The Fidelity Requirements for Fixed Wing Flight Simulator Training Final Report

Author: James E. Pattison 200683406 Supervisor: Prof. J. F. Ralph Assessor: Prof. S. Maskell Date: 30 April 2014

I confirm that I have read and understood the University’s definitions of plagiarism, collusion and the fabrication of data from the Code of Practice on Assessment. I confirm that I have not committed plagiarism or fabrication of data when completing the attached piece of work, nor have I colluded with any other student in the preparation and production of this work.

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Summary This report examines the role of Flight Simulation towards the training of modern-day pilots,

and specifically seeks to increase its involvement in the General Aviation sector. It highlights

the improvements Flight Simulation has brought to flight safety over the years, but also

recognises the crucial fact that the vast majority of pilots in training do not receive any

Flight Simulator training as part of a standard training programme. The report looks at the

considerable benefits of simulator training towards both low hour General Aviation pilots as

well as the potential cost saving benefits for Flight Training Organisations. The report

analyses how vital the advancement in Flight Simulation has been over the last decade, and

also how critically important it is in relation to flight safety, specifically towards General

Aviation. Flight Simulation is an ever increasing and investable prospect, due to such rapid

advancements in research and technology in the aviation industry as a whole. This change is

only noticeable in large FTOs; generally there has been no change in the way small GA

schools operate. Flight Simulation has considerably reduced the cost of flight training for

large FTOs whilst also improving safety. It is the aim of this report to recommend that the

same standards should also be demanded in the General Aviation sector. This report

deduces the high viability towards the use of Flight Simulation as a practical means to

reducing the accident rate in the General Aviation sector and concludes by outlining

methods for further research building on the findings presented in this report.

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Acknowledgements The author would like to thank Dr Elias Griffith for his kind assistance and help with MATLAB

code. Thanks also goes to Professor Jason Ralph and Dr Mark White for their continuous day

to day help as well as Professor Simon Maskell for providing insight into continuing this

product into the summer as part of the Universities Student Business Incubation Unit

scheme, where a £500 grant has been applied for. Thanks should also go to the author’s

colleague Tom Burton, for loaning his IMU to this project and for allowing the first unit test

to be in a real aircraft. Finally the author would also like to thank Professor Kenneth

Edwards from the Universities Industrial Advisory Board for his guidance and introduction to

external contacts in the aviation industry.

iii

Acronyms GA General Aviation

PPL Private Pilots Licence

CPL Commercial Pilots Licence

ATPL Air Transport Pilots Licence

CAA Civil Aviation Authority

EASA European Aviation Safety Agency

FAA Federal Aviation Administration

NTSB National Transportation Safety Board

GASCo General Aviation Safety Council

VFR Visual Flight Rules

IFR Instrument Flight Rules

VMC Visual Meteorological Conditions

IMC Instrument Meteorological Conditions

ILS Instrument Landing System

EFATO Engine Failure After Takeoff

CAVOK Ceiling And Visibility OK

AGL Above Ground Level

PAPI Precision Approach Path Indicator

MATLAB Matrix Laboratory

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Table of Contents

Summary ..................................................................................................................................... i

Acknowledgements .................................................................................................................... ii

Acronyms .................................................................................................................................. iii

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

1.1 Background ....................................................................................................................... 1

1.2 Aims and Objectives ..................................................................................................... 3

1.3 Project Approach .......................................................................................................... 3

1.4 Industrial relevance, real-world applicability and scientific impact ............................. 4

2. Literature Review ................................................................................................................... 6

2.1 Introduction ...................................................................................................................... 6

2.2 Review of Research Papers .............................................................................................. 7

2.2.1 General Aviation Accidents ....................................................................................... 7

2.2.2 Transfer of Training ................................................................................................. 11

2.2.3 The General Aircraft Flight Simulation Device ........................................................ 13

2.2.4 The Role of Flight Simulation in Pilot Training ........................................................ 13

2.2.5 Training Effectiveness .............................................................................................. 15

2.3 Discussion of Future Research Opportunities ................................................................ 16

2.4 Closure ............................................................................................................................ 17

3. Theory .................................................................................................................................. 18

3.1 The Flight Simulation Device .......................................................................................... 18

3.1.1 The Composition of the FSD .................................................................................... 18

3.1.2 The Mathematical Model of the FSD ...................................................................... 19

3.2 The Flight Model Components ....................................................................................... 20

4. Design ................................................................................................................................... 21

4.1 The Flight Simulation Device (FSD) ................................................................................ 21

4.2 The Inertial Measurement Unit (IMU) ........................................................................... 23

5. Experimental Method .......................................................................................................... 24

5.1 Stage 1 – Aircraft Model Development .......................................................................... 24

5.2 Stage 2 – Simulator Testing ............................................................................................ 25

5.2.1 Development of Standard Training Profile .............................................................. 25

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5.2.2 Simulator Integration .............................................................................................. 25

5.2 Stage 3 – Aircraft Testing ............................................................................................... 28

6. Results and Discussion ......................................................................................................... 30

6.1 Results ............................................................................................................................ 30

6.1.1 Flight Test 1 ............................................................................................................. 30

6.1.2 Flight Test 2 ............................................................................................................. 32

6.1.3 Flight Test 3 ............................................................................................................. 34

6.1.4 Flight Test 4 ............................................................................................................. 35

6.1.5 Flight Test 5 ............................................................................................................. 39

6.1.6 Flight Test 6 ............................................................................................................. 41

6.2 Discussion ....................................................................................................................... 43

6.2.1 Discussion of Flight Testing ..................................................................................... 43

6.2.2 The Circuit Importance ............................................................................................ 45

6.2.3 Limitations ............................................................................................................... 46

7. Conclusions and Recommendations .................................................................................... 48

Works Cited .............................................................................................................................. 49

Appendix A ............................................................................................................................... 52

Appendix B ............................................................................................................................... 53

Appendix C ............................................................................................................................... 55

Appendix D ............................................................................................................................... 56

Appendix D ............................................................................................................................... 60

Appendix E ............................................................................................................................... 61

Appendix E ............................................................................................................................... 62

Appendix F ............................................................................................................................... 65

Appendix G ............................................................................................................................... 68

1

1. Introduction With the ever increasing role of Flight Simulation in Commercial and Military Aviation, it is

becoming essential to find a viable means of measuring the training effectiveness gained, in

order to influence the introduction of such technology into the General Aviation sector.

Here, a brief background is presented on the different areas of aviation and their respective

simulator involvement towards flight training. The literature review focuses on previous

research undertaken in the field in order to relate the project to current problems in

General Aviation training. This includes research towards the fidelity requirements for fixed

wing Flight Simulation and also the potential benefits of this synthetic training towards

reducing accident rates in General Aviation.

1.1 Background Undoubtedly Flight Simulation has had a major influence on improving safety for civil

operations and is now regarded as a standard means of training for new and current pilots.

The largest operators of Flight Simulators in aviation are the airlines; they are used as type

converter trainers and also as a platform for the compulsory bi-annual checks all pilots must

undertake. Flight Simulators are a widely accepted training mechanism in the commercial

environment. Large commercial simulators cost in excess of £6M and they are closely

regulated by the airlines themselves and aviation authorities in order to ensure they meet

strict training requirements. As well as having a strong influence on improving safety across

the board, Flight Simulators also provide a considerable cost saving advantage. This makes

them an attractive proposition for airlines that spend hundreds of thousands of pounds

training their pilots each year. There have been significant technological advances in

simulation over the past few years, leading to a reduction in cost of simulation hardware

and improved performance. Currently this change is only noticeable in the civil sector. Thus

this technology has the potential for wider applications and to be expanded and

implemented into other sectors of the aviation industry.

These advances are only noticeable in the civil sector as they are focussed on the large

‘Level-D’ standard simulators. These are full motion simulators used by airlines and the

military; they have no comparison to small General Aviation ‘part task trainers’ or PTTs.

These PTTs range from simple computer-based models of specific aircraft systems to full-

scale replicas of cockpits, for initial familiarisation work with the aircraft.

‘The international Full Flight Simulator Level-D standard (the highest current standard)

requires a motion platform capable of moving the simulator cab in all six degrees of freedom

and an outside world visual system giving 150 x 40 degrees of view to each pilot. Military

Flight Simulators are more variable in design but most military transport aircraft and many

military helicopter simulators are based on the civil FFS design.’ [1]

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Figure 1 shows a FFD Level-D simulator manufactured by the French firm Thales.

Figure 1 - A FFD Level-D Standard Flight Simulator [1]

With regards to the General Aviation sector, pilots have no requirements to undergo any

Flight Simulator based training. The training methods associated with PPL and CPL flight

training are centred upon airborne exercises and ground school. These have changed very

little over the past 70 years, and as such simulator integration, a huge part of ATPL training,

has been completely left out of the syllabus.

In the United Kingdom, pilot licensing is regulated by the Civil Aviation Authority under the

scrutiny of the European Aviation Safety Agency. Each member nation in the EU has

responsibility for regulating their own pilot licensing. The principal reference for flight crew

licensing in the UK is CAP804 which is published by the CAA on paper and online. [2]

In the UK, the CAA stipulates a minimum requirement of 45 flight hours in order to gain a

PPL. However, this is dependent on a number of key factors such as the pilots’ aptitude and

skill, meteorological conditions and the duration between lessons. Currently, the average

flight time for PPL students in the UK is just under 80 hours and this can be achieved in

around 6 months at a rate of 2 hours flown per week.

The current CAA minimum requirements stipulate that ‘Applicants for a Private Pilot Licence

must be at least 17 years old, hold a valid EASA Part-MED Class 2 Medical Certificate, and

have met the specified practical and theoretical training requirements laid down in EASA-

FCL. This presently includes nine written theory examinations, completing at least 45 hours'

flying training, including ten hours' solo flying, five hours' solo 'cross-country' flying and at

least one solo flight of not fewer than 150 nautical miles with full-stop landings at two or

more different aerodromes other than the aerodrome of departure.’ [2]

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1.2 Aims and Objectives Aim:

To research the effectiveness of training for specific scenarios of flight, in order to measure

how much training time on a simulator can benefit real-world flight training with regards to

overall safety.

Objectives:

• To research the effectiveness of training for specific scenarios of flight and identify critical operational areas that pilots experience problems with during training.

• To investigate problem areas and examine how pilots could be more effectively

trained with the use of Flight Simulation.

• To measure how much training on a simulator can benefit real-world flight training, with regards to overall safety as well as the cost saving benefit.

• To enhance the existing training framework for GA pilots, building on the document

ICAO9625.

1.3 Project Approach The first stage involved selecting a group of pilots that were suitable for this level of testing.

Both novice and instructor pilots were chosen. Novice pilots who had completed the circuit

ground school were deemed of an acceptable level by the flying school to take part in the

exercises. These pilots were subsequently immersed in the challenging environment of the

visual circuit at Liverpool airport. Current problems and/or challenge areas were identified

with the aid of an instructor from Liverpool Flying School. This instructor also verified testing

techniques of the project to ensure they conformed to the standard PPL syllabus. Learning

outcomes were measured by plotting recorded simulator data in MATLAB against real world

data. Consequently existing methods and safety could be improved by measuring pilot

performance in a multitude of training scenarios. Finally the most efficient form of training

was implemented into a specific training scenario, with overall performance re-assessed.

The overall aim of testing and evaluation was to reduce accident rates and improve safety

by rectifying current issues with the use of a simulator. Currently flight training is heavily

biased towards large commercial aircraft training requirements, and there is little aid for

small GA pilots wishing to learn to fly. GA pilots have the highest accident rate, as they have

low hours and less training. This equates to an overall lack of flying experience. Critical

operational areas that novice pilots experience are to be identified and an appropriate

alternate training method developed. The final aim is to help reduce accident rates and

improve safety. Learning outcomes were measured with the aim of improving existing

methods and safety. Finally the most efficient form of training was implemented into a

specific training scenario, with overall performance re-assessed.

4

1.4 Industrial relevance, real-world applicability and scientific impact Currently there is a massive problem in aviation, within 40 to 70 hours most pilots earn their

private pilot’s licence. After this phase students leave their instructors and enter ‘The Killing

Zone, discovered by Dr. Paul Craig a seasoned pilot, experienced flight instructor and author.

He is a long striving promoter of improving flight training and flight safety and has spoken

widely on the subject.

This killing zone is a period from 50 to 350 hours, and is widely considered a vital time in

order for pilots to gain experience for a potential future career in aviation. It is in this deadly

zone that most pilots are killed than all other periods combined. [3] If critical operational

areas that pilots regularly report problems with are scrutinised, then more effective

methods can be devised. This would benefit Flight Training Organisations (FTOs) around the

world and there is huge interest and investment in this area. Takeoff accidents have been

shown to be caused by three main categories; improper aircraft configuration, a

minimalistic approach to pilot planning and engine failure. When considered together,

takeoffs and landings only account for a very small proportion of the overall flight time, but

they are the most accident prone of any other groups by far.

Regarding real-world applicability, the project builds upon the ICAO document ICAO 9625 –

The Manual of Criteria for the Qualification of Flight Simulators. This manual describes how

simulators that represent aircraft can be used as well as outlining the recommended fidelity

requirements for specific units or elements of flight training that have the potential for

simulator involvement. [4] One of the objectives of this project is to examine the

applicability of ICAO9625 aiming to enhance the existing framework for GA pilots. Currently

ICAO9625 is a guidance document and pilots do not have to abide by it. Listed below are the

current vague guidelines towards fidelity and Flight Simulation.

• None or Not Applicable (N);

• Generic (G);

• Representative (R); and

• Specific (S). [4]

With future research it is hoped to produce an equivalent document that is mandatory for

flight training, instead of an advisory document. This will provide exact descriptions of the

fidelity level required for operations. This project builds upon the current document and

aims to enhance the existing framework for GA pilots in particular and define succinct

parameters for the application of fidelity to flight training scenarios. An interesting point to

note is that to train a pilot in the RAF, costs the taxpayer £1M each due to the depth of

training and knowledge required. Simon Maskell from QinetiQ estimated that the cost to

the taxpayer of a soldier killed in action is also around the £1M mark. Therefore if

potentially life threatening situations can be recreated with the use of a synthetic Flight

5

Simulation Device then this gives scope to applying the idea to industry. Improvements to

safety and also significant cost saving advantages are highly appealing to training providers

and flight training schools alike, in terms of improvements in training as well as the potential

reduction for loss of live giving scope to industrial applications to this project.

6

2. Literature Review

2.1 Introduction The following question will be answered in this literature review:

What research has previously been undertaken on the fidelity requirements for fixed

wing Flight Simulator training?

The use of a ‘Simulator’ is a broad generalisation of any machine that provides pilot training,

so some limitations were applied in order to narrow down the literature that is available on

this subject.

However, it must be noted that previous research in this highly specific field is extremely

limited, with respect to the training effectiveness of low cost Flight Simulation. Minimal

research has been pursued in a Flight Test environment specifically involving General

Aviation; therefore there is a reduced amount of available knowledge in the discipline but

still comparisons can be drawn between research papers.

The following limitations were applied to this literature review:

Only fixed wing aircraft

Only single piston engine aircraft

Only General Aviation simulation

Only low cost Flight Simulation Devices

Table - 1 Keywords used for research of current papers

Keywords Scopus Compendex Web Of Science

General Aviation Accidents 29(2) 52(1) 50(1)

Transfer of Training 89(3) 32(2) 62(2)

Low Cost Flight Simulation 48(3) 57(3) 58(1)

Flight Simulation in General Aviation 52(6) 91(4) 94(4)

Training Effectiveness of Flight Simulators 45(2) 62(0) 65(0)

Numbers in brackets represent the number of relevant papers applicable to the question.

7

2.2 Review of Research Papers

2.2.1 General Aviation Accidents A key factor in this project was drawing on information presented in a book entitled The

Killing Zone. The author states that pilots who currently have between 50-350 flight hours,

are more likely to be involved in a fatal accident, than other pilots with more or less

experience. The book combines NTSB accident investigation reports and statistics to provide

a compelling argument to support this theory. The author draws particular attention to

various stages of flight that this group of pilots owe particular care and attention to, due to

their varying levels of experience. [5]

It is this cohort of pilots that have the greatest accident rate and whilst there is evidence to

suggest Flight Simulator training reduces accident rates for airlines, the accident for General

Aviation has remained fairly constant over the past 25 years.

The Aircraft Owners and Pilots Association (AOPA) publish an annual report on General

Aviation accident statistics. Figure 2 shows a graph published in the 1999 NALL report. This

graph is a comparison of US GA accidents per 100,000 hours, the average rate can be seen

to be 2 accidents per 100,000 hours flown.

Figure - 2 US General Aviation Accidents [6]

8

The most recent NALL report for non-commercial fixed-wing aircraft can be seen in Figure 3.

In 2012 there were 216 fatal non-commercial fixed-wing accidents, although this is the

second lowest number in more than 30 years, the average accident rate per year has

remained relatively constant. This is in contrast to the accident rate for airlines, where there

is valid evidence to suggest simulator training compliments flight training thus lowing the

accident rate for commercial aviation. If the two graphs are compared it is evident there has

been little change to the accident rate for General Aviation over the past 38 years.

Figure 3 - NALL Report of General Aviation Accidents, 2003 – 2012 [7]

According to John Ewing, an aviation mentor, ‘The popular ways to get into trouble in a

small plane are to run out of fuel, attempt to continue VFR flight into deteriorating weather

conditions (IMC), and low-level manoeuvring flight (particularly take-off and landing). The

highest risk last year was low-level manoeuvring flight and the most likely to lead to a

fatality was continued flight into deteriorating weather.’ [5]

The report concludes, ‘The majority of accidents involve human factors or pilot judgement’.

[7]

The European Aviation Safety Agency’s more recent annual safety review shows that in

Europe there is a similar situation. Table 2 summarises these figures for European fixed wing

aircraft (under 2250kg).

Table 2 - Distribution of fatal accidents by aircraft category and operation type for the period [8]

9

The basis behind the introduction of recurrent checks for General Aviation is the same as in

civil aviation. This is the ability to expose pilots to serious emergency-type situation with the

use of a synthetic flight training device. The main use of Flight Simulation training is to

ensure the pilot is sufficiently competent in every-day aspects of flight, but the simulator

can be also used to expose a pilot to potentially catastrophic scenarios which could lead to

the loss of an aircraft and lives. Normally these scenarios cannot be safely replicated in a

real aircraft and so few GA pilots will have experienced them.

The following situations can be replicated in a General Aviation simulator, thus exposing the

pilot to:

• EFATO.

• Deteriorating weather during VFR flight conditions.

• A potential landing field divert leading to an increased pilot workload.

• Fuel management and navigation planning, for example strong tailwinds/headwinds.

• Spatial disorientation, for example when there is no obvious horizon.

• An array of potential cross-wind situations on landing.

• Incipient spin, for example on the final stages of the approach caused by a turn that was

too severe.

• Sudden wind shear on the final stages of an approach and downdraughts caused by

thunderstorms.

Allerton drew reference to an important survey, where the flight conditions involving the

loss of a Piper Saratoga at sea were replicated in a Flight Simulator at Cranfield University.

The accident details are available in NTSB identification report NYC99MA178 [9]

The report states: ‘With visibility reducing to between 5 and 8 nautical miles on a dark night,

the pilot descended from 5500 feet overland to 2200 feet over water. The pilot was non

instrument-rated and the haze conditions at the time resulted in a complete loss of the visual

horizon. The report states that the pilot became disorientated and subsequently crashed into

the sea with the loss of all occupants. The report also cites a section entitled Instrument

Flying – Coping with Illusions in Flight, from FAA advisory circular 61-27C, which states

‘spatial disorientation as a result of continued VFR flight into adverse weather conditions, is

regularly near the top of the cause/factor list in annual statistics on fatal aircraft accidents’.

A study by Barr-Gill [10] showed that pilot workload can become high during single-pilot

operations in General Aviation aircraft as a consequence of the dynamics of light aircraft.

10

Figure 4 - Visibility 8 nm over land [6] Figure 5 - Visibility 8 nm over sea [6]

These flight conditions were replicated in one of the Flight Simulators at Cranfield University.

With a visibility of 8 nautical miles over land at an altitude of 5000 feet, sufficient visual cues

are available to discern the horizon, as shown in Figure 4. However, over sea, it is impossible

to detect the horizon and the pilot is effectively reduced to IFR conditions, as shown in Figure

5. It is speculated that a significant proportion of current PPL pilots would also experience

difficulties with these conditions in a Flight Simulator, although these pilots would hope to

avoid encountering these flight conditions.

It was also noted that a simulator exercise to demonstrate the seriousness of this situation

might provide more of a deterrent to pilots than a pamphlet or a paragraph in an advisory

circular.’ [6]

This statement is an important point to note, as running a simulator exercise of this kind

would be cheap and economical for flight schools to operate on a large scale basis as part of

a PPL or CPL training program. For any pilot who experiences this exercise, the

complications of entering IMC without the proper training or experience would be

reinforced in any pilots’ mind more than a simple paragraph of information.

In reference [11] Bruckhart studied a group of pilots, and concluded that accident rates

could be reduced by 40% after simulated exposure to potentially fatal scenarios was

increased as part of a flight training programme. [11]

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2.2.2 Transfer of Training Although Flight Simulators are widely accepted as valid training tools in the aviation

industry, people continue to raise doubts as to their limitations in the so called transfer of

learning. It has been established that modern Flight Simulators are most useful as

procedural trainers, this enables pilots ‘to be trained with verisimilitude of simulation and

transfer effectiveness’ [12] theoretically enabling them to fly a real aircraft.

In a recently published discussion paper by The Royal Aeronautical Societies Flight

Simulation Group, The impact of Flight Simulation in aerospace, it was stated that ‘The

effectiveness of a training task is the ‘training transfer’ resulting from training in a synthetic

device compared with that in an aircraft, often measured as the ratio of the number of hours

of airborne training that can be replaces with training in a simulators. Studies have shown

that, for certain tasks, high levels of training transfer can be achieved with low-fidelity

training devices.’ [13]

In reference [14] Roessingh conducted a study on the Transfer of Manual Flying Skills from

PC-Based Simulation to Actual Flight—Comparison of In-Flight Measured Data and Instructor

Ratings.

The results of the average performance score (%) between group (a) – the control group and

group (b) – all groups are shown in Figure 6.

The author reported that they ‘Analysed learning curves—on the basis of in-flight recorded

data—of three different groups that received training in manual flying skills (aerobatics).

Each group was subjected to a different type of ground training preceding each flight lesson,

that is, no simulation for the C group, standard PC simulation for the S group, and PC

simulation with extra features for the X group. The accuracy of flight profiles for all aerobatic

manoeuvres was analysed, during 189 flight lessons (all flight lessons except the first

introductory lesson for each trainee) on the basis of 25 predefined criteria for the

manoeuvres to be flown in terms of altitude, acceleration, speed, roll angle, pitch angle, and

heading. All three groups demonstrated a comparable level of skill at the beginning of the

training and comparable progress per lesson of approximately 3% per lesson of the

maximum attainable score. Despite the 500 min extra ground training of the S and the X

group, no significant increments or decrements in the level of manual flying skills were found

as a result of the skills that were acquired with the simulation on the ground. Thus, there

was neither negative transfer nor positive transfer of manual flying skills learned during the

simulation lessons.’ [14]

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Figure - 6 The top graph (a) depicts the in-flight learning curve for the control group extracted from the in-flight

data recordings and averaged over trainees and manoeuvres. Error bars represent the standard deviation in

the score per lesson for the control group. The bottom graph (b) depicts these in-flight learning curves for all

three groups: the control group (C), the standard PC group (S), and the extra PC-configuration group (X). [14]

This is an interesting point to note, as it reiterates the use of Flight Simulation Devices as

purely procedural trainers. This is reflected by their extensive and continued use in the

airline industry as a means to teach procedural skills. However, it has also been proven that

FSD’s are useful as a means to teach perceptual-motor skills, but there is little evidence of

this in Roessingh’s findings, thus highlighting the need for continued research. In reference

[15] Kirlik et al. ‘Highlighted the importance of training via exposure to concrete, situational

patterns in the task environment thus allowing for optimal transfer of learning.’ [15],

Therefore for this research task the level of manual flying skill achieved by the trainee pilots,

was kept independent towards any potential for the transfer of training towards a low-cost

Flight Simulation Device.

13

2.2.3 The General Aircraft Flight Simulation Device

2.2.3.1 The Flight Simulation Device (FSD)

In the conference paper, The Research on the General Aircraft Flight Simulation Device, the

authors critically analyse the in depth knowledge required behind building an FSD. This

proved to be crucial background reading for any project, as an FSD cannot be improved if

the processes behind its creation are not fully understood.

The FSD is primarily used to simulate the aircraft’s real-time flying environment and motion

state in various flight conditions. It is composed of the computer simulated cockpit, the

sound system and the visual system [16]. The Flight Simulation Device plays an

indispensable role in pilot training courses. Its key benefits include having low-energy power

consumption, high efficiency, high economy, and above all safety. As training with a Flight

Simulation Device is not limited by the training field or the weather condition [17], this

makes it an ideal tool for cultivating aeronautical staff, both the General Aviation staff and

special operation staff in the utilisation of a Flight Simulation Device in training courses. [18]

The composition of the FSD is discussed in detail in the following theory section.

2.2.4 The Role of Flight Simulation in Pilot Training

2.2.4.1 Commercial Simulator Training

ATPL training has strict regulations including simulator integration as part of a flight training

program, and the flight crews undergo recurrent checks every 6 months. Flight crews are

able to practise emergency drills and likely scenarios they may encounter can be reproduced

in a safe environment. The aim is to prepare crews for all eventualities in the hope that

should these skills ever be required, flight crews will have had the highest level of training

possible and so will be able to react accordingly and handle the situation with an increased

level of safety.

These simulators are exact replicas of the aircraft, with identical flight management

systems, avionics and displays. The level of fidelity in these so called ‘Level-D’ simulators is

noteworthy as the aircraft dynamics, motion systems and visual systems are almost identical

to flying the real aircraft. In order to ensure these simulators conform to the international

standards of fidelity, they are closely regulated by the airlines as well as the aviation

regulatory authorities. [6]

2.2.4.2 General Aviation Training

As previously mentioned, General Aviation has a very different approach to pilot training. It

is centred upon an almost historic flight training syllabus and has no simulator integration as

part of a standard course. A key point to note is that simulator training in the GA sector has

been limited to instrumental procedural trainers, usually used for IFR training. This includes

ILS approaches and various other navigational approaches incorporating navigational aids.

14

Simulators are not usually incorporated into a PPL’s flight training course, except for

procedural work, but it is important to note this is entirely voluntary as pilot qualification is

ultimately determined by the hours flown.

In the paper, The Case for Flight Simulation in General Aviation, Allerton noted that there

have been a few instances where instrument flight trainers have been accepted ‘Based on a

credits scheme, amounting to recognition of a few hours Flight Simulator training as the

equivalent of airborne training.’ He also noted that ‘Unlike airline pilots, licence renewal is

mainly based on hours flown rather than an assessment of piloting skill.’ This means that

unlike ATPL training very few pilots, if any, actually receive any simulator training as part of

a PPL or CPL course as there is no requirement for it from the regulating aviation

authorities. [6]

Table 3 summarises the various types and numbers of pilots licence issued worldwide, thus

reflecting differences in approaches to simulator training across the globe.

Table - 3 Pilot Licences Issued Worldwide [6]

Region PPL CPL ATPL

Europe 162 600 (67%)

35 200 (15%)

43 450 (18%)

North America

374 290 (58%)

133 250 (20%)

140 940 (22%)

Other 114 000 (47%)

72 850 (30%)

56 800 (23%)

Total 650 890 (58%)

241 300 (21%)

241 190 (21%)

Allerton also drew conclusions from these figures, based on ICAO data for 1997 [19], stating that

in Europe, less than one in five pilots holds an ATPL licence. In other words, over 80% of pilots

receive no simulator training or checking, whatsoever. The situation is similar for the number of

new licences issued per year. Table 4 shows the number of licences issued between 1990 and

2000 in the UK, for the different categories. [6]

Table - 4 Pilot Licences Issued in the UK between 1990 and 2000 [6]

PPL CPL ATPL

34 512 (65%) 11 650 (22%) 6 729 (13%)

A critical evaluation of these figures shows that 87% of General Aviation pilots trained in the UK

in the last 10 years will have received no Flight Simulator training. Allerton concluded that if a

potential 18 simulators were operated for only 40 hours per week, these could provide 10 hours

of training for the 3500 PPL pilots (approximated) trained annually in the UK. [6] This is an

important observation, as it provides a realistic view towards promoting the use of low Flight

Simulation in the General Aviation sector.

15

2.2.5 Training Effectiveness Flight training devices have been utilised for pilot training for over 70 years. Due to rapid

advancements in computer technology and microprocessors, simulation technology has

improved dramatically and the benefits of simulation have become accepted by airlines and

military organisations. During this time a number of studies have been lead into the

effectiveness of training.

In reference [6] Allerton observed that there is still ‘No substantial body of knowledge to

predict or measure the effectiveness of flight training devices’. Therefore, conducting

measurements in order to determine an FSD’s effectiveness proved a challenge during this

research project. This is due to;

• ‘The only method to measure training effectiveness is to conduct a series of trials

comparing the performance of sets of subjects who are given simulator training with

equivalent sets of subjects who receive no simulator training.

• Training effectiveness can be measured in terms of the quality of training or in terms of

cost effectiveness, typically the financial savings accruing from transferring the training from

an aircraft to a synthetic training device.

• It is impractical to use commercial Flight Simulation facilities in research programmes. At

the same time, the cost of simulation facilities has discouraged the participation of

universities in research programmes.’ [6]

Allerton also observes that due to this apparent lack of understanding of the application of

simulation, a resultant emphasis on simulator fidelity has been relied upon in airline

simulation. It is also noted that this simulator fidelity ‘requirement’ is often independent of

cost or training benefit, as there is an assumption that training effectiveness is directly

proportional to the cost of a simulator, despite any evidence to support this statement.

Therefore, there is resistance to adopt low-cost training devices which is reinforced by an

apparent lack of understanding on the subject. Figure 7 shows a graphical representation of

the fidelity vs. cost dilemma. In reference [20] Duncan stated it is evident that with ever

increasing investment, fidelity can only be improved to a certain point. Where after one can

expect a reduction in return in performance of the simulation device.

Figure 7 - A graphical representation of the fidelity versus cost dilemma [20]

16

2.3 Discussion of Future Research Opportunities Research was also conducted in order to identify potential future research opportunities.

Tau theory came about when trying to work out how pilots manage to judge their approach

to the runway or even round an obstacle e.g. low flying. Somehow they need a certain

capacity in order to judge and anticipate their future path in the aircraft. Critically when

flying low level, pilots need to make continuous adjustments in speed, height and heading.

M. Jump found coherent tau relationships. ‘Pilots used the same constant rate of change of

tau strategy to perform approach and landing manoeuvres’, he reports. ‘They can 'tau'

down onto the runway visually or using cockpit instrument displays.’ [21]

This built on the survey paper The tau of flight control [22], in which the author proposes a

new ‘Tao’. This is a new concept and understanding of how pilots reach what they want to

achieve with an aircraft. Tau is suggested as being based on the ‘time to close on a goal, or

close a gap τ(t).’ This project has the potential to build on the initial hypothesis of τ-theory

whilst utilising Flight Simulation methods. [22]

Figure - 8 Example tau-coupling hypotheses for approach and land manoeuvre [23]

In reference [23] Jump proposes a hypothesis combining a ‘Strategy of tau coupling between

the perceived distance to the landing point (DL) to some distance ahead of the landing point

(DR’) is used.’ This is applicable in the final stages of the approach when an aircraft goes

through the stage of flare and landing. Figure 8 considers the slant range and angle required

for tau-coupling.

‘It should be noted that, at this stage, the actual visual ‘cues’ used to close the gaps are not

in themselves under investigation. In a good visual environment, there are likely to be a

variety of components in the optical flow field providing a degree of redundancy, and

therefore sources for taucoupling, to the pilot.’ [23]

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2.4 Closure In answer to the question ‘What research has previously been undertaken on the fidelity

requirements for fixed wing Flight Simulator training?’ the literature review affirms that

there has been widespread research conducted towards the use of large scale Flight

Simulation Devices in the airline industry. However, there have been few research

programmes investigating the application of low cost synthetic training devices towards the

General Aviation industry.

The paper The Case for Flight Simulation in General Aviation [6] is the most significant study

to date and therefore the most applicable and influential paper to this research project. The

author critically analyses this specialist field and summarises ‘The application of synthetic

training in General Aviation lags some twenty years behind other sectors. If the benefits of

simulation, which have been so successful in airline training, could be applied to General

Aviation, then there are enormous potential improvements in the quality of training and in

aviation safety, by exploiting the advances afforded by computer technology. However, this

approach to flight training needs to be supported by objective studies to quantify these

benefits and, more importantly, to establish the limitations of synthetic training, particularly

in areas where the use of Flight Simulation results in negative transfer of training.’ [6]

Therefore, it is important that progress is made in this area with the overall aim of reducing

the accident rate for General Aviation. This is due to a general lack of understanding of the

subject and also inconsistencies in findings of particular research papers, for example in

reference [14]. Here it was concluded that neither negative nor positive transfer of flying

skills could be proven as a result of simulated lessons, thus reiterating the need for

continued research into this specialised field and highlighting opportunities for potential

future research.

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3. Theory

The focal aim is to research and identify the effectiveness of current training on specific

scenarios, and to measure the learning outcome. Once this is achieved, improvements can

be made to existing methods thus improving overall safety. As an end result a pilot’s

chances of making it through the Killing Zone are increased - theoretically. An initial

prognosis suggests that that safety amongst pilots with between 50-350 hours can be

increased through the use of Flight Simulation. This is achieved by scrutinising problematic

areas novice pilots routinely experience problems with, and improving existing flight training

methods, through the use of Flight Simulation.

3.1 The Flight Simulation Device

3.1.1 The Composition of the FSD In reference [18] the authors note that although most FSDs have their own individual

system structure, they still have the similar overall basic framework and system components

in common. An abridged version of a FSD’s key systems is as follows;

‘The aircraft flying dynamics simulation system

The aircraft flying dynamics simulation system is a critical system in the FSD, not only

because it is the most important part to ensure the simulation resemblance, but it also acts

as a data source to drive other systems.

The visual simulation system

The visual simulation system can provide spatial positions, flying environments and

battlefield data for the pilot. According to statistics on flight-simulation-practice relative

importance for dynamic or visual simulation, the more manoeuvrable the aircraft is the

better visual simulation system is needed.’ [18]

John Cox, a retired airline captain with U.S. Airways and experienced safety advisor,

explained that;

‘Takeoff and landing are when the airplane is in closer proximity to the ground. Additionally,

this is when the speed is slower, more manoeuvring is occurring, and there are more

airplanes in the airspace.

According to Boeing statistical studies, 16% of fatal accidents occur during takeoff and initial

climb, while 29% occur during the approach and landing.’ [24]

Therefore it must be noted that for non-military aircraft, especially with respect to General

Aviation, the visual simulation is far more important in simulating the correct fidelity for the

takeoff and landing phase of flight.

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‘The computer simulation system

The computer simulation system plays an essential role in the FSD. Its main purpose is to

calculate the models of the aircraft dynamics system and other systems, as well as manage

and control the flying simulation system.

The aircraft acceleration and overload simulation system

This system is used to simulate the effect of aircraft acceleration and overload system. It

needs to provide a simulated movable cockpit based on the multi-degree-of-freedom motion

platform.

The sound and noise simulation system

The sound and noise simulation system is a key part of any FSD as it is vital in increasing the

fidelity of the simulation system.’ [18]

3.1.2 The Mathematical Model of the FSD ‘All flying functions implemented by the simulation system need to build corresponding

mathematical models, based on which the software is developed, and they connect to each

other by the system controlling software.’ [25] The authors of The Research on the General

Aircraft Flight Simulation Device noted that that for all simulators, the mathematical models

involved were; the aircraft flight dynamics and motion model, the aircraft system simulation

model and the environment simulation system model. These models are shown below in

Figure 9. Here both the environment and aircraft motion model are included as part of the

overall mathematical model. [18]

Figure 9 - The Mathematical Model of the FSD [18]

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3.2 The Flight Model Components In the paper PC Based High Quality and Low Cost Flight Simulator [26] the components of

the flight model are described; this is shown below in Figure 10. The importance of the

Equation of Motion is summarised below. As this system had already been created for the

simulator, it is not required knowledge but it is still useful information and an abridged

version is presented below.

Figure 10 - Components of the Flight Model [26]

‘The most important block is the Equation of Motion. It works out the flight state according

to the summation of forces and moments acting on the centre of gravity of the simulated

aircraft (A/C). The forces and moments come from various source. Firstly, aerodynamic

coefficients are defined in the Aerodynamic Coefficients block as functions of the flight state

of the A/C including such as Mach number, angle of attack, angle of sideslip, true airspeed,

and geometric characteristics of the aircraft. The geometric characteristics of the aircraft

include such as control surfaces deflections, high lift devices, landing gear, and centre of

gravity location [27].’ [26]

Appendix B provides detailed descriptions of some model building methods, including the

mathematical integration of the Equations of Motion.

21

4. Design

4.1 The Flight Simulation Device (FSD) The synthetic Flight Simulation Device used was a Piper PA-38-112 Tomahawk simulator,

registration G-LFSD. On September 9th 2006, this aircraft was involved in a crash at

Hawarden airport due to a heavy landing caused by wind shear on the final stages of the

approach to Runway 21. This resulted in the aircraft being written off and donated to the

FlightLab at The University of Liverpool.

Appendix A contains a CAA published chart for Hawarden Airfield, this site of the crash. The

approach to Runway 21 can be seen in the northern sector of the chart, with the arrow

dictating the approach made to the runway on the day of the crash.

Since then, the aircraft shell has been converted into a low fidelity, low cost FSD for

University research purposes. Work began on G-LFSD in the summer of 2011 to convert it to

a static simulator. At present the simulator offers the primary flight controls of pitch, roll

and yaw as well as controls for flaps, trim, throttle and mixture. A new radio stack has been

installed but it not yet functioning. This is the next stage of construction, as well as the

integration of a full instrument panel into the simulator and the improvement of the wrap

around visuals.

The FSD runs the Flight Simulation software X-Plane 9 in conjunction with an instructor’s

station. This allows research into low fidelity procedural work to be carried out at low cost,

making it an ideal device for the testing and evaluation of current and experimental flight

training methods. As part of the project the simulator has been upgraded with the addition

of 4 screens giving a 180’ field of view for the pilot.

Figure 11 shows the aircraft after conversion to a basic FSD with the main forward view

displayed on a TV screen and one of the 4 additional screens visible.

22

Figure 11 - The Flight Simulation Device

During initial testing, it was discovered that the FSD has a number of limitations in its design,

due to it being such a low cost, and hence low fidelity device as visible in Figure 11. These

will be discussed in the limitations section.

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4.2 The Inertial Measurement Unit (IMU) In order to measure the effect prior training on a synthetic simulation device has on pilot

performance, an IMU was integrated into a Flying School aircraft. This IMU is an entirely

separate project, but the overall aim was to develop a low cost flight data recording pack

that can be used in support of on-going final year project Flight Simulation and modelling

projects.

Flight modelling and simulation projects typically require access to Flight Test data in order

to carry out model validation studies to provide confidence in the use of the model for

research. Data sets can be sparse, especially for General Aviation (rotary and fixed wing)

aircraft as well as vintage aircraft. These aircraft feature in current research and in order to

provide the data for these projects, this project aimed to develop a low cost solution to

flight data acquisition. The student used existing hardware and also carried out a review of

emerging hardware including tablet based applications in order to develop this capability.

The project also examined the feasibility of application of the kit to other areas e.g.

UAV/Model testing, this makes it an ideal tool for verifying the effect synthetic simulation

has on pilot training.

The IMU project was started by using an existing Inertial Measurement Unit, webcam and

laptop. The fabrication of a power supply was incorporated into the feasibility of using a

Raspberry Pi (£75), mini IMUs (£50), draw wire sensors or optical displacement

measurement was also examined. The device is show in Figure 12.

Figure 12 - The low cost Inertial Measurement Unit

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5. Experimental Method

5.1 Stage 1 – Aircraft Model Development The aircraft model used on the simulator was created with the use of the development

software, FlightLab. ‘FlightLab is a flight vehicle modelling and analysis tool developed by

Advanced Rotorcraft Technologies that allows users to interactively produce models from a

library of modelling components. This is achieved by arbitrarily selecting the modelling

components, interconnecting them into a custom architecture, and assigning aircraft specific

data to the parameters of these components.’ [28]

Figure 13 - FlightLab Model Editor (FLME) [28]

Figure 13, shows the FlightLab Model Editor (FLME). It is this program that was used to edit

the X-Plane PA38-112 flight model used in the research project.

25

5.2 Stage 2 – Simulator Testing

5.2.1 Development of Standard Training Profile During Stage 1 testing, two candidates were used during this preliminary period in order to

develop a suitable training plan for the PA38-112 simulator. Each candidate was a first year

pilot studies student and had; 10 hours of previous flight time, completed at least a single

landing without instructor input and had not previously flown in the visual circuit. The

training profile developed is shown in Appendix B. The purpose of developing this briefing is

to ensure all candidates receive the same technical briefing with regards to how the visual

circuit should be flow. This training plan was then approved by an instructor from Liverpool

Flying School in order to ensure it confirmed to the standard PPL syllabus.

5.2.2 Simulator Integration As the FSD runs X-Plane 9.0, it is equipped with an X-Plane 9 instructors station used for

flight monitoring and control. Therefore, a vast array of variables can be recorded with each

flight as can be seen in Figure 14. Times, Joystick ailerons/elevators/rudders,

Pitch/roll/headings, Throttle command and Landing gear vertical force data sets were

selected for this project.

Figure 14 – X-Plane 9 data selection panel

26

When developing the experimental test method, it must be noted that exact defined

parameters are required in order to lower the general factors. When analysing stages of

flight, there many variables that must be either eliminated or kept constant throughout, in

order to ensure the reliability of the experiment. These are as follows;

Pilots must be up to circuit standard and have received the prior ground school

briefing from Liverpool Flying School Instructors.

Only the visual circuit was examined. This covers Exercises 12 and 13 in the PPL flight

training syllabus as shown in Figure 15.

A standard training profile for flying the circuit was briefed to each pilot before the

exercise (Appendix C).

Figure 15 shows a cross-sectional view of the standard left-hand visual circuit PPL students

were expected to perform, after the standard training profile had been briefed to each

candidate.

Figure 15 – Cross-sectional view of the visual circuit [29]

The visibility conditions used for simulated flight experiments are shown below in Table 4.

Table 4 - Visibility conditions used for simulated flight experiments [23]

27

During this stage of testing, the simulated weather was set to CAVOK and the visibility

condition was V1. As can be seen from Table 4, V1 sets a visibility of unlimited in daylight

conditions with no cloud coverage; this is regarded as the ‘Baseline condition’.

CAVOK is defined as:

‘Ceiling and Visibility are OK; specifically,

(1) There are no clouds below 5000 feet above aerodrome level (AAL) or minimum sector

altitude (whichever is higher) and no cumulonimbus or towering cumulus;

(2) Visibility is at least 10 kilometres (6 statute miles); and

(3) No current or forecast significant weather such as precipitation, thunderstorms,

shallow fog or low drifting snow.’ [30]

Runway 27 was the active runway incorporating a left hand visual circuit. The 2D forward

view is shown in Figure 16.

Figure 16 – Pilots forward view from the FSD

Each simulated flight was recorded using the X-Plane Instructors station. A real-time visual

plot of the aircraft track can be displayed. From this display, various aircraft parameters

were altered, these include heading, altitude, speed and position, as shown in Figure 17.

28

Figure 17 – X-Plane 9.0 Instructor station view

5.2 Stage 3 – Aircraft Testing As Allerton noted ‘The only method to measure training effectiveness is to conduct a series

of trials comparing the performance of sets of subjects who are given simulator training with

equivalent sets of subjects who receive no simulator training.’ [6]

Therefore, measurements also needed to be taken whilst the pilot was flying a real aircraft

in order to record the flight profile. Initially it was intended to use the Chief Flying

Instructors’ GPS unit, a Garmin Aera 550, but this was only available at certains times

consiquently limiting the time available for testing. These units cost in excess of £800, thus

rather exceeding the budget for this project.

It was decided to integrate a low cost data acqistition kit into an aircraft, in order to

compare Flight Simulator and aircraft results. The aim was to develop a low cost flight data

recording pack that could be used in support of on-going final year project Flight Simulation

and modelling projects thus making it an ideal tool for use during testing.

As shown in Figure 18, the kit was trialed in a PA38-112 aircraft registration G-LFSA.

29

Figure 18 – IMU integration into aircraft

30

6. Results and Discussion In this section, the results from all simulator sessions will be presented; the aircraft Flight

Test and following simulator session will also be discussed.

MATLAB 2013b was used in order to take the outputted .txt file from X-Plane and convert it

into a usable .csv file, after which data could be plotted in order to draw comparisons

between sets of data. The full code is presented in Appendix D.

The MATLAB code shows how a .txt to .csv conversion is able to be carried out in order to

plot the flight data and also how the file can be altered to stipulate the number of simulator

input files to be processed by changing, i, in the section for n=1:i

Therefore filenames can be generated for any amount of Flight Simulator outputted text

files 'flightData_%i'

filenameTemplate = 'flightData_%i';

for n=1:1

In this example the output of running the file is;

text filename = flightData_1.txt

csv filename = flightData_1.csv

6.1 Results In total, 6 individual Flight Tests were carried out of which 5 were simulator sessions and 1

was a Flight Test in a real aircraft. The results are as follows;

6.1.1 Flight Test 1 During the first Flight Test, the weather was CAVOK (Ceiling and Visibility are OK) and time

was set to local. The aircraft was handed to the pilot at 1000ft AGL, 90kts and on downwind

to Runway 09. On handover the pilot proceeded to manoeuvre the aircraft for landing by

turning and descending onto right base. Once this was achieved, the aircraft was set up for

a standard visual approach whilst adhering to the standard PPL syllabus. Once the aircraft

had touched down and come to a stop the test was ended.

The aim of the initial test was to investigate the aspect of flight to be examined, for this

flight a single pilot was used. The flight data recorded is show below. Appendixes E and F

provide a snapshot of the raw .txt flight data and the .txt to .csv file conversion respectively.

Initially the project only looked at the landing stage of an aircraft. After Flight Test 1 this was

31

deemed too limited in terms of the data that could be collected and so other elements of

the PPL training syllabus were examined.

Figure 19 – Latitude vs. Longitude plot of Flight Test 1

Figure 20 – Altitude vs. Latitude vs. Longitude plot of Flight Test 1

32

Figure 21 – Altitude vs. Time plot of Flight Test 1

6.1.2 Flight Test 2 After the initial test was reviewed, it was established that the entire circuit should be

included in the Flight Testing phase, rather than just the final stages of the approach. The

basis behind this is described in further detail in the discussion section. This test involved

flying the complete standard visual circuit and comparisons were drawn between how

accurately pilots were able to maintain the correct altitude whilst flying the aircraft in such a

restricted and highly concentrated environment. The Altitude vs. Time plot of this sortie is

shown below in Figure 22.

33

Figure 22 – Altitude vs. Time plot of Flight Test 2, circuits 1 to 4

The instructor station was used to visualise live flight data as the sortie progressed, this is

shown below in Figure 23.

Figure 23 – Real-time instructor view of the circuit detail flown

34

It is evident that from this test, the pilot manage to fly the aircraft more accurately the more

the circuit was flown. The first circuit climbed to 1200ft, 200ft above normal circuit altitude,

with the final circuit achieving a much smoother top-of-climb averaging around the 1000ft

mark. The final circuit has been enlarged in order to show the vast improvement from the

initial circuit flown. It is evident that with increased simulator time, the procedural element

of the circuit can be vastly improved than that of a pilot who receives no prior training.

Figure 24 – Altitude vs. Time plot of Flight Test 2, final circuit

6.1.3 Flight Test 3 This test involved testing a similar pilot of equal experience and according to the flight

instructor, this pilot is of the same ability as the pilot in Test 1 and 2 and eventually Tests 5

and 6 and 7. This pilot did not have any prior simulator training and experienced problems

with the low fidelity of the FSD. The Altitude vs. Time plot of the circuits plot is shown in

Figure 25.

35

Figure 25 – Altitude vs. Time plot of Flight Test 3, circuits 1 to 4

Here, no obvious comparisons can be drawn to suggest a positive or negative influence on

the effectiveness of training. However, as the flight progressed it is evident that accuracy of

maintaining the standard circuit altitude of 1000ft AGL is shown to grow gradually worst,

this would suggest prior simulator training would improve pilot performance, as in Flight

Test 2.

6.1.4 Flight Test 4

The purpose of Flight Test 4 was to introduce the standard checks and radio calls expected

of a PPL student in their training to fly Exercise 14 - the First Solo Flight. This test was carried

out with the same pilot as in the previous Flight Test 3. These checks are outlined in

Appendix C and include the following in corresponding order; FLAG, BUMPFLIES-L and LOI

checks.

1. The FLAG check is carried out immediately after departure at 300ft AGL.

2. The BUMPFLIES-L check is carried out after the downwind radio call to air traffic

control.

3. The LOI check is carried out during flap deployment to ensure the max flap limiting

speed has not been exceeded and they have been deployed correctly.

36

The results of Flight Test 4 are shown below; during the fourth circuit (Figure 26) the aircraft

experienced a sudden loss of control due to a cog in the ‘makeshift’ design of the simulator

detaching itself from the control column. This particular circuit did not factor into the overall

evaluation but is important to note as not all tests ran perfectly each time due to the low

cost nature of the FSD.

Figure 26– Altitude vs. Time plot of Flight Test 4, circuit 1

37

Figure 27– Altitude vs. Time plot of Flight Test 4, circuit 2

Figure 28– Altitude vs. Time plot of Flight Test 4, circuit 3

38

Figure 29– Altitude vs. Time plot of Flight Test 4, circuit 4

Figure 30– Altitude vs. Time plot of Flight Test 4, circuit 5

39

From this data it is evident that initially accuracy of maintaining altitude is poor as the

altitude fluctuates between +/- 200ft but by circuit 3 this has dramatically improved. The

major factor in this test was the incident of circuit 4 where, due to no fault of the pilot, the

aircraft lost 600ft and had to be climbed back up to normal circuit altitude by applying full

power and so checks were not executed as methodically as they normally would be. This

had a detrimental effect to the final circuit, where pilot fatigue also influenced performance

due to the circuit being such a high workload environment. Therefore, it was deemed

unnecessary to carry out further testing after an hour’s circuit detail and the test was

ended.

6.1.5 Flight Test 5 This stage involved implementing the IMU into a PA-38 aircraft and devising MATLAB code

in order to process the IMU’s outputted data. The code had to be significantly altered in

order to process IMU data instead of Flight Simulator data, the complete code is shown in

Appendix F.

For this test the student pilot from Tests 1 and 2 requested ATC to fly a single standard left-

hand visual circuit from Runway 27. Due to issues associated with flying a light aircraft at a

busy international airport, the aircraft was requested at late notice to change runway to 09,

to extend its downwind leg and also to fly two right-hand circuits at the end of the

downwind leg for traffic separation. The plots of the circuit are as follows.

Figure 31 – Latitude vs. Longitude plot of Flight Test 5

40

Figure 32 - Altitude vs. Latitude vs. Longitude plot of Flight Test 5

Figure 33 – Altitude vs. Time of day plot of Flight Test 5

41

6.1.6 Flight Test 6

In the final test, it was deduced that reverse engineering the operation would prove most

useful. This meant conducting a flight in the aircraft and then replicating this flight on the

simulator with the same pilot. Here, the runway used, weather and non-standard circuits

can be replicated therefore making data comparison much more useful. This test was

conducted from runway 09 left-hand, with the inclusion of two orbits and an extended

downwind leg during the two circuits flown (as requested by ATC). The results of the final

test are shown below.

Figure 34 – Latitude vs. Longitude plot of Flight Test 6

42

Figure 35 - Altitude vs. Latitude vs. Longitude plot of Flight Test 6

Figure 36 – Altitude vs. Time of day plot of Test 6

43

6.2 Discussion

6.2.1 Discussion of Flight Testing As discussed in Flight Test 6, initially pilots were tested on the FSD and then subjected to the

real aircraft, this was an airworthy PA38-112 Tomahawk owned by Liverpool Flying School. It

was then discovered that due to the unpredictable nature of flying at an international

airport, predicting an aircraft sortie is extremely difficult. This is due to a number of factors;

Runway 09 or 27 could be used; this is often changed at last minute. This is depicted

in Figure 37, standard circuit, and Figure 38, non-standard circuit.

Due to other more high priority traffic than single engine piston aircraft flying in a

circuit, the aircraft is often asked to carry out a number of orbits at the end of the

downwind leg, as shown in Figure 39.

Also for traffic separation the aircraft is routinely asked to extend its downwind leg,

leading to the final approach commencing at 1000ft rather than the standard 700ft,

as shown in Figure 40.

Bad weather causes a pilot to fly a low level circuit; here the aerodrome must always

be kept in visual range and it is flown at 500ft. This leads to the circuit taking on an

oval pattern rather than a standard rectangular pattern at a non-standard altitude.

Figure 37 – Standard left-hand circuit [29] Figure 38 - Non-Standard right-hand circuit [29]

44

Figure 39 - Orbits due to traffic separation [29] Figure 40 – Extended downwind circuit [29]

If any one of these factors is requested by air traffic control, this has a major effect on the

standard circuit pattern expected of a student pilot. It was initially intended for the latitude

versus longitude of the pilot flying the simulator to then be compared to the same pilot

flying an actual aircraft, thus comparing how accurately a pilot can fly a visual circuit under

the same conditions.

Therefore for Flight Test 5, comparing the aircrafts lat/long track with that of its simulated

counterpart in Flight Test 4 was impossible. No accurate correlation can be drawn with

regards to training effectiveness and hence level of transfer of training that could be gained.

It was decided that the only measurable way of comparing flights was to compare the

aircrafts altitude over the time taken, this is a key point as it factors out all of the

abnormalities associated with flying a non-standard circuit at a busy aerodrome.

Figure 41 shows a comparison of real world and simulated flight data, proving that

similarities can be drawn between the Altitude versus Time plot for both scenarios. This is

an important observation as in reference [6] Allerton stated that: ‘There is no substantial

body of knowledge to predict or measure the effectiveness of flight training devices.’ Due to

the restricted timeframe of this project, only a limited amount of testing could be achieved.

This observation provides a viable backbone towards the continuation of research with

regards to measuring the effectiveness of a Flight Simulation Device.

45

Figure 41 – Comparison of real world and simulated flight data showing relationship between the Altitude

versus Time plot for both scenarios

6.2.2 The Circuit Importance During the Flight Test 2, it was decided that the entire visual circuit should be examined in

the following Flight Test phases. The basis behind this is that the circuit provides an accurate

measure of a pilot’s capability. The reason for this is that it is a summation of the most

complex parts of flight training as it encompasses half of all flying skills or aspects learned up

to that stage of flight. Finally it is a very demanding exercise due to the aircraft being flown

in such a concentrated and hectic environment of an international airport.

Therefore, only the circuit detail was prudently adhered to during future flight testing as the

most complex parts of flight training can be pieced together as one in this environment. It

was suggested by Professor Ken Edwards from the Universities Industrial Advisory Board,

that “A virtue should be made of what appears” when referring to the circuit testing phase.

46

6.2.3 Limitations Throughout the course of the project, the limitations of the simulation device were obvious

during early stage testing. As a result pilots, instructors and any other bodies involved in the

project provided feedback on any limitations they discovered.

It was immediately apparent that the weather either needed to be kept constant at CAVOK

or set to real world. Initial testing suggested that the fidelity level of the simulator in

conjunction with X-Plane was not sufficient in order to generate realistic current weather

conditions. This was reflected in the final Test Flight 6, where simulator conditions were set

to mimic the previous aircraft sortie during Flight Test 5.

As part of the Flight Testing regime, an Instructor from Liverpool Flying School was invited to

fly a standard visual circuit in the simulator, and to report back with findings on the overall

fidelity of the simulator. Figure 42 illustrates the Instructors forward 2D view on short finals

for Runway 27 at Liverpool.

The instructor reported a number of abnormalities with the simulator. These are as follows;

1. No yaw with increased or decreased power setting

2. Trim inoperative

3. Altitude visual poor and very difficult to judge altitude and position due to eye point

location

4. Cockpit transparency is not realistic

5. Flaps produce far too much drag causing a rapid decrease in speed and nose drop

6. Turn PAPI’s off so pilots rely more on the outside ‘picture’ than landing aids

Figure 42 – 2D Forward view from the pilot’s perspective

47

These limitations of the PA-38 simulator became apparent during testing. The lack of

vibration caused an overall lack of feeling for the pilot, leading to reduced fidelity. Secondly,

even though 4 extra screens had been added, the visual display is still very limited giving a

degraded field of view. This was most noticeable when pilots were required to pick a feature

and then turn the aircraft onto it; many of them misjudged this due to the lack of visual

acuity. It is fundamentally important this is rectified as it is vital to maintain excellent special

awareness at all times in the visual circuit, especially at a busy aerodrome such as Liverpool.

Thirdly, it was noted that the visual cueing of the simulator is sufficiently less than the real

aircraft, giving a noticeable deterioration on pilot performance. This is mainly due to

acceleration cues being poor. In response, there is the potential for the inclusion of motion

within the simulator. It was noted that the simulators effectiveness would improve

drastically if a motion base was added, as motion and increased visual acuity have the effect

of increasing pilot workload, hence an increased potential for more realistic results. Finally

the aircraft model has been described only as ‘partially realistic’. The model rolls too fast

when in reality the PA-38 is rather sluggish. This problem can be dealt with by altering the

model characteristics in FlightLab.

48

7. Conclusions and Recommendations In summary, the overall scope of the study has been achieved by building on the current

level of research in this specialised area, but there is still a long way to go with regards to

convincing flight training organisations and regulators alike to include simulator based

training as part of an approved PPL or CPL training programme.

The project aimed to; research the effectiveness of training for specific scenarios of flight and identify critical operational areas that pilots experience problems with during training, investigate problem areas and examine how pilots could be more effectively trained with the use of Flight Simulation, measure how much training on a simulator can benefit real-world flight training, with regards to overall safety as well as the cost saving benefit and finally enhance the existing training framework for GA pilots, building on the document ICAO9625. These aims have been achieved to a limited extent as the flight simulation device used throughout could only ever achieve a very low level of fidelity, hence results reflected this limitation. However, it is important to remember that this synthetic simulator was built for the sole purpose of promoting the research into low cost Flight Simulation Devices. Therefore, there is a trade-off between spending extortionate amounts for a high quality simulator, and simply spending enough in order to adequately train pilots for procedural work whilst increasing overall. If a medium can be found with relation to the cost versus fidelity of a synthetic General Aviation simulator, it is hoped that with future research the overall safety of General Aviation can be improved. Correct implementation is vital and lessons can be learnt from civil and military training programmes with close emphasis paid to the period following a pilot gaining their PPL or CPL, as described in ‘The Killing Zone’. The ultimate aim being to integrate simulator based training as part of a PPL course. Therefore it is vitally important that research is continued towards quantifying the effectiveness of low cost flight training devices, in order to expand the knowledge base surrounding the subject. The main observation throughout testing is that the visual cueing is rather poor; this

includes the acceleration cues and the flight model itself and it was suggested that for

further research the aircraft model should be reworked by measuring the dimensions of a

PA-38 and recreating it in The FLIGHTLAB Model Editor (FLME). This is beyond the scope of

this project and would be more applicable as another project for continuation on the

findings presented in this report.

Recommendations for future research include;

Increasing the visual acuity by installing more displays to increase the fidelity as low

cost

Adding a motion base to give the pilot a sensation of manual input force

Implementing force feedback on the controls so input can be felt rather than judged

Increasing the visual scene image quality of the flight simulation software

49

Works Cited

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[4] “ICAO9625 - Manual of Criteria for the Qualification of Flight Simulators,” [Online].

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/media/Files/AOPA/Home/Pilot%20Resources/Safety%20&%20Proficiency/Accident%20

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2014].

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[12] R. SN, “Concepts and definitions. Ch in Aviation Psychology.,” Iowa State University Press,

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platform.,” Journal of Tsinghua University (Science and Technology), vol. 8, pp. 1405-

1408, 2006.

[18] Y. Wang, C. Zhang, H. Liu and Z. Wu, “The Research on the General Aircraft Flight

Simulation,” in Third Pacific-Asia Conference on Circuits, Communications and System

(PACCS), 2011.

[19] Anon, “ ICAO Statistical Yearbook. Doc. 9180/23,” October 1999.

[20] J. Duncan, “Fidelity Versus Cost and Its Effect on Modeling & Simulation,” 2006.

[21] K. Harvey, “Like the birds & bees,” [Online]. Available:

http://www.liv.ac.uk/researchintelligence/issue30/visualguidance.html. [Accessed 10 12

2013].

[22] G. D. Padfield, “The Tau of flight control,” 2011.

[23] M. Jump and G. D. Padfield, “Tau Flare or not Tau Flare: that is the question: Developing

Guidelines for an Approach and Landing Sky Guide,” 2005.

[24] J. Cox, “Ask the Captain: Are takeoffs and landings more dangerous?,” 26 08 2003.

[Online]. Available:

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danger-takeoffs-landings/2693891/. [Accessed 15 04 2014].

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Changchun, 2009.

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[26] Z. Lei and a. L. H. Jiang Hongzhou, “PC Based High Quality and Low Cost Flight Simulator,”

in International Conference on Automation and Logistics, Jinan, 2007.

[27] C. J. Atkinson, “Development of an Aerodynamic Table Lookup System and Landing Gear

Model for the Cal Poly Flight Simulator,” 2002. [Online]. Available:

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%20Senior%20Project.pdf. [Accessed 24 04 2014].

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http://www.flightlab.com/flightlab.html. [Accessed 2013 12 12].

[29] PPL-Flight-Training.com, “Flying Circuits : Take-off, Approach & Landing,” [Online].

Available: http://www.ppl-flight-training.com/circuits-briefing.html. [Accessed 22 04

2014].

[30] “CAVOK,” [Online]. Available: http://en.wiktionary.org/wiki/CAVOK. [Accessed 09 12

2013].

[31] C. A. Authority, “ATC Surveillance Minimum Altitude Chart - ICAO,” [Online]. Available:

http://www.nats-uk.ead-

it.com/public/index.php%3Foption=com_content&task=blogcategory&id=76&Itemid=12

5.html. [Accessed 12 12 2013].

[32] B. a. F. L. Stevens, “Aircraft Control and Simulation,” John Wiley & Sons, New York, 1992.

[33] The Mathsworks, “Aerospace Blockset for Simulink,” in MATLAB USER’S GUIDE, 2005.

[34] Y. H. a. K. Boyle, Antennas: From Theory to Practice, Wiley-Blackwell, 2008.

52

Appendix A

Figure 43 - Hawarden ATC Surveillance Minimum Altitude Chart [31]

53

Appendix B Equation of Motion

‘As the core of the simulation model, the Equation of Motion affects the fidelity of the Flight

Simulation directly. So we consider many effects which influence the dynamic of the A/C,

such as Earth rotation, Earth flattening, mass of A/C altering. Although the effect on flight

dynamic due to Earth rotation is small because of low speed of normal commercial aircrafts,

they always fly across a long distance. So the Coriolis force can change their positions

largely. In addition we use quaternion instead of Euler angles to describe the A/C attitude in

order to avoid singularity. Meanwhile, we neglect the Earth’s nutation and polar motion

which affect the flight dynamic trivially.

The Equation of Motion block considers the rotation of an Earth-centred Earth-fixed (ECEF)

coordinate frame about an Earth-centred inertial (ECI) reference

frame . The origin of the ECEF coordinate frame is the centre of the Earth,

additionally the body of A/C is assumed to be rigid, an assumption that eliminates the need

to consider the forces acting between individual elements of mass. The representation of the

rotation of ECEF frame from ECI frame is simplified to consider only the constant rotation of

the ellipsoid Earth ( ) including an initial celestial longitude ( ) [32]. The translational

motion of the ECEF coordinate frame is given in (1), where the applied forces b F is in the

body frame,

Where m is the mass of the A/C, is the velocity of the A/C centre in body-axis, is the

angular velocity of the A/C with respect to (w.r.t) ECI in body-axis, is the direction

cosine matrix from ECI frame to Body frame, and is the Earth rotation rate w.r.t ECI as

The A/C position, ( ) in ECI is calculated in (2),

The angular rate of the A/C w.r.t ECEF frame ( ) which is used to calculate the attitude of

A/C in body-axis as is defined in (3),

The rotational dynamics of the body defined in body-fixed frame are given in (4),

54

Where the applied moment is and the inertia tensor I is with respect to the body origin.

The integration of the rate of change of the quaternion vector is in (5),

Now, we have listed the equations which satisfy one of the functions of the Equation of

Motion block. The next step, we need to transform these equations to Simulink model.

Fortunately, Aerospace Blockset [33] which is one of the Simulink components offered us a

ready-made model, Custom Variable Mass 6DoF ECEF (Quaternion). So we just needed to do

a little improvement on it. This is an advantage of COTS software, mature, reliable and easy

to use. Figure 44 presents the position of each equation. Equation (1) were realized in the

blocks identified by red, (2) in the green, (4) in the yellow, (3) and (5) in the light blue.’ [26]

Figure 44 - Simulink diagram of the Equation of Motion [26]

55

Appendix C Standard circuit brief for PA38-121 Tomahawk

Aircraft state; Clean On threshold 0kts Parking brake on Tasks; 1. Release parking brake, apply full power and rotate at 65kts. 2. Maintain standard climb out at 70kts. 3. Shoulder check FLAG check @ 500ft. 4. Crosswind turn at 700ft, climbing turn no more than 15’ angle of bank. 5. Level off at 1000ft applying Attitude Power Trim (APT) to then maintain 90kts. 6. Turn onto downwind and conduct BUMPFLIES-L downwind checks. 7. Using Power Attitude Trim (PAT), decent and turn onto left base applying 1 stage of flap with LOI check. 8. Turn onto finals maintaining a normal decent rate at 70kts, applying the second stage with LOI check. 9. Flare the aircraft and reduce power to idle. 10. Apply breaks to reach a stop then apply parking break. 11. End flight. Aircraft Checks FLAG Flaps Landing Light Altimeter Gear BUMPFLIES-L Breaks Undercarriage Mixture Pitch Fuel Location Instruments Engine Safety Landing Light LOI Limitation Operation Indication

56

Appendix D

MATLAB Code for analysing both Simulator and IMU gathered Data.

Code for running tests

close all; % Closes all figures

clear; % Clears all variables (DO NOT USE ‘clear all’ that clears breakpoints too)

clc; % Clears command window

drawnow; % Refeshes plots (allows figures to shut)

filenameTemplate = 'flightData_%i';

for n=1:1

filename = sprintf(filenameTemplate, n);

% Generate filename

textFilename = sprintf('%s.txt',filename);

csvFilename = sprintf('%s.csv',filename);

% Just for debug

fprintf('text filename = %s\n', textFilename);

fprintf('csv filename = %s\n',csvFilename);

% Generate csv file

ConvertToCSV(textFilename, csvFilename);

flightData = readtable(csvFilename); % Too many constants in this dataset to see plots

properly

% Run test/display function

DisplayFlightData(flightData, n);

end

57

Code for converting the simulator or IMU output file from .txt to .csv

function [] = ConvertToCSV(textFilename, csvFilename)

fid1 = fopen(textFilename, 'r');

if (fid1>=0)

% Read flight sim file

txt = char(fread(fid1).');

if (strfind(txt,'|')) % If it has the bars

% ORDER IS VERY IMPORTANT

txt = strrep(txt, ' __',''); % remove leading double underscores

txt = strrep(txt, ' _',''); % remove leading underscores

txt = strrep(txt, ',','_'); % convert commas to underscores

txt = strrep(txt, '___','_'); % convert triple underscores to singles

txt = strrep(txt, '__','_'); % convert double underscores to singles

txt = strrep(txt, '|',','); % replace | with comma

txt = strrep(txt, ' ',''); % remove spaces

% txt = strrep(txt, 13,''); % remove extra line feeds

end

fclose(fid1);

% Write to new CSV file

fid2 = fopen(csvFilename, 'wt');

if (fid2>=0)

fwrite(fid2, txt);

fclose(fid2);

end

end

end

Code for displaying the function DisplayFlightData

function [] = DisplayFlightData(dataTable, dataIndex)

DisplayFlightData_map(dataTable, dataIndex, 10*dataIndex+1);

DisplayFlightData_3D(dataTable, dataIndex, 10*dataIndex+2);

DisplayFlightData_alt(dataTable, dataIndex, 10*dataIndex+3);

end

58

Code for displaying DisplayFlightData_map

function [] = DisplayFlightData_map(dataTable, flightNumber, figNum)

figure(figNum);

% hP11 is called a ‘handle’ - it allows modification of the line later on

% using the functions ‘set’ and ‘get’

hP11 = plot(dataTable.lat_deg, dataTable.lon_deg, 'b-x');

xlabel('Latitude (deg)');

ylabel('Longitude (deg)');

grid on;

% Thicken lines

set(hP11, 'LineWidth', 2); % These names can be found in the help under ‘line properties’

% set(hP11, 'MarkerSize', 10);

% Add labels to each line

hLegend1 = legend('Aircraft track');

% Allow plot to refresh now

str = sprintf('Latitude/Longitude plot of flight %i', flightNumber);

title(str);

drawnow;

end

Code for displaying DisplayFlightData_alt

function [] = DisplayFlightData_alt(dataTable, flightNumber, figNum)

figure(figNum);

%Plotting 2D Altitude

hP31 = plot(dataTable.real_time, dataTable.alt_ftmsl, 'b-x'); % Same function as XY plot

% hold on; % Allow multiple plots

% hP32 = plot(dataTable.real_time, dataTable.alt_ftmsl + 10, 'm-.'); % For a second plot

% hP33 = plot(dataTable.real_time, dataTable.alt_ftmsl + 20, 'c-'); % For a third plot

hold off; % New plot will overwrite existing plots

xlabel('Time (s)');

ylabel('Altitude (feet)');

grid on;

% Thicken lines

set(hP31, 'LineWidth', 2);

% Add labels to each line

hLegend3 = legend('Aircraft track');

set(hLegend3, 'Location', 'SouthEast'); % Put in lower corner out of the way

% Allow plot to refresh now

str = sprintf('Altitude versus Time plot of flight %i', flightNumber);

title(str);

drawnow;

end

59

Code for displaying DisplayFlightData_3D

function [] = DisplayFlightData_3D(dataTable, flightNumber, figNum)

figure(figNum);

% Plotting 3D

hP21 = plot3(dataTable.lat_deg, dataTable.lon_deg, dataTable.alt_ftmsl, 'b-x');

xlabel('Latitude (deg)');

ylabel('Longitude (deg)');

zlabel('Altitude (feet)');

grid on;

% Thicken lines

set(hP21, 'LineWidth', 2);

% Add labels to each line

hLegend2 = legend('Aircraft track');

set(hLegend2, 'Location', 'NorthEast');

% Set 3D view angles

view([-100, 50]);

% Allow plot to refresh now

str = sprintf('3D Altitude plot of flight %i', flightNumber);

title(str);

drawnow;

end

60

Appendix D

Raw .txt Data Output

_real,_time | _totl,_time | missn,_time | timer,_time | _zulu,_time | local,_time |

hobbs,_time | __lat,__deg | __lon,__deg | __alt,ftmsl | __alt,ftagl | ___on,runwy |

__alt,__ind | __lat,south | __lon,_west |

546.15363 | 540.30151 | 540.30151 | 0.00000 | 20.64481 | 20.64481 |

383.22095 | 53.30593 | -2.83167 | 976.74255 | 951.57733 | 0.00000 |

966.48169 | 52.00000 | -4.00000 |

546.35950 | 540.49695 | 540.49695 | 0.00000 | 20.64486 | 20.64486 |

383.22095 | 53.30592 | -2.83181 | 976.51978 | 951.26868 | 0.00000 |

966.26019 | 52.00000 | -4.00000 |

546.55194 | 540.69891 | 540.69891 | 0.00000 | 20.64491 | 20.64491 |

383.22095 | 53.30590 | -2.83196 | 976.35889 | 951.01843 | 0.00000 |

966.08600 | 52.00000 | -4.00000 |

546.75543 | 540.90308 | 540.90308 | 0.00000 | 20.64496 | 20.64496 |

383.22095 | 53.30589 | -2.83211 | 976.33411 | 950.90302 | 0.00000 |

966.04926 | 52.00000 | -4.00000 |

546.94873 | 541.09558 | 541.09558 | 0.00000 | 20.64501 | 20.64501 |

383.22095 | 53.30588 | -2.83225 | 976.43054 | 950.94244 | 0.00000 |

966.13586 | 52.00000 | -4.00000 |

547.15131 | 541.30048 | 541.30048 | 0.00000 | 20.64506 | 20.64506 |

383.22095 | 53.30587 | -2.83240 | 976.64240 | 951.16882 | 0.00000 |

966.33948 | 52.00000 | -4.00000 |

547.34808 | 541.49432 | 541.49432 | 0.00000 | 20.64511 | 20.64511 |

383.22095 | 53.30585 | -2.83254 | 976.92535 | 951.46588 | 0.00000 |

966.61566 | 52.00000 | -4.00000 |

547.55212 | 541.70117 | 541.70117 | 0.00000 | 20.64516 | 20.64516 |

383.22095 | 53.30584 | -2.83269 | 977.28076 | 951.83716 | 0.00000 |

966.96851 | 52.00000 | -4.00000 |

547.74500 | 541.89191 | 541.89191 | 0.00000 | 20.64521 | 20.64521 |

383.22095 | 53.30583 | -2.83283 | 977.64935 | 952.22095 | 0.00000 |

967.33240 | 52.00000 | -4.00000 |

61

Appendix E

Raw .txt to .CSV Conversion

real_t

ime

totl_t

ime

missn

_time

timer

_time

zulu

_tim

e

local

_time

hobbs

_time

lat_d

eg

lon_

deg

alt_ft

msl

alt_ft

agl

on_r

unwy

alt_in

d

lat_s

outh

lon_

west

546.1

5363

540.3

0151

540.3

0151

0.000

00

20.6

4481

20.64

481

383.2

2095

53.3

0593

-

2.83

167

976.7

4255

951.5

7733

0.000

00

966.4

8169

52.0

0000

-

4.00

000

546.3

5950

540.4

9695

540.4

9695

0.000

00

20.6

4486

20.64

486

383.2

2095

53.3

0592

-

2.83

181

976.5

1978

951.2

6868

0.000

00

966.2

6019

52.0

0000

-

4.00

000

546.5

5194

540.6

9891

540.6

9891

0.000

00

20.6

4491

20.64

491

383.2

2095

53.3

0590

-

2.83

196

976.3

5889

951.0

1843

0.000

00

966.0

8600

52.0

0000

-

4.00

000

546.7

5543

540.9

0308

540.9

0308

0.000

00

20.6

4496

20.64

496

383.2

2095

53.3

0589

-

2.83

211

976.3

3411

950.9

0302

0.000

00

966.0

4926

52.0

0000

-

4.00

000

546.9

4873

541.0

9558

541.0

9558

0.000

00

20.6

4501

20.64

501

383.2

2095

53.3

0588

-

2.83

225

976.4

3054

950.9

4244

0.000

00

966.1

3586

52.0

0000

-

4.00

000

547.1

5131

541.3

0048

541.3

0048

0.000

00

20.6

4506

20.64

506

383.2

2095

53.3

0587

-

2.83

240

976.6

4240

951.1

6882

0.000

00

966.3

3948

52.0

0000

-

4.00

000

547.3

4808

541.4

9432

541.4

9432

0.000

00

20.6

4511

20.64

511

383.2

2095

53.3

0585

-

2.83

254

976.9

2535

951.4

6588

0.000

00

966.6

1566

52.0

0000

-

4.00

000

547.5

5212

541.7

0117

541.7

0117

0.000

00

20.6

4516

20.64

516

383.2

2095

53.3

0584

-

2.83

269

977.2

8076

951.8

3716

0.000

00

966.9

6851

52.0

0000

-

4.00

000

547.7

4500

541.8

9191

541.8

9191

0.000

00

20.6

4521

20.64

521

383.2

2095

53.3

0583

-

2.83

283

977.6

4935

952.2

2095

0.000

00

967.3

3240

52.0

0000

-

4.00

000

62

Appendix E

GPS data processing code

% Clear existing variables and windows

clear;

close all;

drawnow;

clc;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% READ FILE - The GPS Excel file can be saved as CSV

% File to load

csvFilename = 'LFS290314GPS.csv'; % Can be anyname, or 'flightData.csv'

% Handy table access function - automatically creates ‘field names’ from

% column headings

T = readtable(csvFilename); % Too many constants in this dataset to see plots properly

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Convert/Extract GPS Times to number of hours in same day

% I.e. Zulu time in original data

% E.g. '2014-03-29T12:27:30.000Z' to 12.4583333

numRows = size(T,1);

newGPSTime = zeros(numRows,1);

for n=1:numRows

% Get string to read '2014-03-29T12:27:30.000Z'

str = T.GPSTime{n};

% Get parts of string we are interested in

hourStr = str(12:13); % '12'

minStr = str(15:16); % '27'

secStr = str(18:23); % '30.000'

% Convert to numbers

hours = sscanf(hourStr, '%i'); % 12

minStr = sscanf(minStr, '%i'); % 27

secStr = sscanf(secStr, '%f'); % 30.000

% Convert to hours

% Seconds would be nicer, but that is what the flightsim seems to output

newGPSTime(n) = hours + minStr/60 + secStr/3600;

end

% Slot back into place

T.GPSTime = newGPSTime;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% RENAME VARIABLES TO COMMON CONVENTION

% - Or you can change the table column names in the CSV to match

63

lat_deg = T.Latitude;

lon_deg = T.Longitude;

alt_ftmsl = T.Altitude_ft_;

real_time = T.GPSTime;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Plotting 2D - XY

figure(1);

% hP11 is called a ‘handle’ - it allows modification of the line later on

% using the functions ‘set’ and ‘get’

hP11 = plot(lat_deg, lon_deg, 'b-x');

xlabel('Latitude (deg)');

ylabel('Longitude (deg)');

grid on;

% [OPTIONAL] - Thicken lines

set(hP11, 'LineWidth', 2); % These names can be found in the help under ‘line properties’

set(hP11, 'MarkerSize', 5);

%set(hP11, 'MarkerFaceColor', 'k');

%set(hP11, 'MarkerEdgeColor', 'k');

% [OPTIONAL] - Add labels to each line

hLegend1 = legend('Aircraft track');

% [OPTIONAL] - Allow plot to refresh now

str = sprintf('Latitude versus Longitude plot of flight 1');

title(str);

drawnow;

% Plotting 3D

figure(2);

hP21 = plot3(lat_deg, lon_deg, alt_ftmsl, 'b-x');

xlabel('Latitude (deg)');

ylabel('Longitude (deg)');

zlabel('Altitude (feet)');

grid on;

% [OPTIONAL] - Thicken lines

set(hP21, 'LineWidth', 2);

set(hP21, 'MarkerSize', 5);

%set(hP21, 'MarkerFaceColor', 'k');

%set(hP21, 'MarkerEdgeColor', 'k');

% [OPTIONAL] - Add labels to each line

hLegend2 = legend('Aircraft track');

set(hLegend2, 'Location', 'NorthEast');

% [OPTIONAL] - Set 3D view angles

view([-100, 50]);

% [OPTIONAL] - Allow plot to refresh now

str = sprintf('3D Altitude plot of flight 1');

title(str);

drawnow;

% Plotting 2D - Time

figure(3);

hP31 = plot(real_time, alt_ftmsl, 'b-x'); % Same function as XY plot

hold off; % New plot will overwrite existing plots

xlabel('Time of day (decimal hours)');

ylabel('Altitude (feet)'); % ???

64

grid on;

set(hP31, 'LineWidth', 2);

set(hP31, 'MarkerSize', 5);

%set(hP31, 'MarkerFaceColor', 'k');

%set(hP31, 'MarkerEdgeColor', 'k');

% [OPTIONAL] - Add labels to each line

hLegend3 = legend('Aircraft track');

set(hLegend3, 'Location', 'SouthEast'); % Put in lower corner out of the way

% [OPTIONAL] - Allow plot to refresh now

str = sprintf('Altitude versus Time plot of flight 1');

title(str);

drawnow;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

65

Appendix F

Preliminary Project Specification and Gantt chart

DEPARTMENT OF ELECTRICAL ENGINEERING AND ELECTRONICS

Student Name: James Pattison Group: (e.g. EEE, MEI, CSEE): AVwPS

Supervisor: Prof. Jason Ralph Code: (e.g. HH56):H431

Proposed Assessor(s): Prof. Simon Maskell Student Reg. No.:200683406 E.Mail:

sgjpatti@liv.ac.uk

Project Title: The Fidelity Requirements for Fixed Wing Flight Simulator Training

Project Specification

A. Project Description and Methodology:

(Overall view of the project with proposed route to realisation i.e. what the project aims and objectives and

how you are going to do it?)

The aim of my project is to research the effectiveness of training for particular flight

simulation scenarios, with the objective of measuring how much training time on a

simulator can benefit real-world flight training with regards to overall safety.

In order to achieve this, I will aim to take pilots from various backgrounds, from novice

through to qualified pilot, and immerse them in various environments and measure

what the most efficient form of training would be for that particular environment.

Currently flight training is biased towards large commercial aircraft training

requirements and there is little aid for small General Aviation pilots. GA pilots have the

highest accident rate as they have low hours and less training. I wish to identify critical

66

operational areas that pilots experience problems with and how they could be

more effectively trained.

B. Project Tasks and Milestones: (indicate the tasks and milestones that should be achieved and their

expected dates) (e.g. Understanding of theory, designs of circuits, construction of circuits, software

specifications, working demonstrations etc.)

Tasks

Understanding of theory in relation to Human Factors

Relate to ICAO 9625 Manual of criteria for the Qualification of Flight Simulators

Identify units/elements of flight training to be examined in order to develop training scenario

Identify fidelity levels and associate with units/elements (Aircraft, Cueing, Environment simulation)

Milestones

Interim presentation - Semester 1 Week 4

Interim report - Semester 1 Week 11 - Aim to complete half of all work

Simulator test – Semester 1

Bench inspection – Semester 2 Week 10

Final thesis – Semester 2 Week 12

C. Project Deliverables: (Indicate what should be completed at the end of the project)

(e.g. This list should indicate what will be presented / demonstrated at the final bench inspections)

Specific learning & training targets for specific units/elements of flight training with

tailored simulator training

Guidance on appropriate fidelity requirements biasing towards GA rather than

large aircraft

Identify issues in training and tailor to training scenarios in order to improve safety

Aim to produce an effective simulator training profile to maximise training benefit

67

D. Project Rationale and Industrial Relevance.

Currently flight training is biased towards large commercial aircraft training

requirements

Improve syllabus for novice pilots in order to improve safety

GA pilots have the highest accident rate, few hours and less training

Examine applicability of ICAO9625, aim to enhance existing framework for GA

pilots

Benefit flight training schools, commercial operators & regulators

Aim to produce an effective simulator training profile to maximise training benefit

Student Signature: _________Signed on original____ Date: ___________________

Supervisor’s Signature: _________Signed on original___ Date: ___________________

Gantt chart

68

Appendix G

Revised Preliminary Project Specification and Gantt chart

DEPARTMENT OF ELECTRICAL ENGINEERING AND ELECTRONICS

Student Name: James Pattison Group: (e.g. EEE, MEI, CSEE): AVwPS

Supervisor: Prof. Jason Ralph Code: (e.g. HH56):H431

Proposed Assessor(s): Prof. Simon Maskell Student Reg. No.:200683406 E.Mail:

sgjpatti@liv.ac.uk

Project Title: The Fidelity Requirements for Fixed Wing Flight Simulator Training

Project Specification

A. Project Description and Methodology:

(Overall view of the project with proposed route to realisation i.e. what the project aims and objectives and

how you are going to do it?)

This project aims to research the effectiveness of training for particular flight

simulation scenarios, with the objective of measuring how much training time on a

simulator can benefit real-world flight training with regards to overall safety.

In order to achieve this, pilots from various backgrounds will be taken, from novice

through to qualified pilot, and immersed in various environments. Following this

measurements would be taken in order to determine the most efficient form of training

would be for that particular environment. Currently flight training is biased towards

commercial aircraft training requirements and there is little aid for small general

(GA) aviation pilots. GA pilots have the highest accident rate as they have low hours and

69

less training. Critical operational areas that pilots experience problems will be identified

and a more effective method for training will be devised in order to improve their

chances of making it through the ‘Killing Zone’

B. Project Tasks and Milestones: (indicate the tasks and milestones that should be achieved and their

expected dates) (e.g. Understanding of theory, designs of circuits, construction of circuits, software

specifications, working demonstrations etc.)

Tasks

Understanding of theory in relation to Human Factors

Relate to ICAO 9625 Manual of criteria for the Qualification of Flight Simulators

Identify units/elements of flight training to be examined in order to develop training scenario

Identify fidelity levels and associate with units/elements (Aircraft, Cueing, Environment simulation)

Milestones

Interim presentation - Semester 1 Week 4

Interim report - Semester 1 Week 11 - Aim to complete half of all work

Simulator test – Semester 1

Bench inspection – Semester 2 Week 10

Final thesis – Semester 2 Week 12

C. Project Deliverables: (Indicate what should be completed at the end of the project)

(e.g. This list should indicate what will be presented / demonstrated at the final bench inspections)

Specific learning & training targets for specific units/elements of flight training with

tailored simulator training

Guidance on appropriate fidelity requirements biasing towards GA rather than

large aircraft

Identify issues in training and tailor to training scenarios in order to improve safety

Aim to produce an effective simulator training profile to maximise training benefit

70

Student Signature: _________Signed on original____ Date: ___________________

Supervisor’s Signature: _________Signed on original___ Date: ___________________

Revised Gantt chart

D. Project Rationale and Industrial Relevance.

Currently flight training is biased towards large commercial aircraft training

requirements

Improve syllabus for novice pilots in order to improve safety

GA pilots have the highest accident rate, few hours and less training

Examine applicability of ICAO9625, aim to enhance existing framework for GA

pilots

Benefit flight training schools, commercial operators & regulators

Aim to produce an effective simulator training profile to maximise training benefit