceivable moments. Yet when applied practically to the early designs this

will not be the case and consequently will have to be factored into the modelling

process. Buoyancy is a key principle for balloon and other lighter than air systems and

is felt as an upward force proportional to the amount of fluid the body displaces.

Buoyancy forceof a fluid=Weight of fluid displaced by body

None mechanically powered balloons exploit this idea by displacing huge amounts of

air in order to achieve a large enough force to maintain flight and therefore this

relationship can be applied to the ‘balloon bot’ during periods of minimal movement [1].

During motion, having a large buoyancy will create a trade-off against drag which will

compromise the stability and motion of the UAV. Due to the easy nature of conducting

buoyancy tests, the procedure can be repeated and differing sizes tested in order to

achieve the perfect compromise. During the moments of powered flight, the other forces

in effect, for instance lift and drag, will need to be calculated and modelled in order to

reveal the magnitude of their influence.

Due to the circular nature of the balloon shape, the fluid flow over the surface will also

need to be investigated. The fluid in contact with the surface, also known as the

boundary layer, suffers a decelerating effect due to the amount of skin friction

encountered and the viscosity of the fluid. Under certain pressures the airflow can be

brought to rest, which in turn leads to separation. This greatly reduces the aerodynamic

effect of the body as the fluid flow, still influenced by the adverse pressure, begins to

fold backwards creating reverse flow and turbulent air [2]. The readiness of the flow to

undertake this action is associated to the Reynolds number of the body, which links of


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the ratio of inertial forces to viscous forces. This value affects the flow at the boundary

layer, in particular its thickness and point of separation. As the ‘balloon bot’ will have a

high Reynolds Number, a more turbulent boundary layer will be present, delaying the

point of separation. The Reynolds Number is also a dimensionless quantity, which will

prove an advantage when coming to make scale models for aerodynamic testing [3].

Mathematically modelling the aerodynamic effects of size, shape, velocity and mass

will also prove potentially vital, as it is paramount to effectively quantify each

individual element before models are built and tested. There are various ways of

efficiently doing this, one of which is the Euler-Lagrange equations, which are used to

help with optimization and finding when a particular problem is at its maximum. It

employs the proven theory that at any point that the function is at a maximum or

minimum then its derivative is therefore zero. Then whether the point is a maxima or

minima is determined by using the second derivative. These are linked into Newtonian

laws and can therefore also be used to help predict motion [4]. Another effective way of

doing this is by using Navier-Stokes equations. By adopting these it is easier to

eliminate unnecessary values and focus on the unknowns with the greatest effect. These

can also then be used to allude to the turbulent nature of the flow beyond the point of

contact in the balloons wake [5].

Due to the rarity of indoor flying balloon robots, it may also be of some use to explore

other forms of aerial vehicles which enjoy similar characteristics to the proposed design.

An example is the Bosch SASS lite, a non-rigid helium filled balloon with a similar

engine mounting position to that predicted of the ‘balloon bot’. The non-rigid nature of

the design brings into question the stability of the craft whilst in motion, which was

overcome in this case by highly pressurising the balloon’s skin and keeping speeds of

travel low on the Bosch. With stability whilst moving a huge factor for any balloon


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based aircraft due to the effect of rolling, a centrally mounted engine also combatted

any potential issues that could have arisen during flight, by focusing the largest

percentage of its mass through its centre of gravity [6]. Also with the indoor nature of the

balloon bot, gusting and varying wind direction can be neglected during the tests,

leading overall to a much more stable set of test parameters. There are also theoretical

procedures to help calculate the stability of an object in fluid flow.

Due to the lighter than air nature of the balloon bot, investigating micro UAV’s will

also yield some benefit, as they too will also employ a high thrust to weight ratio and

also have a tendency to operate indoors or confined environments. Interestingly many of

the advancements in this area have come from studying insects of similar

characteristics, which include; higher Reynolds Numbers, high thrust to weight, low

overall weight, relatively low velocity range and being able to stably fly in its own

turbulent air flow [7].

The low velocity and powered nature of the UAV have led to the conclusion that

adopting a nacelle with a convergent nozzle would aid in boosting the net thrust of the

system, allowing greater manoeuvrability and velocity range. A convergent nozzle, also

known as a ‘propelling nozzle’ constricts the flow and thus maximises the exit velocity.

By taking advantage of the incompressible nature of the flow, mass flow rate is

uniform, relinquishing the equation:

V 1 A1=V 2 A2

Therefore by reducing the outlet area, the output velocity will rise proportionally with

its decline [8].

During the development of any new concepts how the design phases are undertaken

shall essentially decide the success or failure of the project. The process of; concept,


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research, design, test, refine design and then finalise is a model that has been widely

acknowledged as the accepted practice of any design tasks. Employing this procedure

effectively to the balloon UAV will enable a smoother design curve towards the final

product [9].

In design orientated projects operating in scarcely ventured territory, simulated testing

known as ‘computational fluid dynamics,’ abbreviated to CFD in engineering circles,

has become a paramount feature, vastly reducing costs and increasing the accuracy of

the initial models created. Using programs such as SolidWorks, with its addition of

FlowXpress, parameters such as; flow speeds, pressure stagnation, wake distribution

and aerodynamic inefficiencies can be monitored and addressed before production even

begins, inherently increasing the likelihood of success of the opening model [10].

Also a key aspect of any design task is how the data is interpreted and employed

moving forwards to create more improved iterations of the model. Through a

comprehensive and thorough examination of test data, anomalies and inefficiencies can

be designed out and any fundamental errors rectified. Furthermore, through scouring the

results, the test its self can be altered to ensure that the correct parameters are being

illuminated successfully and are being effectively measured. There are many forms of

presenting results so that the lessons of the data are more glaring which can be;

graphically, so that trend lines can be plotted highlighting the data drift, Tabular, the

results are inherently more organised reducing the risk of oversights and visual

programs, such as flow diagrams illustrating the physical behaviour of the data [11].

Continuing with data analysis, ensuring the accuracy of both practical and theoretical

values is of paramount importance during any research venture. The accuracy’s

significance is amplified by the fact that there isn’t much information to directly


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compare with our own discoveries. To this end, performing error analysis between

theoretical and practical parameters will highlight if any mistakes or miscalculations

have been made. Zuljian and Grum (n.d) demonstrate this practice and its practical

applications [12]. Furthering its importance is that during testing, scale models shall be

used and by proving the mathematics is applicable to the scale model will allow

extrapolation to the full scale final design.


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3. Model Description

A balloon UAV is comprised of many differing materials and intellectual practices

which, when cohesively brought together, realise the aim of a successfully flying

balloon robot. These aspects will now be investigated and discussed to achieve a greater

understanding and appreciation of the task undertaken.

Beginning with an overall vision of the UAV itself, there will be a large balloon, helium

filled and around 8ft in diameter providing the lift, seated into a stabilising structure

with the electrical aspects housed and connected below. This will consist of all the

electronics, from the motherboard to the control devises. Attached to the outside of the

housing will be the propulsion system, in the form of two propellers with channelling

convergent exhausts driven by motors, providing both the horizontal and vertical

motion, orientated by a servo that rotates the rig. A simplistic design is depicted below:

Figure 1: Initial Balloon Design


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3.1Buoyancy

As would be expected of a ‘balloon bot’, the most important aerodynamic devise is the

balloon itself, all the lift and the majority of the drag will be produced by the balloon as

its passes through the air. Bodies submerged in fluids are fundamentally at the mercy of

their own design, most paramount of which is that of its aerodynamic profile. The way

that the object interacts with the surrounding air will drastically affect its potential

performance once functional. As a balloon is the only source of aerodynamic lift, then

exploiting the buoyancy force has become integral to the success of the project. As

Anderson (1991: 27) demonstrated, ‘any object immersed in a fluid will still experience

a force even if there is no relative movement.’ This is known as the Hydrostatic

Equation:

dp=−gρ dy

and is in relation to the pressure force changing as the height of the body is changed.

The negative sign illuminates that any useful, effective lift will happen in the same

plane as gravity, but in the opposite direction and therefore up. A major benefit of this

law is that it perfectly illustrates that there will also be no moment forces acting on the

body, as all forces act through the objects centre of gravity and all horizontal forces

cancel each other out by notion of them being equal. This will enable a more naturally

statically stable structure uninfluenced by rotational inertial forces. Underwater this

effect is amplified and can be felt with a simple experiment of trying to push a ball or

balloon under the surface. A resistive force acts vertically and attempts to return the

object to its equilibrium point above the surface. If the force pushing down does not

maintain the balance, then this eventuality comes to the fore. In this situation, the


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density of the water is far greater than that of the air inside the object and therefore this

creates an upward force known as ‘Buoyancy’.

Buoyancy forceof a fluid=Weight of fluid displaced by body

In the air, the principle is still the same, with gravity taking on the role of the

submergence force. All that needs to change is that the air inside the balloon needs to be

lighter than that of the air around it in order to create a perceivable buoyancy force. In

order to do this, then the conventional air inside the balloon must be substituted with a

more concentrated mix lighter elements. With the known volatility of Hydrogen, the

most common and practical solution is to create a body filled primarily with Helium, as

much as 90%, thus spawning a ‘lighter than air’ craft. As the variance between the two

densities is far less than the water based example, then to fully capitalise on this

theorem, the balloons have to displace vast volumes of air to generate the required

buoyancy force to carry useful payloads and ratify their functionality. This phenomenon

is reduced slightly in the case of the ‘balloon bot’ due to its indoor nature; the projected

altitude limits are very low, maintaining the density of the air at its maximum, thus

creating the largest possible void between the density of the air and that of inside the

balloon. These basic principles will have to be taken into account when the selection of

prospective equipment process begins.

A practical experiment was deduced to physically witness and more notably, measure

the force produced. The balloon would be inflated up to its operational size, then a

harness attached by string, which would carry the load to be added. Moving forward,

masses would be added in small intervals until the buoyancy force became equal to that

of the weight and equilibrium reached. Then using a scale the total rig would be added


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and the simple process of measuring the total physical mass, minus the reading on the

scale would provide a practical value for the buoyancy force.

This experiment would be carried out multiple times and on differing dates in order to

reduce the error as much as possible. In this test the error manifests itself in many

forms, such as human error when applying the weights, although this is very minimal,

they would need to be applied gently to negate and momentum forces when added.

Also, the pressure in the room can vary depending on the weather; therefore conducting

the test under varying conditions would provide an unbiased vision of which conditions

would be the best to conduct the final flight test under.

3.1Drag

Buoyancy and therefore lift may be the primary focus in the preliminary stages of

design, but they come with a harsh trade off manifested as drag; lift induced, form and

skin frictional. Drag is a parasitic force which always opposes the direction of motion,

acts in the plane of relative fluid flow and is proportional to the velocity of that flow [2].

Usually in the case of airborne vehicles, this is taken into account during the early

design of the aerofoil and its effective impact minimised. Yet, as the balloon is a non-

rigid structure, and its hull integrity maintained only by pressurisation from the inside,

manipulating its shape isn’t an option. This shortcoming leads us to that all of the drag

will be classed as profile drag, the sum of form and skin friction, with most of the

potential drag likely to be encountered will be form, around 90%. The rest is left to skin

friction as there isn’t any lift induced drag because of the uniform shaped nature of the

balloon [13]. Form drag is produced solely because of the profile of the object, with the

larger the presented cross-section producing the most drag. The specified balloon for the

UAV has a very large cross sectional area of 4.909 m2, yet, in this project, the usually


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damaging size shouldn’t be irrevocable. The reason for this is that the profile drag of an

aerofoil is proportional to its velocity squared:

FD=12

ρ v2CD A

And as the UAV will not be attaining speeds of more than 1−2m s−1 as it flies indoors,

then the drag value will be dramatically lowered.

In order to fully maximise this equation, a value for the coefficient of drag (CD) must be

approximated. This parameter has ties with the Reynolds number of the balloon, a

dimensionless quantity that links the viscosity of the surrounding fluid to the inertial

forces of the balloon. This quantity can also be used to estimate any potential

disturbances in the wake of the UAV, with characterised wake patterns being linked to

values with different profiles. The equation to calculate this constraint is:

Re=V DH

v

With V being the relative velocity of the fluid flow at a distance away from the object

as so the flow is undisturbed. DH is a quantity known as the hydraulic diameter, in the

case of the sphere is simply its diameter, and finally v, the kinematic viscosity of the

adjacent fluid [14]. By simple inspection of the order of magnitudes of each parameter, it

becomes abundantly clear that the driving value behind the formula will be the

kinematic viscosity and as an estimation, that Re is inversely proportion to v, which

leads to the idea that the design specifications of the balloon UAV ultimately will have

little effect on the final Reynolds number and that the external stimuli of the operational

surroundings dictates final practical performance levels.


Figure 2: Reynolds number flow predictions.

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Through using this formula and inputting readily available data, a value attained is:

Re=2∗2.50

15.11 x10−6=3.31 x105

As an operational value, this is extremely high, fundamentally controlled with the low

performance expectations of the balloon UAV. The primary use of this parameter is to

estimate the wake disturbances and flow patterns around the immersed object, allowing

the design to be tailored further still before any physical parts are made. Through

employing the Reynolds numbers predictive nature it is expected that the balloon will

have laminar flow at the boundary layer up until separation, generating a turbulent

wake, as illustrated in figure 2:

This prediction comes with inherent unreliability and to this end, computational fluid

flow simulations shall be run in order to confirm the true nature of the flow patterns.

The aptly named, FloXpress, is a simulation tool that makes up part of the SolidWorks

program package shall be employed to gain a visual appreciation of the balloon’s

interaction with the surrounding fluid.

Upon obtaining the confirmation of the Reynolds number flow, estimations about the

likely drag levels can be made through the relationship of Reynolds number to


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coefficient of drag. NASA research into drag coefficients of a sphere relinquished a

comprehensive set of results, with the trend clearly illustrated in graphical form (figure

12:?). Through extrapolation to the x-axis and assuming the balloon surface is smooth,

which at maximum inflation will be the case, it is clear that the CD of a sphere carrying

our Reynolds number is approximately 0.5 [15]. The implications are that theoretical

calculations can now be made of drag levels at an array of velocities. Then, by plotting

this trend, allow for informed choices to be made about the operational range of the

UAV.

Although the values attained will not be the absolute values, there are certain

advantages to having a value to work with before the critical testing phases. The first of

these being that it will enable the mathematics and the theory to be verified if the

theoretical and practical values come comparatively close. This helps eradicate any

mistakes that many have crept in during the design process, whilst also giving

confidence to pursue more complex solutions. Secondly, understanding these

characteristics will allow for the design of the final stabilising structure to be tailored to

the specific requirements of the rig, as the maximum values of payload and velocity will

be agreed. Finally, they will assist in the final testing procedures, as any anomalous

results from miss-calibration of the wind tunnel will be effective caught and rectified.

3.2 Propulsion

The propulsion of any aircraft is the fundamental driving factor behind its raw

performance, furthering capabilities in not only velocity, but; range, altitude and

payload. With this in mind propulsion can also be aerodynamically exploited in order to

achieve the maximum thrust available from the propellers. One avenue to pursue this is

to add a nacelle, encasing the propellers, with a convergent exhaust nozzle for the


Figure 3: Diagram of potential nacelle design

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propeller to blow air through. As the flow is forced through the conical nozzle, the air

will be accelerated and thus providing extra propulsion.

In order to adopt this approach, the flow must be assumed to be incompressible, which

due to the very low speeds anticipated will be the case for the balloon UAV. With this

in mind, the mass flow rate into the cone will be equal to that out of it, therefore

allowing density changes to be ignored, simplifying the mass flow rate equation to:

V 1 A1=V 2 A2

This explicitly states that if the area of the exit nozzle is smaller than that of the

entrance then the velocity of the airflow will increase [16]. Initially the velocity of the

air at the inlet had to be calculated, which, using the rpm (3000) and propeller pitch

(3in) was achieved to yield a value of 3.81 m s−1. Then applying this value to the mass

flow rate equation, a value of 0.0824 kgs−1was achieved. These hand calculations now

allow for the system to be theoretically and computationally verified in the same vein as

the flow predictions, providing a solid foundation on which final predictions can be

made of the overall performance characteristics of the UAV.


V1

A1

V2

A2

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4 Theoretical/Experimental Calculations

The production of any conceptual design requires a series of critical path tasks to have

been completed before manufacture can proceed, with the next step being theoretical

and experimental validation of the UAV. Before assembling any aspects of the final

design, it is imperative to understand each components performance characteristics and

how they complement each other towards the final objective. Theoretically determining

these parameters and then practically testing reduces wastage during the process, but

more importantly, creates a more accurate preliminary designs, reducing the number of

iterations before optimising the model.

4.1 Buoyancy Experiment

By beginning with the balloon itself, a key limitation of the UAV’s performance will be

its proficiency at carrying payloads, enabling a more complex stabilising structure and

heavier, more powerful motors. Therefore, by calculating this, a solid base prediction

can be made of secondary components. For testing, scale models of the final balloon

had to be used, primarily to save expense, in balloons and helium, and time spent

inflating.

The buoyancy can be found by, ‘the weight of fluid displaced by the body (Anderson:

1984: 27).’ Using this information, calculating the buoyancy is a formality as it will be:

(weight of displace air−weight of helium insideballoon )−weight of the balloon


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The collective buoyancy calculations are all below:

Volume of a sphere=43

π r3

¿ 43

π 0.453, r=0.45 m

V sphere=0.3817 m3

Weight of dsplaced air=V sphere ρair

¿0.3817 (1.225 ) , ρair=1.225 kg m3

W air=0.4676 kg

Weight of Heliumballoon=V sphere ρhelium

¿0.3817 (0.1785 ) , ρhelium=0.1785 kgm3

W helium=0.0681 kgm3

Payload total=[(W ¿¿ air−W helium)−W balloon ]¿

¿ (0.4676−0.0681 )−0.010 , W balloon=0.010 kg

Payload total=0.3889 kg

Buoyancytotal=Payloa d total∗9.81

¿0.3889∗9.81

Buoyancytotal=3.8151 N

Density values [17].


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This value gains significance upon completion of the experiment to practically measure

the buoyancy of the balloon, then the efficiency of the system can be quantified. Also, it

can be used to gauge the success of the practical and allow any errors to be rectified and

the mistake not integrated further.

The practical experiment was detailed previously, page 11, where the test balloon would

be inflated to its stated maximum and mass increments added in order to achieve an

operational value for the buoyancy.

The test began initially by taking readings of the pressure, in mmHg, and the

temperature, in kelvin, enabling a calculation for the air density at that moment. This

would further allow for a theoretical value for the lift to be postulated based on these

parameters and the volume at which the balloon is inflated too. Then filling the balloon

to the predetermined of radius 0.45m with pressurised helium from the container. Due

to the volatility of a highly pressurised balloon and for overall safety, latex gloves were

worn at all times to avoid bursting the subject. Inflation finished once the desired size

was reached, maximum and the knot tied to seal the balloon. String, pre-attached to a

mass harness was then tied the knot at the base of the balloon ready for the increments

to be added.

Before the masses additions could begin, the scales had to be calibrated and zeroed,

ensuring accuracy. With the practical now ready to begin, the system placed on the scale

and the masses added in 100g steps, subtracting the reading from the computed system

weight at each occasion, an approached repeated with scale readings from 631.5 –931.5

grams.

Then, the average difference between these readings illustrates the balloons payload

capabilities, which, when multiplied by gravity, yields the buoyancy force.


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Also deduced from this information was the density of the helium inside the balloon,

which, when the value is studied will allude to the concentration and purity found

inside.

A full copy of the acquired data can be found as table 1 page 46 with the vital

information tabulated below:

Helium density Lift0.236079611 0.330325

4.2 CFD Simulations

A number of experiments were conducted using CFD as it enables metaphysical tests to

be conducted and results collated to a high degree of accuracy. The main subjects were

the design and testing of two different nacelle designs, with the vision of increasing

overall propulsion of the UAV and the balloon, to generate flow and wake simulations

to plot the disturbance made through the air.


TheoreticalCircumference(cm

) Radius V L

0.439 0.354391

0.351617

Experimental Readings

Scale reading Without Balloon

(g)

Scale reading with Balloon (g)

Total lift(lift + spring mass)

631.5 300.8 330.7 330.7731.5 399.9 331.6 331.6831.5 502 329.5 329.5931.5 602 329.5 329.5

P a g e | 21

4.2.1 Balloon Simulation

Beginning with the balloon, the aim was to see how the air reacted to the subject

traveling through at a predicted 2ms-1. The results would firstly, either confirm or deny

the wake predictions form using the Reynolds number, secondly, illustrate pressure

build up on the balloon with the view to passing on the information to the structural

division to aid stability and finally, clearly demonstrate the flow characteristics at the

boundary layer over the surface of the balloon.

The selected program used was SolidWorks, due to its comprehensive flow simulations

addition FloXpress. To begin, the design has to be fabricated in the software, with the

case of the balloon, a simple sphere with the volumetric conditions identical to that of

the physical object.

Then by loading this into the programs FloXpress add on, computational domains can

be selected, allowing the temperature, pressure and flow speed to be dictated. Then by

meshing this the solver can compute the iterations of the system, yielding data on many

system parameters, though the ones applicable here were the:

Flow patterns

Iso-pressure images

The Reynolds number calculation had been conducted with a predicted velocity of

2 m s−1 and for continuity and for direct comparison, this value was used as part of the

input domain for the simulation, along with room temperature of 293.15 K and ISA sea

level pressure 101325 Pa.

The results and images of the relinquished data fields, velocity and pressure can be seen

below (figures 4 and 5: 22):


Figure 5: Velocity simulation results. Figure 4: Pressure simulation results.

P a g e | 22

More comprehensive images are displayed as appendices 4, 5 and 13, pages 53 and 57

and the complete set of results tabulated as table 2, page 47.

4.2.2 Nacelle Simulation

CFD was also used to design and test the nacelle propeller housing which followed a

similar process to that of the balloon by initially having to input the geometry

specifications of each design in order to comparatively test them. Two designs were

tested, with more iterations enabling the correct design would be selected. One, a

conventional cone shape, tapering with straight line to the exit (figure 6:23) the other,

curved, reducing in area dramatically before remaining more constant towards the exit

(figure 7:23), both are illustrated below with images directly from the SolidWorks

program, with larger images as appendices 6 and 7, page 54:


P a g e | 23

Then using the principle alleviated to earlier the:

V 1 A1=V 2 A2

The velocity output computed.

It is clear to see that,V 2∝r2, with r being the radius of the outlet. With this information

estimations were made as to the scale of the reduction in r, finally settling on a third.

The reasons for this are that although the flow is simulated as incompressible, further

tapering the exit nozzle would practically cause certain levels of stagnation pressure

build up as the flow is forced outwards, which in turn would reduce the overall

efficiency. Also due to the low powered nature of the propellers, flow ‘eddying’ in the

outlet could severely lower performance.

This hand calculated information now allowed the system to be simulated using

FloXpress from SolidWorks. Two conical nozzles were modelled, the first with curved

tapering edges, the second with a straight tapered nozzle, both demonstrated with

drawings from SolidWorks, (Figures 6 and 7) had an inlet size of 150mm to encase the

propeller, then converging to 50mm at the exhaust exit.


Figure 6: Straight taped nacelle. Figure 7: Curved nacelle

P a g e | 24

The only unknown, was alluded to earlier, V 1=3.68 m s−1, with the theoretical

calculations shown:

rpm∗60=rph

3000∗60=180,000 rph

180,000∗3=540,000 inches ph , when propeller pitch=3 inches

Then thorough conversions:

V 1=3.81 ms−1

By then using this information in the equation, we generate an expected exit flow

velocity of:

3.81 (0.01767 )=V 2 (0.001963 )

V 2=34.30 m s−1

This now needs to be validated by the simulation where it was observed that for the

same inlet velocity, the airflow speed was greater when using the curved tapered

nacelle, yielding a velocity of 36.214 m s−1, compared to that of 34.2202 m s−1for

alternate profile. A condensed results table is depicted below:

ResultsName – Curved Nacelle Unit Value

Maximum Velocity m/s 36.214

Name – Tapered Nacelle Unit Value


The complete tabulated results are displayed as tables 3 and 4, pages 48 and 49.


P a g e | 25

The advantage of CFD is that the simulations provide fully developed motion footage,

allowing for a visual appreciation of the flow and pressure dynamics. Figures 8 and 9

depict the velocity flow through the nacelle, complete with colour representation in the

key:

Full size images can be found as appendices 8 and 9, page 55.


Figure 8: Straight tapered nacelle simulation results. Figure 9: Curved nacelle simulation results.

P a g e | 26

5. Data Analysis

A fundamental aspect of conducting simulations, tests and experiments is that the

results have to be thoroughly analysed, generating a greater noesis of the parameters

being monitored. From the literature, Lewis-Beck, dictates that through in depth data

analysis the model can be either conclusively supported or that changes need to be

made.

The advantage of theoretical calculations before the tests come to the fore during

analysis also, as the validity of the test and the acquired data can now subjected to

scrutiny and any anomalous results removed from the data selection and retested.

5.1 Buoyancy Experiment

Upon initially conducting the data analysis for the experiment, it has significant benefit

to first, compare the theoretical to practical values, with 3.8151 N theoretically and

3.2402 N during the experiment. This discrepancy is to be expected as theoretical

calculations are based on an idealised set of parameters and most importantly, 100 %

helium concentration. As shown during the test, the helium density value of

0.2361 kgm3, compared to a pure value of 0.1785 kgm3 illustrates that its purity level is

much lower than idealised having a large impact on the important air to balloon weight

differential.

A secondary aspect that will have impacted the absolute lift value was that, on safety

grounds, we were advised not to inflate the balloon to its maximum as the risk of

puncture exponentially increases. To this end, the radius of the experimental balloon is

0.439, and if this was factored into the theoretical calculations the buoyancy would

immediately be lowered to 3.4826 N , 0.3326 N lower, further closing the gap and


P a g e | 27

increasing the reliability of both values. This new force can be used to estimate the

helium purity value and indicates a value close to 93 % .

The success and inherent correlation between the two values means that a prediction for

the buoyancy of the full size balloon, where r is 1.25 m, can be made and also carry the

93 % purity value forwards to give a more accurate representation of the practical value

yielding a theoretical buoyancy of 82.5180 N , then applying the purity factor generates

a final practical buoyancy value of 76.7418 N , effectively allowing a payload of

7.823 kg.

5.2 CFD Simulations

The CFD simulations obviously use computer programs to compute the desired

scenarios and generate the data spread in many formats; video simulations, iso -pressure

images or tabular form, making their analysis a far more interesting prospect.

5.2.1 Balloon Simulation

The primary focus during this simulation was to investigate the flow and wake patterns

when disrupted by the balloons presence and then compare these to the theoretical

interpretation previously depicted.

Beginning with the wake flow analysis, the predicted flow pattern was generated from

use of the Reynolds number and issued an estimation of the disturbance (figure 2:14).

Through controlling the computational domain of the simulation and selecting the same

size sphere and velocity of motion, the program was able to render a moving image

demonstrating the reaction of the fluid, demonstrated by figures 4 and 5 (page22) and a

further rendered image in the appendix as figure 13 page 57.


P a g e | 28

Firstly, the visual comparison of the two predictions are identical, even to the point of

separation. The boundary layer remains intact, known as the coanda effect – a fluids

tendency to attach to a smooth surface [18], until the adhesive force is overcome by the

force from the direction of travel, at which point the separation air flow constricts the

disturbed eddying flow between it, most clearly demonstrated on figure 4 (page 22).

The disrupted air then begins a helical flow pattern (figure 13:57), most likely caused

from sideslip off the cascading geometry of the balloon. Also the wake signals a

stagnation of low pressure to the rear of the balloon as the airflow begins to converge

after separation before stabilising as the pressure returns closer to that of the ambient.

This all signifies the reliability of the calculated Reynolds number, and from that, the

coefficient of drag, which now allows a secondary experiment to predict the drag level

faced by the UAV at an array of velocities.

A further simulation was of the pressure stagnation upon the balloons surface and the

image (figure 5:22) clearly illustrates that the area under the largest pressure is the face

perpendicular to the motion of travel. The pressure gradually reduces until it reaches its

minima, parallel to motion as the airflow is slightly accelerated by the balloon as it

travels over its largest radius.

5.2.2 Nacelle Simulation

The first note of comparison, is that the simulated velocities are close to the theoretical

value, which indicates the credibility of the test and that human error, in the form of

data input, did not occur. This success now allows the comparison of the two proposals

to be analysed with greater credibility and further reinforces the technique of theoretical

validation.


P a g e | 29

The implications of the simulation reaching a definitive result made the choice of the

most advantageous option for the UAV simple and also provided proof that the design

orientation was the correct one. Also for the curved convergence, the airflow reaches

the maximum speed earlier in the nozzle, stabilising before exit, which has added

propulsive benefit with a directionally uniform airflow.

In order to endorse the results from the simulation, a practical test will take place, were

the physical effect can be witnessed. Also the assumption of uniform, incompressible

flow had been made, which in practice would not be the case as slight compression

would take place towards the exit of the nozzle, in turn marginally constricting the fluid

flow and slightly reducing the nacelles effectiveness.


P a g e | 30

6. Further Experiments

Completing the data analysis on the first stage of experimental testing alluded to the

success and viability of parameters that had been calculated. Now, as stated in the

literature by Ertas, next in the design process is to refine and test again. However the

initial tests ended in positive results, leaving the only consideration to be the level of

drag likely to be encountered during operation.

6.1 Drag Force Prediction

Having an accurate prediction of the operational drag forces will significantly aid in

beginning to understand the complexity of the model when in motion. Managing to

attain a value for the drag at a range of values will enable the system to be more

effectively modelled by mathematics. Through using the formula:

FD=12

ρ v2CD A

The magnitude of the drags influence can be examined at a range of velocities, a sample

calculation takes the form of:

FD=12

(1.225 ) v2 (0.5 ) (19.635 ) , ρ=1.225 , CD=0.5 , A=19.635

The CDwas the value that was proven from the balloon wake simulations, as this

reinforced that Reynolds number and from the association between the coefficient of

drag and the Reynolds number for a sphere investigated by NASA (2010) and illustrated

in graphical form (Figure 12:57) [15].

Now through varying v between 0 and 2m s−1 ,the relationship between the two can be

appreciated, depicted by figure 10 (page 31).


P a g e | 31

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

1

2

3

4

5

6

7

Drag Force Vs Velocity

Drag

Velocity (ms-1)

Drag

Forc

e (N)

Figure 10: Drag vs Velocity graph

The complete table of results is in the appendix, table 5, page 50.


P a g e | 32

7. Further Analysis

Analysis in to the secondary experimentation will illuminate the need to carry out any

more investigations into yet alluded to parameters, whilst also increasing the

understanding of previous experimental data sets.

7.1 Drag Force Prediction

The velocity range of the UAV is likely to be low, and therefore the drag calculations

were only modelled up to2m s−1.

Through visual analysis of the graph, it is clear to see the exponential rise in drag in

accordance to the increase in the velocity. The understanding behind this is that the drag

force FD∝ v2causing the exponential gradient rise. The drag is also dependant on the

cross sectional area and therefore also proportional to r2, whereas the buoyancy,

B∝ r3, thus creating a trade-off between buoyancy and drag, as seen in the literature.

The drag force prediction is a vital part of the design process as it is one of the four

fundamental forces that drive motion; lift, weight, thrust and drag. In the UAV’s case,

the lift and the weight forces will remain constant at all times due to design

specifications, therefore promoting thrust and drag forces to an increased level of

prominence. Being able to definitively know the obstructive force at any velocity will

allow for the thrust levels to be designed to exceed the resistive forces of drag and drive

the system forwards.


P a g e | 33

8. Conclusions

In this section the implications of the work carried out shall be conducted, focusing on

how this will affect the model and procedures moving forwards and any future work

that could be conducted if time allowed. Initially, discussions about each experiments

evaluation shall transpire.

8.1 Discussion

Analysed results only highlight discrepancies within the data stream, to fully understand

and therefore utilise the findings, demonstrating the reasons for these incongruences

shall alleviates the results. Through discussing the differences and then comparing these

back to the literature, the success, reliability and validity of the experiments can be

proven.

4.

5.

6.

7.

8.

8.1

8.1.1 Buoyancy Experiment

During the buoyancy experiment, it was demonstrated that from the theoretical value,

0.2424 N of lift performance was lost, generating an error of:

Error=Theoretical−ExperimentalTheoretical

∗100

¿ 3.4826−3.24023.4826

∗100


P a g e | 34

Error=6.96 %

As the literature depicted, this is seen as a very acceptable level of error, although

aiming to improve this value will inevitably improve the UAV’s performance and ease

computational design reliability. As established in the analysis, the purity of the helium

wasn’t perfect at 93 % , and increasing this would further reduce the statistical error.

One method of inducing this would be, before helium inflation, to pump all the residual

air out of the balloon, seal the base, then attach it to the helium tanks, thus improving

purity and ultimately the buoyancy force inducted.

This aside, the levels of lift confirmed by the balloon will mean there will definitely be

a surplus once the motor construction and stabilising structure are added, which gives

the distinct advantage of being able to add ballast to the system. The benefit of this is

that we get to decide where we want to the concentration of weight to be, and to

increase the stability of the UAV as a whole. Ideally the ballast would need to be

located centrally to deter the system from any kind of pitch and roll during motion.

8.1.2 CFD Simulations

Computational fluid dynamics is a relatively new technology that has vastly improved

the art of design and simulation, allowing multiple variations, some only altered by

millimetres, to be tested in accordance with one another at no physical cost. This not

only reduces the cost, but use of materials, wastage, time and man power, allowing

design focus to view the peripherals, encompassing and integrating the whole system

together as they are designed simultaneously.

8.1.2.1 Balloon Simulation

Conducting the simulations on the balloon allowed for an understanding to be gained of

aspects that cannot easily be physical monitored. Using a wind tunnel is one of few


P a g e | 35

ways to measure the airflow over the surface of objects, yet when that object is a

balloon, the situation becomes more complex as fixing the balloon to achieve a

consistent reading would be almost impossible.

The aim of the experiment was to confirm the flow was behaving in the predicted way,

thus confirming the Reynolds number for the system, which in turn confirms the

coefficient of drag promoting further work, as supported by the design process from the

literature.

The results of the perceived wake of the balloon was exactly as expected, supported by

the theory, pointed towards a conclusive success. Through images of the simulation

(figures 4, 5:22) the expected laminar flow, primarily due to low air speed, was

perceived up until the separation point, where the viscous nature of the flow becomes

overawed by the force of the flow and breaks away from the boundary layer on the

surface of the balloon and becoming turbulent in the wake.

8.1.2.2 Nacelle Simulation

A similar case to the simulation of the balloon, the investigation was conducted using

computational means and the flow patterns simulated. The aim of the design was to

induce an air flow velocity increase as the profile of the nacelle narrows, a hypothesis

strongly supported by the relevant literature, most notably Cohen and Rodgers.

As seen in the results data, one design accelerated the air more efficiently than its

counterpart down to it sleeker profile design. Also, as the profile converged more

aggressively before levelling out, the air flow was accelerated most initially, stabilising

before the exit nozzle. This in itself is more advantages, as a more uniform flow would

provide greater thrust capacities in the desired direction, in comparison to the where the

air flow will likely be turbulent on exit and therefore lose efficiency.


P a g e | 36

The obvious success of the experiment made progressing forwards with the design

process much simpler, and also supports the statements made in the literature regarding

design techniques.

Unfortunately, due to strict time constraints and limited apparatus, the planned physical

conduction of experiments with the nacelle wasn’t able to take place, where the effects

on the airflow from the simulation would be mirrored and results compared. From the

literature, it was clear to not expect the exemplary performance characteristics from the

computational test, as these are an idealised set of circumstances and inefficiencies such

as; pressure stagnation, eddying currents and skin friction from the model are neglected.

8.1.3 Drag Force Prediction

This experiment became valid directly from the success of the balloon simulation test

discussed earlier (page 27). Progression in this manner is supported in the literature and

depicts a success project and allows secondary parameters to be indirectly monitored, in

this case the drag.

Aforementioned, again during the balloon simulation section, (page 34) physically

measuring airflow characteristics of a balloon in a wind tunnel would be problematic

and therefore many parameters have had to be modelled theoretically. The implications

of this are that, with any theoretical calculation, the attained value will always be an

idealised situation, where certain inefficiencies aren’t taken into account to reduce the

complexity of the formulas.

Here, the material of the balloon is neglected and to this end, skin friction isn’t factored

into the final drag value. Fortunately, according to Shapiro (1961) around 90% of the

drag encountered will be form drag, with the other 10% determined by skin friction.


P a g e | 37

The levels of drag predicted were only of very small intensities due to the low velocities

attained and therefore this discrepancy will have little effect of on the final output.

Further reducing its importance is that, from the results yielded from the nacelle

simulations, there is an abundance of thrust that far exceeds the resistive forces like to

be encountered.

8.2 Outcomes

The aim of the project was to design a functioning balloon UAV and in this section the

final processes of manufacturing the robot shall be discussed with explanation, analysis

and discussion of issues faced.

Upon the group completing the necessary research into their designated fields, the time

came to complete the physical entity of the ‘balloon bot’. Two structural design were

produced and therefore we created two versions of the robot:

The initial design had the structural casing seated centrally below the balloon. The

concept mirrored that of a hot air balloon, an air vehicle with similar characteristics,

with the propulsion system hung in suspension below the balloon in line with its

aerodynamic centre for maximum stability and performance. The propellers were then

mounted at 300mm from the central point on a 3mm steel rod.

The second again had all the main electrical components housed in the structural casing,

although this was physically attached to the base of the balloon, rather more like the

traditional blimps depicted in the literature such as the Bosch SASS lite. The arms on

which the propellers are then connected was reduced for the second iteration to induce

aspects with comparative testing capabilities. They were mounted at 150mm from the

centre, which overall had many performance benefits.


P a g e | 38

Between the two designs, it was initially clear to see that form a stability aspect, the

second design would be the most beneficial allowing for smoother control and reducing

the amount of induced roll and yaw upon power application. This was due to the free

hanging nature of the first design where, as power was applied the housing would rock

and then the moment translated into the balloon harming overall performance.

8.2.1 Rotational analysis

Completing the UAV allows for the opportunity to perform practical experiments that

would otherwise prove problematic. One such test was a rotational analysis,

investigating the varying performance characteristics of the two designs during rotation.

The hypothesis is that, the wider placed motors will reduce the rotation period, as the

turning moment will be increased due to the extra perpendicular distance [19]:

Moment ( Nm )=Force∗Perpendiclaur distance

Understanding this area will allow for more apt designs to be devised during future

work, including providing a stable rotational time period that allows the user to react to

the manoeuvre.

Of the two designs, the main difference was the location of the propellers, with the first

placed 300mm from the centre, with this distance reduced to 150mm for the second

design. Then through monitoring the time taken to alter the orientation of the UAV to

varying angles the following data set was acquired with the complete data set found as

table 6, page 51 in the appendix:

300mm armsRotatio

n Degree

Time (s) (Average

)0 0

90 0.7


P a g e | 39

180 1.3360 2.1

150mm arms

0 090 1

180 1.4360 2.6

From the attained results it is clear to see the hypothesis is correct as the large moment

arm induced significantly reduced rotation times, between 30-40% during most

rotations. Although in most cases obtaining peak performance characteristics is the

projected endeavour, in this case, achieving stable operational performance is the key

requirement. Observed during the experiment was that the smaller arm offered this

prerequisite, allowing for greater ease of control, increasing the reaction window to

accurately steering the robot. The slower turning circle also lends itself to the relay lag

between remote input into the program and the instruction then being carried out by the

audrino.

Due to the conclusive nature of the result and analysis, the shorter moment arm design

was sanctioned as the final structural rig to be permanently operated.

8.3 Future Work

As with any design and manufacturing project with a finite development timescale,

there are avenues that couldn’t be fully explored, the complexity of the project ensured

that there are a multitude of an areas to investigate and therefore subject prioritisation

had to take place. Discussing future work can alleviate important facets of potential

development directions, also once the design is fully functional, improving efficiency

becomes an important subject of exploration.


P a g e | 40

8.3.1 Balloon Development

A key area of development would be investigating potential shapes for the balloon, as

the overall intricacy of the design was substantial, simplification in certain areas

allowed for the design to fit the allotted timeframe. A spheres crude shape allowed for

structural designs to retain a more modest approach and provide completed models.

Developing a proficiency in this area will decrease the most resistive force faced during

operation, drag, which as illustrated in the literature (Shapiro, 1961) manifests itself

mainly as profile drag, 90%, thus by inhibiting the profile of the object in question

interacting perpendicular to the airflow, parasitic drag forces shall be reduced. The

major gains will be through reducing the drag encountered, thus improving not only

operational efficiency, but also peak performance characteristics furthering acceleration,

top speed and manoeuvrability.

Altering the shape would induce the necessity for secondary research into other areas

such as helium diffusion. As helium diffuses through the surface of the balloon. If the

shape was anything other than perfectly uniform, a sphere, then its profile would alter

slightly and this would have to be investigated. Circumstances such as this would place

an operational life span on the UAV before certain aspects would have to be serviced.

Also, the final structural design was far lighter than anticipated, coming in at around

500 g, as a result the balloon had payload capabilities far beyond what was necessary

and during testing the balloon was not fully inflated. To this end, using the buoyancy

calculations undertaken previously, it becomes apparent only 6.39 %of the original

payload capacity is required (after efficiency factors applied) and, to reduce the amount

of required ballast, a balloon with a radius of 0.5 m would satisfy.


P a g e | 41

The advantages go further than reducing ballasts complications, as the reduced size has

secondary benefits in reducing the induced drag from the balloons profile. A gain such

as this would lower the peak drag at 2m s−1from 6 N to 0.96 N , significant progress

encountering 84 % less restive force. Again, this is only taking form drag into the

scenario, so the practical value would be slightly higher once skin friction is taken into

account. The new information is illustrated in the graph below (figure 11):

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

0.2

0.4

0.6

0.8

1

1.2


Drag

Velocity (ms-1)

Drag

For

ce (N

)

Figure 11: Revised drag prediction.

8.3.2 Structural Advancements

Another significant area would be to perform aerodynamic analysis on the equipment

housing which attaches to the base of the balloon. The final design would cause a

substantial amount of drag, and through a joint venture with the structural design team,

focusing on surfaces whose profile interacts directly with the air flow, creating more

aerofoil like surfaces to generate a more laminar flow.


P a g e | 42

The advantages of progression in this area are profound and demonstrated in vast

amounts of literature (Batchelor, 1973) and although the surfaces lift production will be

minimal, it’s a capacity that isn’t required with the abundance being produced through

buoyancy. The effects of the drag reduction will be very similar to that of the balloon

increasing the almost all efficiency and manoeuvrable aspects of the UAV.

Although, advancements in this sector must be approached with slight trepidation, the

structures primary function is to house the externals of the robot and becoming too

aggressive with aerodynamic pursuits could jeopardise the integrity of the structure.

8.4 Conclusion

As a projects lifecycle comes to an end, an important task to carry out is reflection, to

ensure that lessons have been understood and can be carried forwards and applied to the

next situation.

It was observed that the advancement of technology was leading the world towards

automating many of the previously human operated equipment. This is clearly visible in

other engineering sectors, most notably manufacturing, where applying users to

practical applications has become obsolete and replaced by more accurate, efficient

computational systems. With the development of artificial intelligence (AI) the cross

over between where a humans judgement and a computers analysis is most effective is

becoming more hazy, couple this with the added requirement for casualty minimisation

and stringent safety applications, the aerospace industry is heavily investing and

developing unmanned aerial vehicles.


P a g e | 43

With this in mind, this paper has aligned itself with these views and transcribes the

undertaking of the design, manufacture and testing of such an aircraft. The ‘balloon bot’

UAV applies the previously learnt lessons of unmanned flight to produce the final

indoor flying robot. The venture was partially successful with several controlled

airborne successes occurred during closed door tests, although ultimately no sustained

flight was verified.

There were many difficulties faced and overcome during the project such as;

information black spots, testing difficulties and temperamental apparatus. The lessons

of the delicacy of testing with volatile equipment, as one major burden during testing

was the sensitivity of the balloons which regularly popped halting progress. This

highlighted the difficulties faced in the industry of practical design, demonstrating the

timescales of such tasks and inconveniences of facet failures. Further complications

arose from the sporadic material on the subject, meaning most of the work was primary

research.

Moving forwards, certain improvements could be made to the critical path in order to

achieve a more successful outcome, by potentially beginning construction and testing

earlier to allow contingency periods in the event of process failures.

Overall, as robotics was an uncharted academic subject, the advancement demonstrated

during the project term illustrates the success and progression of the group. By working

together cohesively and relying on each other to complete tasks to move forwards, an

operational product was produced and individual understand of such matters enhanced.

The rarity of directly applicable subject matter increased the difficulty of the project, yet

this was overcome soundly. The literature on model designs mirrors that of which we


P a g e | 44

applied, depicting the overall successful nature of the study, even if in fact the final

product still required further work.

9. References

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2. Lachmann, G. Boundary layer and flow control. New York [u.a.]: Pergamon

Press. 1961.

3. Kermode, A., Barnard, R. and Philpott, D. Mechanics of flight. Harlow:

Longman. 1996.

4. Hazewinkel, M. Lagrange equations (in mechanics), Encyclopedia of

Mathematics. Berlin: Springer. 2001.

5. A.R. Vasel-Be-Hagh, R. Carriveau, D.S.-K. Ting, Numerical simulation of flow

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6. Munson, K. Jane's unmanned aerial vehicles and targets. Coulsdon, Surrey,

UK: Jane's Information Group. 1995.

7. Zufferey, J.C. Bio-inspired Flying Robots: Experimental Synthesis of

Autonomous Indoor Flyers. Lausanne: EPFL Press. 2008.

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Brunt Mill, Harlow, Essex: Longman Scientific & Technical. 1987.


P a g e | 45

9. Ertas, A. and Jones, J. C. (1996). The Engineering Design Process. New York:

John Wiley & Sons, Inc. 1993.

10. Tu, J., Yeoh, G. H. and Liu, C. Computational Fluid Dynamics. Amsterdam:

Butterworth-Heinemann. 2008.

11. Lewis-Beck, M. S. Data Analysis. Thousand Oaks, Calif: Sage Publications.

1995.

12. Zuljian, D. and Grum, J. n,d. An Introduction to Error Analysis, the Study of

Uncertainties in Physical Measurements/ John R Taylor.

13. French, A. Newtonian mechanics. New York: W.W. Norton. 1971.

14. Shapiro, A. Shape and flow. Garden City, N.Y.: Anchor Books. 1961.

15. Grc.nasa.gov. Drag of a Sphere. [online] Available at:

http://www.grc.nasa.gov/WWW/k-12/airplane/dragshpere.html [Accessed: 26

Mar 2014].

16. Batchelor, G. An introduction to fluid dynamics. 1st ed. Cambridge: University

Press. 1973.

17. Engineeringtoolbox.com. Air Properties. [online] Available at:

http://www.engineeringtoolbox.com/air-properties-d_156.html [Accessed 15

Mar 2014].

18. Tritton, D. Physical fluid dynamics. 1st ed. Oxford [England]: Clarendon Press.

1988.

19. Serway, R. A. and Jewett, Jr. J. W. Physics for Scientists and Engineers. 6th Ed.

Brooks Cole. 2003.


P a g e | 46

10. Appendices

10.1 Tables

Table 1 – Buoyancy Test Data.

Temperature 297.65Pressure 99791.7928Density 1.16817267

String Mass 0Theoretical

Circumference(cm) Radius V L

0.439 0.354391

0.351617

Experimental Readings

Scale reading 1 Scale reading 2

Total lift(lift + spring mass)

631.5 300.8 330.7 330.7731.5 399.9 331.6 331.6831.5 502 329.5 329.5931.5 602 329.5 329.5


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Helium density Lift

0.236079611 0.330325

Table 2 – Balloon Simulation Results.

Min/Max Table

Name Minimum Maximum

Pressure [Pa] 101323 101327

Temperature [K] 293.198 293.202

Velocity [m/s] 0 2.74006

X – Component of Velocity [m/s]

-0.224311 2.7299

Y – Component of Velocity [m/s]

-1.32104 1.32313

Z – Component of Velocity [m/s]

-1.32037 1.32294

Fluid Temperature [K] 293.198 293.202

Mach Number [ ] 0 0.0079846

Shear Stress [Pa] 0 0.0111969

Heat Transfer Coefficient [W/m^2/K]

0 0

Surface Heat Flux [W/m^2] 0 0

Density [kg/m^3] 1.20368 1.20373


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Table 3 – Straight Tapered Nacelle Results.

SolidWorks FloXpress Report

ModelModel Name: F:\Balloon Robot\straight cone with lids.SLDASM

Smallest Flow PassageSmallest flow passage: 0.145666421 m

FluidAir

Inlet Mass Flow 1Type Mass Flow Rate

Faces <1 >

Value Mass Flow Rate: 0.0783 kg/s

Temperature: 293.2 K

Environment Pressure 1Type Environment Pressure

Faces <1 >

Value Environment Pressure: 101325 Pa


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ResultsName – Tapered Nacelle Unit Value


Table 4 – Curved Nacelle Simulation Results.

SolidWorks FloXpress Report

ModelModel Name: F:\Balloon Robot\curved cone completed.SLDASM

Smallest Flow PassageSmallest flow passage: 0.145666421 m

FluidAir

Inlet Mass Flow 1Type Mass Flow Rate

Faces <1 >

Value Mass Flow Rate: 0.0783 kg/s


Environment Pressure 1Type Environment Pressure

Faces <1 >


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Value Environment Pressure: 101325 Pa


ResultsName – Curved Nacelle Unit Value


Table 5 – Drag/Velocity Data.

density 1.225A 4.909Cd 0.5

drag (N)v (ms-

1)0 0

0.015034 0.1

0.060135 0.2

0.135304 0.3

0.240541 0.4

0.375845 0.5

0.541217 0.6

0.736657 0.7

0.962164 0.8

1.217739 0.9

1.50338 1


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11.81909

1 1.12.16486

9 1.22.54071

4 1.32.94662

7 1.43.38260

8 1.53.84865

6 1.64.34477

2 1.74.87095

5 1.85.42720

6 1.96.01352

5 2

Table 6 – Rotational Analysis.

Rotational Analysis

300mm arms Readings

Rotation Degree

Time (s) (Average

)0 0 0 0 0 0 0


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90 0.70.67

0.69

0.72

0.71 0.71

180 1.31.33

1.28

1.34

1.31 1.27

360 2.12.08 2.1

2.11

2.11 2.09

150mm arms

0 0 0 0 0 0 0

90 10.95

1.03

1.01

0.98 1

180 1.41.36 1.3

1.41

1.43 1.43

360 2.62.55

2.59

2.66 2.6 2.61

10.2 Figures

Figure 1 – Original Balloon Design.

Figure 2 – Reynolds Number Flow Prediction.


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Figure 3 – Propulsion Diagram.

Figure 4 – Balloon Velocity Simulation Results.


V1

A1

V2

A2

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Figure 5 – Balloon Pressure Simulation Results.

Figure 6 – Straight Tapered Nacelle.


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Figure 7 – Curved Nacelle.

Figure 8 – Straight Tapered Nacelle Simulated Results.


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Figure 9 – Curved Nacelle Simulated Results.

Figure 10 – Drag vs Velocity Graph.


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0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

1

2

3

4

5

6

7


Drag

Velocity (ms-1)

Drag

For

ce (N

)

Figure 11 – Revised Drag Prediction.

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

0.2

0.4

0.6

0.8

1

1.2


Drag

Velocity (ms-1)

Drag

For

ce (N

)

Figure 12 - NASA Drage of a Sphere Graph.


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Figure 13 Balloon Simulation Flow Pattern
