D4.3 Simulation - the Endless Runway · [1]: “This work package will cover all aspects of the...

D4.3 Simulation Modelling and Analyses

This document contains the description of the ATM simulations that have been carried out for the Endless Runway project. It includes the scenarios that have been modelled, the simulation tools and their adaptation to the circular runway shape, and finally the simulations results and analyses.

Project Number 308292 Document Identification D4.3_Simulation Status Final Version 2.0 Date of Issue 11-04-2014

Authors S. Loth; H. Hesselink; R. Verbeek; M. Dupeyrat, S. Aubry

Organisation DLR, NLR, ONERA

Classification Public

EC DG-RTD

Contract: ACP2-GA-2012-308292- ENDLESS RUNWAY

Ref.: D4.3_Simulation_Modelling_and_Analysis

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The Endless Runway D4.3_Simulation

Document Change Log Version Author Date Affected Sections Description of Change

0.1 S. Loth 7/02/2013 All Initiation of the document structure

0.2 M. Dupeyrat 20/08/2013 §2 Scenario Definition

§3.1 Runway Scheduler

Scenarios and runway scheduler behaviour detailed

0.3 S. Aubry 28/08/2013 §3.1 Runway Scheduler Minor updates

0.4 S. Loth 26/09/2013 All additional text in some section, review comments, corrections

0.5 M. Dupeyrat 27/09/2013 All Comments answered and document reviewed.

0.6 S. Loth 29/09/2013 All Updated text for sections. Working on comments, references

1.0 30/09/2013 All Release version

2.0 H. Hesselink 11/04/2014 All Review EC + final meeting

Document Distribution

Organisation Name

EC Ivan Konaktchiev

NLR Henk Hesselink, René Verbeek, Carl Welman, Joyce Nibourg

DLR Steffen Loth, Franz Knabe, Sandro Lorenz, Paul Weitz

ONERA Maud Dupeyrat, Sébastien Aubry, Peter Schmollgruber

INTA Francisco Mugnoz Sanz, María Vega Ramírez, Albert Remiro

ILOT Marián Jez

Review and Approval of the Document

Organisation Responsible for Review Reference of comment documents Date

All 1.0 11-04-2014

Organisation Responsible for Approval Name of person approving the document Date

NLR H. Hesselink 11-04-2014

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Table of Contents

Document Change Log 2 Document Distribution 2 Review and Approval of the Document 2 Abbreviations 5

Introduction 7 1.

1.1 Scope of the document 7 1.2 Simulation and analyses overview 8

Scenario Definition 9 2.

2.1 Description of the use cases 9 2.1.1 Low wind use case 9 2.1.2 High wind use case 11 2.2 Description scenario parameters and rationales 13

Modelling and Simulation Framework 16 3.

3.1 Runway 17 3.1.1 Low wind use case 18 3.1.1.1 Single departing flight 18 3.1.1.2 Single arrival flight 20 3.1.1.3 Orchestration 21 3.1.2 High wind use case 22 3.1.2.1 Single departing flight 24 3.1.2.2 Single arrival flight 25 3.1.2.3 Orchestration 25 3.2 Terminal Manoeuvring Area 26 3.2.1 TrafficSim 26 3.2.2 TMA Simulation Concept and Simulation Tool TrafficSim 27 3.2.3 Preparation and Running the Simulation 27 3.2.4 Checking for Conflicts 29 3.2.5 Conflict Resolution 29 3.2.6 Extensible Workflow Management for Simulations 30 3.3 Ground 30 3.3.1 Taxiway Usage 30 3.3.2 Turnaround Modelling 31 3.3.3 Stand Selection 32

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Simulation results and analyses 33 4.

4.1 Runway 33 4.2 TMA 34 4.2.1 Conflicts 34 4.2.2 Capacity 36 4.2.3 Flight Distance and Duration 40 4.3 Ground 43

Conclusion 48 5.

References 50 6.

Appendix A Data extraction from the BADA files 51

Appendix B Eurocontrol Demand Data Repository – File Types 56

Appendix C Ouput files of the runway scheduler 57

Appendix D Segment and TMA Coordinates 58

Appendix E Traffic Scenario Movements 59

Appendix F Result charts 62

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Abbreviations Acronym Definition

Arr Arrival

ATM Air Traffic Management

BADA Base of Aircraft Data

DDR Demand Data Repository

Dep Departure

DLR Deutsches Zentrum für Luft- und Raumfahrt

DOW Description of Work

ER Endless Runway

EWMS Extensible Workflow Management for Simulations

ft feet

IATA International Air Transport Association

ICAO International Civil Aviation Organisation

ILOT Instytut Lotnictwa

INTA Instituto Nacional de Técnica Aeroespacial

ISA International Standard Atmosphere

kts Knots

LDL Landing Length

LFPG Paris Charles de Gaulle airport

m meter

MLW Maximum Landing Weight

NLR Nationaal Lucht- en Ruimtevaartlaboratorium

NM Nautical Mile

ONERA Office National d’Études et de Recherches Aérospatiales

s second

TAS True Air Speed

TERA the Endless Runway Airport

TMA Terminal Manoeuvring Area

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TOL Take Off Length

WP Work Package

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Introduction 1.This document D4.3 “Simulation” is part of work package 4 “ATM” of the Endless Runway project.

As described in the DOW [1]:

“This work package will cover all aspects of the operation of aircraft at the airport, including aspects concerning navigation systems. The operations include the approach and departure phase, runway operations during take-off and landing, and some basic ground movement considerations. Based on the conceptual work, simulation models will be setup, scenarios defined, simulations performed, and analysed.”

Five tasks are associated to the objectives of the WP, structured as follows:

Objective Task

Develop the operational concept for airspace and runway ops. 4.1 Airspace and Runway Operations

Develop a basic ground operation concept 4.2 Ground Operations

Define the scenarios that should be evaluated in the simulation 4.3 Scenario Definition

Setup and model the simulation 4.4 Modelling

Run the simulation, record and analyse the data 4.5 Simulation and Analyses

This document, D4.3, is based on the ATM concept presented in D4.2 [4], which was the output of Tasks 4.1 and 4.2.

1.1 Scope of the document D4.3 covers the work related to Tasks 4.3, 4.4 and 4.5 of WP4 and provides the simulation approach, the scenarios used and the analyses of the results from the ATM perspective. Specifically, the document will cover the simulation framework, required parameters, scenario data, the analyses approach and the results.

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The document will contain the simulation setup, the scenarios and the results of the evaluation. The following areas are part of the document:

Scenario Definition

• Description of the use cases • Brief description of the scenario parameters and their rationale.

Modelling and Simulation framework

• Description of the general simulation approach • Description of the simulation tools • Description of the recorded and analyzed data

Simulation results and analyses

• Presentation of obtained results

Conclusion

1.2 Simulation and analyses overview The concept of the Endless Runway should be evaluated by using simulations. In a first step it had to be checked, whether available simulations can be used and adapted to the Endless Runway idea. It turned out, that some tools can be used and some have to be developed for the project. Three different areas have been identified to be evaluated, the runway itself, the surrounding TMA and the ground movement area. For the runway a special tool was setup by ONERA to optimize the usage, the TMA was simulated with the DLR in-house solution TrafficSim and the ground area was implemented in Simmod Pro!.

The layout of the Endless Runway has been taken from the conceptual work of WP4. The runway is separated into 18 segments and there are also 18 arrival and departure routes that connect to the same number of TMA entry and exit points.

Two use cases have been worked out. A low wind situation, where all segments of the runway can be used and a high wind situation where only a limited number is available. Because of limited resources in the project, only the low wind use case has been taken for simulation as this is considered the more demanding one.

The base for the simulations is a real traffic data file for flights to and from Paris Charles de Gaulle on 1st of July 2011. By using the developed runway scheduler tool these data were processed to a get an optimized and conflict free flight plan file for the Endless Runway airport. This flight plan was then taken by the other simulation tools as an input. This approach leads to an optimized runway schedule but has the effect that TMA and ground might not operate at the optimum.

To evaluate the capacity of the Endless Runway different traffic demands have been setup. By adding virtual flights to the original flight schedule from Charles de Gaulle, traffic demands up to 2 times have been generated.

All three areas (runway, TMA, ground) have been evaluated separately by the used simulation tools. Different parameters as delays or capacity are used to get a first indication on the feasibility of the concept.

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Scenario Definition 2.DOW

Scenarios will be developed to cover various situations and conditions at the airport, to enable an evaluation of capacity and environmental aspects. A reference airport will be taken with a conventional runway, which can be used as a comparison to The Endless Runway. High and Low wind operations as well as departure/arrival peaks are foreseen as specific interesting scenarios.

In D2.2 [2], two airports categories are envisaged as potentially positively impacted by a circular runway design:

• Small seasonal airports • Large hub airports

The two categories are significantly different in terms of airport infrastructure and expected traffic demand and distribution. As examples for the categories Palma de Mallorca and Paris Charles de Gaulle have been selected. A detailed description of the differences between them can be found in [2]. Besides the different timely distribution of the traffic (seasonal and daily) also the geographic distribution of the flights is taken into consideration.

In the scope of the project it was not possible to setup complete simulations for both categories. Therefore the large hub airport (taking Paris Charles de Gaulle) was considered as the most constraining and limiting case. In addition, in order to fully use the circular runway length, a scenario with traffic flows coming from every direction was preferred.

2.1 Description of the use cases Two use cases are applicable to the operation on the Endless Runway, depending on the weather (wind) situation. In low wind conditions, the aircraft will be able to take off and land in any direction, at any position on the circle. This will allow optimizing the runway schedule based on the direction the aircraft uses in the TMA.

In high wind conditions, part of the runway will deal with cross wind exceeding the safety limits. In this use case, the runway will be separated into two parts, where wind speed and wind direction determine the length of each section and the parts of the runway open for use.

2.1.1 Low wind use case

In the low wind case, wind speed is lower than 20 kts.

On the ground, aircraft follow the taxiways in the directions authorized by the circulation map, see Figure 1, from their runway high-speed exit to their allocated gate for arrivals, and from their gate to the runway entry for departures. Figure 1 depicts the circulation map for an Endless Runway operated counter-clockwise. All directions are reversed if the runway is operated clockwise.

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Figure 1 - Circulation map for aircraft in the low wind case

On the runway, aircraft take-off and land within their allocated runway segments. Those are determined as a function of the aircraft preferred route and performances and of the other traffic.

In the TMA, aircraft can use any of the TMA entry and exit routes described in [4] and shown on Figure 2. Arriving aircraft will fly directly from their last En-Route point (or from origin airport in the case of free flight) to the allocated TMA entry point, and vice versa for departing aircraft. The TMA entry point corresponds to the first runway segment reserved for landing roll for arriving aircraft, while the TMA exit point corresponds to the last runway segment reserved for take-off roll for departing aircraft.1

1 In Figure 2 the TMA entry and exit points are named Arr00 to Arr17 and Dep00 to Dep17. Entry Point Arr00 is the first point on the arrival route that is connected to the start of runway segment 00. The same concept applies to the departures. Exit point Dep14 is the last point of the departure route that starts at the end of runway segment 14. This is valid for the anti-clockwise operation of the runway. If the direction changes to clockwise, Entry and Exit points are switched from Arr to Dep and vice versa. This is indicated by the identifiers in brackets in Figure 2.

ER low wind counter clockwise configuration

ARRDEP

Terminal A

D

Stop bar (holding position)

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Figure 2 - TMA arrival and departure routes available in the low wind case

2.1.2 High wind use case

In the high wind case, wind speed is higher than 20 kts, leading to some parts of the runway where the crosswind limits are exceeded. The runway will be split in two parts whose separation axis will correspond to the wind direction. The two runway parts operate in opposite directions, always facing the wind at one point. Runway segments joining the two parts are not allowed for operations.

On the ground, aircraft follow the published circulation map established depending on the wind direction from their runway high-speed exit taxiway to their allocated gate for arrivals, and from their gate to the runway entry for departures. Figure 3 shows the circulation map for an Endless Runway with strong North wind.

0 0102

0314

15

1617

04

09 0807

1011

1213

0605

Arr 13(Dep 13)

Dep 05(Arr 05) Arr 14

(Dep 14)

Arr 15(Dep 15)

Arr 16(Dep 16)

Dep 06(Arr 06)

Dep 07(Arr 07)

Dep 08(Arr 08)

Dep 09(Arr 09)

Dep 10(Arr 10)

Dep 11(Arr 11)

Dep 12(Arr 12)

Dep 13(Arr 13)Dep 14

(Arr 14)

Dep 15(Arr 15)

Dep 16(Arr 16)

Dep 17(Arr 17)

Dep 00(Arr 00)

Dep 01(Arr 01)

Dep 04(Arr 04)

Dep 03(Arr 03)

Dep 02(Arr 02)

Arr 17(Dep 17)

Arr 00(Dep 00)

Arr 01(Dep 01)

Arr 02(Dep 02)

Arr 03(Dep 03)

Arr 04(Dep 04)

Arr 05(Dep 05)

Arr 06(Dep 06)

Arr 07(Dep 07)

Arr 08(Dep 08)

Arr 09(Dep 09)

Arr 10(Dep 10)

Arr 11(Dep 11)

Arr 12(Dep 12)

ARP

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Figure 3 - Circulation map for aircraft in the high wind case

On the runway, aircraft take-off and land using their allocated runway segments. Those are determined as a function of the closest aircraft En-Route point, of the aircraft performances and of the other traffic. Aircraft land on the half runway on the same side as their departure airport (direction of origin) or last En Route point, and vice versa for departure aircraft.

In the air, aircraft can use the opened TMA entry and exit routes as shown on Figure 4. Arriving aircraft fly from the last En-Route point (or from origin airport in the case of free flight) to the allocated TMA entry point, from where they will reach the intermediate approach point. Then, they will continue with the arrival route that corresponds to the allocated touchdown runway segment. Similarly, departing aircraft fly on the departure route corresponding to their allocated take-off segment until the intermediate departure point. From there, they use the allocated route until the TMA exit point that will take them to their first En-Route point or straight to their destination airport in case of free flight.

ER high wind configurationARR DEP

Terminal A

Terminal C

Terminal BTe

rmin

al D

Stop bar (holding position)

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Figure 4 - TMA arrival and departure routes available in the high wind case

2.2 Description scenario parameters and rationales As a base for both use cases, existing traffic data are used. An airport that answers to the criteria of being a central hub with traffic flows coming from all direction and all fleet categories represented has been chosen: Paris Charles de Gaulle airport (IATA code is LFPG).

02

0304

07

0605

Dep 13 Dep 05Dep 14Dep 15Dep 16

Arr 13Arr 14

Dep 02

Arr 04Arr 06

04

03

0117

15

13

11

09

07

05

02

00

16

14

12

10 08

06

ARP

48°

Wind: 30 kts

Dep 04Dep 03

Intermediate approach points

Intermediate departure points

08

1415

16

11

1213

10

17 0 01

09

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The following scenario parameters are specified for the modelling and simulation of the operation on the Endless Runway.

Airport altitude: The airport is located at sea level.

Runway characteristics: The runway inner radius and width as well as the number of segments dividing the runway define the length of the runway segments and the average centreline used in the scenario modelling. According to [4], these parameters are fixed and set to respectively 1500 meters (runway radius), 140 meters (runway width) and 18 (number of segments). The runway centreline is taken at the middle of the runway width, that is to say 1570 meters from the circle centre. Knowing the runway average centreline and the number of segments, the length of each runway segment is 2𝜋×1570

18= 548 𝑚. The numbering of the segments

is depicted in Figure 5.

Figure 5 - Endless Runway segments numbering

Meteorological situation: The scene is set under standard atmospheric conditions (ISA). The wind speed is considered to determine which use case is applicable: high wind (>20 kts) or low wind (<20 kts). In the latter case, the directional use of the runway must be chosen (clockwise or counter-clockwise).

Traffic demand: Traffic demand is retrieved from the Eurocontrol s06 file, which contains flight information (callsign, aircraft model) and a few radar plots per flight of all air traffic flows over Europe. It is considered as the traffic demand for the Endless Runway simulation and can be artificially increased or decreased to evaluate capacity limits of the Endless Runway. July 1st, 2011 is used as it was the busiest traffic day of the year 2011 in Europe and departures and arrivals on LFPG are extracted. 1474 flights are accounted for that day, from 00:14 to 23:53. The maximum number of flights per hour observed is 109.

Aircraft performances: For each aircraft of the traffic sample, the following data are extracted from the EUROCONTROL Bada aircraft database ([6]):

• Take-off distance (TOL) • Stall speed in take-off configuration • Landing distance (LDL) • Stall speed in landing configuration • Wake category • True Air Speed (TAS) during climb between FL0 and FL090 • True Air Speed (TAS) during descent between FL0 and FL 030

It is assumed that arriving aircraft are loaded at Maximum Landing Weight (MLW).

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The following Table 1 summarizes the parameters previously described.

Table 1- ER scenario input parameters

Parameter category Parameter Value

Meteorological situation Wind speed 0 kts for the low wind case Strong North wind (25 kts) for the high wind case

Runway characteristics Inner radius 1500 m

Width 140 m

Average centreline 1570 m (segment length : 548 m) Runway directional use counter-clockwise

Traffic demand Extraction for LFPG airport of the s06 file for July 1st, 2011 + exp2 file

Aircraft performances Take-off length see aircraft performances Stall speed at take-off see aircraft performances

Landing length see aircraft performances

Stall speed at landing see aircraft performances

Wake category see aircraft performances

TAS during climb between FL0 and FL090

see aircraft performances and Appendix A

TAS during descent between FL0 and FL 030

see aircraft performances and Appendix A

The following Table 2 gives an example of aircraft performances data for the B747-400 aircraft.

Table 2 - Aircraft performances for the B747-400

Take-off length 3271 m Stall speed at take-off 70 m/s Landing length 1905 m Stall speed at landing 60,7 m/s Wake category Heavy TAS during climb between FL0 and FL090 See Appendix A TAS during descent between FL0 and FL 030 See Appendix A

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Modelling and Simulation Framework 3.DOW

Based on the conceptual work of the previous tasks the preparation of the simulations will be carried out by modelling the airport with The Endless Runway and by preparing the scenarios. To prepare the simulation, tools and/or analytical models will be adapted accordingly.

To transfer the Endless Runway concept developed in D4.2 [4] into a simulation framework, different approaches have been considered. At first it was planned to use Simmod PRO! for all parts of the simulation. Setting up a flight plan as input was not easily possible and had to be done with other tools. Using a fixed runway schedule as a parameter leads also to problems, as Simmod PRO! has no freedom anymore of optimizing aircraft trajectories.

It turned out that a single simulation tool cannot cover all aspects of the concept as they are significantly different from today’s airport operations. Therefore it was decided to use different tools for the different simulation aspects of the Endless Runway airport concept. As the tools are not directly interconnected to each other, all simulations need to be performed and evaluated separately. To align the simulations, a common scenario based on the Eurocontrol data was used. From the ATM perspective the following areas need to be considered

• Runway • TMA • Ground (Manoeuvring Area)

For each of the mentioned geographical areas, operational and design criteria where worked out in [4]. These criteria have been implemented in the simulation tools and modelled as close as possible to the concept. Figure 6 gives an overview of the simulation setup as it is described in more detail in the following sections.

Figure 6 – Simulation Framework setup

ConceptElements

Scenario

PerformanceParameter

SimulationTools

Results

Aircraft Data (BADA, WP 3, …)

Movement Data (Eurocontrol sO6 files)

Data Recording and Analysis

Route Structure(Arrival/Departure) Separation Runway Layout

(Segments)Segment

reservation rulesTaxiway/Stand

LayoutGround movement

concept

Runway Scheduler

Simmod PRO! (Taxi Operations)

Integrated Noise Model (INM) Traffic Sim

Flight Plan Flight Plan

Extensible Workflow Management for Simulations

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3.1 Runway For the runway part a dedicated program was developed by ONERA that is used as runway scheduler. The runway scheduler program takes existing traffic as input that is used as the traffic demand for the Endless Runway. In line with the methodology described in [4], it produces a de-conflicted runway sequence for arriving and departing aircraft.

Figure 7 - Runway scheduler chain

The runway scheduler follows these steps:

1. Recorded traffic data are retrieved from the EUROCONTROL ‘.so6’ files2, which contain flight information (callsign, aircraft model) and a few radar plots per flight of all air traffic flows over Europe for the reference simulation day.

2. Departure and arrival flights for the reference airport are extracted from the file, for the chosen timeframe.

3. Intermediate waypoints are removed, so that only the last En-Route point (or the departure / arrival airport if a direct route is possible) are kept for each aircraft.

4. Landing and take-off distances and durations are computed for each aircraft of the simulation, using Eurocontrol BADA aircraft database and according to the methodology described in [4].

5. The optimum arrival/departure points on the runway3 and the associated take-off/landing distances are used to compute requested runway segments.4

6. A requested timeframe for take-off and landing is established, starting at the departure and arrival time from the input file and lasting the duration computed in step 4.

2 The so6 files are part of the Eurocontrol Demand Data Repository, which includes a high number of different air traffic data from Europe. A list of available Data files is available in Appendix B 3 The optimum arrival/departure point on the runway is computed taking into account the optimum entry/exit point in the TMA. An aircraft going to the South will fly on a TMA departure route going to the South. With a runway in the counter-clockwise direction, this route comes from the West where aircraft lifts-off. 4 In the low wind case, buffer segments are added upwards landing segments and downwards take-off segments.

One day traffic at a European airport (EUROCONTROL s06 file)

Aircraft characterisics: -wake category -performances (BADA) => LDL, TOL, ROT

Runway segments reservation rules

Runway Scheduler

Runway sequence +

Comparative statistics

Runway parameters: Radius, number of segments

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7. The aircraft runway usage is planned sequentially, using time-shifting and space-shifting where necessary5. During this process, wake turbulence separation is applied between aircraft pairs when applicable.

Points 5 and 7 depend on the configuration of the runway, e.g. of the applicable use case. In the next paragraphs, we will detail these steps with concrete examples.

3.1.1 Low wind use case

The method adopted to simulate the attribution of the runway segments along time in the low wind use case is described in the following paragraphs. It will be assumed that there is no wind at all.

3.1.1.1 Single departing flight

Let’s consider the following A320 departure flight at an Endless Runway which is operated counter clockwise.

Type Departure airport

Arrival airport Callsign ICAO Code

Aircraft model

Wake category

Requested take-off time

at airport

First En-Route point bearing from ER airport

DEPARTURE Endless runway airport LFPG

LFBO (Toulouse Blagnac)

AF782UM A320 Airbus A320

M 09:00:50 187

The TOL and VS are extracted from the corresponding .OPF file (see Appendix A).

According to [4], the A320 take-off length on the circular runway is equal to the TOL, that is to say 2,190 metres, which corresponds to 2190

548≅ 3.9 segments, rounded to the upper integer, 4 segments. Consequently,

the additional upstream buffer (10% of this distance) is equal to 0.4 segments, rounded at one segment. 5 segments in total will be booked for this aircraft.

5 In the low wind case, if the desired segments are not available at the desired time, the program looks for the closest available ones, and if not, delays the aircraft to a later slot.

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Figure 8 - Best guess departure point on an Endless Runway airport operating counter-clockwise

The requested take-off roll end bearing being 187° (the aircraft heads south of the Endless Runway airport). Thus, the centre angle corresponding to the ideal take-off point is 187 + 𝜋

2= 277°. This corresponds to

segment (277+10)×18360

= 14, at the west. As 4 segments are requested for the take-off roll and as the runway is oriented counter-clockwise, the first segment to be reserved is segment number 14+4-1 (mod 18) = 17 (at the north). Considering the additional buffer segment, the runway will be reserved from segment 17 to 14-1=13. Then, the aircraft will fly on departure route 14 (as segment 13 is a buffer segment), heading south.

The stall speed in take-off configuration is found equal to 112.1 kts (= 57,7 m.s-1). The take-off duration is estimated equal to:

Δ𝑡 =𝑇𝑂𝐿

0,6 𝑉𝑆+ 25 =

21900,6 × 57,7

+ 25 ≈ 88 𝑠 (00: 01: 28)

Considering that the aircraft aims to start its take-off roll on the runway at 09:00:50 and that this duration includes 10 seconds to line-up from the taxiway to the runway, this means that the desired segments would ideally be booked from 09:00:40 to 09:02:18.

N

α = 187°

N

centre angle = 277°

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3.1.1.2 Single arrival flight

Let’s consider the following A340-300 arrival flight.



Aircraft model

Wake category

Requested touchdown

time at airport

First En-Route point bearing from Endless

runway airport (°)

ARRIVAL LEMD (Madrid Barajas)

Endless Runway airport LFPG

LAN722 A343 Airbus A340-300

H 15:17:22 032

The aircraft is an A340-300, whose performances are directly extracted from the A343_.OPF bada file (see Appendix A).

Its landing length on a straight runway is 1,830 metres, increased of 12.8% for the Endless Runway ([3]) to

2,064 metres, which corresponds to 112,8×1830

100548

≈ 3.7 segments. Consequently, the additional upstream buffer (10% of this distance) is equal to 0.37 segments, rounded at one segment. 5 segments in total will be booked for this aircraft.

Figure 9 - Best guess arrival point on an Endless Runway airport operating counter-clockwise

The arrival bearing being 032° until final approach (e.g. the aircraft arrives from the South-West), the aircraft will land on the segment whose centre angles includes 32+𝜋

2= 122°. This corresponds to segment number

(122+10)×18360

≅ 6. As 4 segments are requested for the landing roll and as the runway is oriented counter-clockwise, the last segment to be reserved is segment number 6-4+1 (mod 18) = 3. Considering the additional buffer segment, the runway will be reserved from segment 7 to 3.

The calculation of the landing duration needs the knowledge of the stall speed in landing configuration. It can be found in the A343_.OPF file. For the A340-300, its value is 101 kt (52 m.s-1).

N

α = 32°

N

centre angle = 122°

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Δ𝑡 =𝐿𝐷𝐿

0,65 𝑉𝑆+ 5 =

20640,65 × 52

+ 5 ≈ 66 𝑠𝑒𝑐𝑜𝑛𝑑𝑠

Considering that the aircraft aims to have landed at 15:17:22, this means that the preferred runway segments would ideally be booked from 15:17:22 to 15:18:28.

3.1.1.3 Orchestration

The requested segments and timeslots are known for all aircraft in the simulation. Timeslots might be extended if wake turbulence separation applies, e.g. when an aircraft of a lighter category aims at using the same segments as a heavier one before. In this case, the segments are booked for a longer time, between 2 and 4 minutes (ICAO wake turbulence separation minima).

Then, as described in [4], to avoid overlap in assignment of segments, the following sequential strategy is adopted.

• The first aircraft of the day gets the desired runway segments and timeframe • For following aircraft, if the required adjoining segments are not available within the preferred

timeframe, the scheduler looks for the closest available ones. If none is available, it delays the aircraft to the first available slot.

The generated traffic file shows the requested timeslots for a given section of the runway, and the attributed one, and computes the delay. The following table is an extraction of the output of the runway scheduler.

Figure 10 - Sequencing of traffic demand on the Endless Runway

It is possible to have a graphical view of the runway segments reservation over time. In the following figure, the time in the middle of the Endless Runway-radar view is the current time. The blue boxes represent the departures, the orange ones the arrivals, with a green line as the boundary of the first booked segment and a red line as the end of the last booked segment. The first black ring is at 5 minutes and the second one is at 15 min.

TypeDeparture

airportArrival airport

Other airport name CallsignICAO Code

Aircraft modelWake

categoryRFL

Closest cruise lat.

(°)

Closest cruise long

(°)

Aircraft bearing

(°)

Endless Runway segment

(assuming counter-

clockwise)

Roll length

(m)

Number of roll

segments

Number of buffer segments

Stall speed (m/s)

Initial approach

speed (m/s)

Final approach

speed (m/s)

Initial takeoff speed (m/s)

Climb speed (m/s)

First requested segment

Last requested segment

Nb segments

Booking duration

(s)

Requested booking

start

Requested booking

end

First booked

segment

Last booked

segmentDelay (s)

Effective booking

start

Effective booking

endComment

ARRIVAL EDDM LFPG Munich International Airport AFR1423 A318 AIRBUS A318 M 360 50.05361 8.63722 253 17 1528 3 1 47.8 138.1 91.6 64.2 116.4 0 15 4 54 08:59:07 09:00:02 9 6 32.689806 08:59:40 09:00:34 Follows AFR3539. Wake turbulence (H, M): 3 minDEPARTURE LFPG LFBO Toulouse-Blagnac Airport AF782UM A320 AIRBUS A320 M 350 47.585 2.29111 187 14 2190 4 1 57.7 139.5 94.4 69.2 120.8 17 13 5 88 09:00:50 09:02:18 1 15 0.0 09:00:50 09:02:18 Shifted from 17 to 1 (2-segment shifting). ARRIVAL CYUL LFPG Montreal / Pierre Elliott Trudeau AFR349 B744 BOEING 747-400 H 390 49.715 -4.62305 101 10 2148 4 1 60.7 141.1 99.8 84.0 131.6 11 7 5 59 09:01:24 09:02:24 11 7 0.0 09:01:24 09:02:24 Request granted without modificationDEPARTURE LFPG EGLL London Heathrow Airport BAW307 A321 AIRBUS A321 M 240 49.04805 2.715 72 8 2280 5 1 60.7 139.5 94.9 72.8 122.6 12 7 6 87 09:01:50 09:03:17 17 12 28.291993 09:02:18 09:03:45 Follows AF782UM

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Figure 11 - ER-radar view of booked segments along time at a busy hour

The graphical representation in Figure 11 was originally developed for passenger processes visualisation by DLR [13]. For the Endless Runway it was adapted to the presentation of the timely distribution of the flight at the runway.

Statistics are provided by the runway scheduler regarding average and maximum delay encountered by aircraft (they do not take into account TMA or taxiing constraints).

3.1.2 High wind use case

The method to simulate the attribution of the runway segments along time in the high wind use case is described in the following paragraphs. However, due to time constraints, it was not possible to implement it in the runway scheduler, nor in Simmod PRO! or TrafficSim.

We assume a strong north wind (25 kts). Therefore, the runway is operated clockwise in its western part and counter-clockwise in its eastern part.

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Figure 12 - Runway directional use with a strong North wind

The runway is now operated as a conventional, two runway airport. Thus, aircraft segments reservation only depends on aircraft landing and take-off length. The aim is to lift-off and touchdown as close as possible to headwind (on Figure 12, segments 13 and 05 for takes-offs, 14 and 04 for landings), avoiding the runway area where crosswind is too strong (segments 08 to 10 and 17 to 01) and without incursion in the protected area where both runway sides converge (segments 00 and 09). The following table, in which these principles have been applied, shows which runway segments will be booked for all possible take-off and landing lengths.

Table 3 - Correspondence between the TOL and LDL and runway segments reserved in the high wind case with a North wind

Number of segments needed

Western side Eastern side

Departure Arrival Departure Arrival

1 13 14 05 04

2 1213 1415 0605 0403

3 1113 1416 0705 0402

4 1114 1316 0704 0502

5 1115 1216 0703 0602

6 1116 1116 0702 0702

7 1016 1117 0802 0701

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3.1.2.1 Single departing flight

Let’s consider the same A320 departure flight as in the low wind case.



Aircraft model

Wake category

Requested take-off time

at airport

First En-Route point bearing from ER airport

DEPARTURE ER airport LFPG

LFBO (Toulouse Blagnac)

AF782UM A320 Airbus A320

M 09:01:00 187

The TOL was already calculated in chapter 3.1.1.1, equal to 2,190 metres, and the number of required segments for the take-off roll to be 4 segments.

Following take-off, the aircraft is heading south-south-west (bearing of 187°), which is it in the left plan of the runway. According to the principles recalled in chapter 2.1.2, this means that the aircraft will take-off on the western part of the runway. In this case, it means of course additional track in the air as the aircraft takes-offs almost in the opposite direction as desired due to the Endless Runway operating as two parallel runways facing the wind.

Figure 13 -Take-off segments and routes on the west side of the runway (strong North wind)

As only 4 segments are necessary for the ground roll, it is possible to take-off almost at headwind: take-off roll will start on segment 11 (following forbidden segment 106) and finish on segment 11+4-1mod (18) = 14 (see Table 3).

Then, the aircraft will fly on departure route 14 heading north until the intermediate departure point, and continue on departure route 15 before exiting the TMA and be authorized to head south.

As seen previously, the take-off duration is estimated equal to 88 seconds (00:01:29).

Considering that the aircraft aims to start its take-off roll on the runway at 09:01:00 and that this duration includes 10 seconds to line-up from the taxiway to the runway, this means that the runway segments would ideally be booked from 09:00:50 to 09:02:28.

6 Note that with an aircraft with a TOL covering 7 segments (maximum TOL), the take-off roll would start exceptionally on segment 10 rather than on segment 11. The formula used is changed as a consequence: an aircraft that needs 7 segments would start at segment 10 and finish on segment 10+7-1=16.

0

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3.1.2.2 Single arrival flight

Let’s consider the same A340-300 arrival flight as in the low wind case.


Arrival airport

Callsign ICAO Code

Aircraft model

Wake category

Requested touchdown

time at airport

First En-Route point bearing from ER

airport (°)

ARRIVAL LEMD (Madrid Barajas)

ER airport LFPG

LAN722 A343 Airbus A340-300

H 15 :18 :29 032

We have already calculated in chapter 3.1.1.2 the LDL, equal to 2064 metres, and the number of required segments for the take-off roll, 4 segments.

The aircraft arrives from the South West (bearing of 32°), which is it in the left plan of the runway. According to the principles recalled in chapter 2.1.2, this means that the aircraft will land on the western part of the runway. Contrary to the departing flight seen above, in this case the aircraft air trajectory is minimised as the aircraft will land South West of the runway.

Figure 14 - Landing segments and routes on the west side of the runway (strong North wind)

As only 4 segments are necessary for the ground roll, it is possible to land on segment 16-4+1=13, almost headwind: landing roll will start on segment 13 and finish on segment 16 (see Table 3).

As seen previously, the landing duration is estimated equal to 66 seconds. Considering that the aircraft aims to have landed at 15:18:29, this means that the runway segments would ideally be booked from 15:17:23 to 15:18:29.

3.1.2.3 Orchestration

The requested segments and timeslots are known for all aircraft of the simulation. Timeslots might be extended if wake turbulence separation applies, e.g. when an aircraft of a lighter category takes-offs or lands behind an aircraft of a heavier category. In this case, the segments are booked for a longer period, between 2 and 4 minutes (ICAO wake turbulence separation minima are used). Furthermore, two takes-offs using 7 segments are not allowed simultaneously.

Requested runway segments are fixed and cannot be moved contrary to the low wind use case.The following sequential strategy is adopted on each side of the runway (independent operations).

• The first aircraft of the day gets the desired timeframe. • For following aircraft, if the runway side is available within the requested timeframe, it takes-offs

or lands at the requested time. If the runway is not available during the timeframe, the aircraft will be delayed to the end of the previous aircraft timeslot.

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3.2 Terminal Manoeuvring Area Modelling of the Terminal Manoeuvring Area (TMA) can be done by different simulation tools. Based on the defined simulation framework defined in chapter 3, the DLR in-house simulation tool TrafficSim was used.

3.2.1 TrafficSim

The designed TMA concept according to D4.2 [4] has many crossings of departure and arrival routes. The runway simulation only considers the capacity and limiting requirements of the runway and the segments and does not take the actual capacity of the TMA into account. Therefore, the implementation of a fast time simulation that calculates the possible trajectory and checks the flights for conflicts is necessary.

Calculation of TMA entry and exit points

In the resultant flight plan of the runway scheduler the touch down and take off segments are shifted to get a maximum capacity. Since the aircraft must take-off and land tangentially to the runway segment, it was necessary to add significant routing points at the border of the TMA, see Figure 15. As a consequence the aircraft can´t flight a direct route but have to take a detour and overfly a TMA ENTRY or EXIT point from origin airport to the Endless Runway and the other way around.

0 01 02

03

1415

16 17

04

09 0807

1011

1213 06

05

04

0117

15

13

11

09

07

05

02

00

16

14

12

10 0806

ARP

Airport A

Optimized for flight distance

Route after segment shifting

Endless Runway Airport

Enroute Segment

ENTRY 03(9.42 NM)

EXIT 10(9.42 NM)

Figure 15 - Entry and Exit Points at TMA border

To implement the routing points for the shifted flight plan, the coordinates of the entry and exit points had to be calculated with the specified distance and bearing. As center of the circle the airport reference point of

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Charles De Gaulle Airport was defined. The exact coordinates for the segments and TMA constraint points are summarized in Table 12 and Table 13 in Appendix D.

3.2.2 TMA Simulation Concept and Simulation Tool TrafficSim

The workflow of analyzing a traffic scenario is standardized for air traffic simulations and is presented in Figure 16. The scheduled flight plan is taken as a basis and the route is defined by adding constraints and routing points. In the TMA simulation, a unique trajectory was generated without checking conflicts between aircraft. This means, each aircraft flies an optimized independent profile and doesn´t know anything about the other trajectories within the scenario. As a result of this, a high number of conflicts exist. The number of conflicts depends on the defined separation standards. A strategy for conflict resolution has to be developed, so that at the end of the simulation exercises a fully conflict free traffic scenario is implemented in the fast time simulation tool.

Figure 16- TMA Simulation Concept Workflow

The traffic scenario is implemented and simulated with the software TrafficSim developed by the DLR Institute of Flight Guidance. The simulation tool requires a flight plan, a constraint list including routes, speed and other information for each flight and the aircraft performance file (BADA 3.9) [6]. The simulation system models the aircraft performance, the environment, the pilot, as well as the controller. The use of fast time simulation makes an investigation of a huge scenario within a few minutes possible. The calculation of trajectories is based on the point-mass-model and logs the trajectory points in a file. The resulting trajectory files include position, speed, heading, fuel, etc. for each second in the simulation.

3.2.3 Preparation and Running the Simulation

To run a simulation with TrafficSim the scheduled flight plan had to be converted in a particular text file. The structure is displayed in Figure 17. The time represents the real time at the assigned segment. The type of file is defined by the ending *.scenario.

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Figure 17 - TrafficSim scenario file

For each flight a unique constraint file has to be created. For example, the routing information of the flight with the callsign AF620JL must be defined in the file AF620JL_LFPG_LFBD_16.cstr (Figure 18). The file defines all necessary information like waypoints, type of descent and type of turn. LFPG16 and EXIT16 as waypoints indicate the take-off segment and the TMA point that has to be overflown.

Figure 18 - TrafficSim Constraint file for flight AF620JL

Company Route : AF620JL_LFPG_LFBD_16 Take off Time : LFPG16 05:54:50 Cruise Flight Level : 290 Departure Airport Name : LFPG Runway Name : Segment 16 Speed Restr Alt : 10000 Transition Alt : 5000 TMA NA Lmt Alt : 2000 Runway Threshold : 183 Runway Latitude : 49.02200877 Runway Longitude : 2.533222034 Arrival Airport Name : LFBD Runway Name : LFBD Speed Restr Alt : 10000 Transition Alt : 5000 TMA NA Lmt Alt : 1684 Runway Threshold : 364 Runway Latitude : 44.82833333 Runway Longitude : -.7155555555 Descent Specification Descent Kind: Continuous_Descent Start Of Steep Descent : 0 Intercept Alt : 4000 Glideslope Angle : 3.0 Level_at_Gate : 5.0 Waypoints Nr, Name , Lat , Long , Turn, Radius 1 LFPG16 49.02200877 2.533222034 mot 2.00 2 EXIT16 48.90186478 2.379989555 sot 2.00 3 LFBD 44.82833333 -.7155555555 mot 2.00

Segment RelTime CallSign ICAO CO_Route CFL … … … … … …

LFPG16 05:54:50 AF620JL A319 AF620JL_LFPG_LFBD_16 290 LFPG09 05:52:45 EZY75HV A319 EZY75HV_LFBO_LFPG_09 340 LFPG12 05:54:45 BCY5002_3 RJ85 BCY5002_3_LFPG_EIDW_12 320 LFPG11 05:56:07 AF660XE A319 AF660XE_LFPG_LFML_11 330 LFPG17 05:55:59 BCY5050_2 RJ85 BCY5050_2_LFPG_EGPH_17 340 LFPG09 05:53:43 NLY8514 A320 NLY8514_LOWW_LFPG_09 380 LFPG05 05:53:55 AFR6881 B744 AFR6881_HKJK_LFPG_05 380 LFPG08 05:54:54 DAL48_2 B763 DAL48_2_KBOS_LFPG_08 370 LFPG00 05:55:59 VLG8202 A320 VLG8202_LEMD_LFPG_00 360 LFPG15 05:58:14 AFR138A A319 AFR138A_LFPG_LOWW_15 330 … … … … … …

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3.2.4 Checking for Conflicts

An additional script checks if the scenario includes conflicts based on the trajectory and parameter settings. The main parameters for the conflict checker are displayed in Figure 19. In the simulation file endless_runway_scenario.tin the requested lateral and vertical separation are set.

Figure 19 - Setup for the conflict checking script

Running the conflict script, results in a table that includes a row for each single conflict. In Table 4 you can see a part of the conflict parameters. The conflicts are represented by two aircrafts, the duration of conflict and the position of the conflict. The original table includes additional parameters like altitude, altitude rate and the track.

Table 4 - Conflicts Table

Callsign WTC Callsign WTC Start Conf

(hh:mm:ss)

End Conf

(hh:mm:ss)

Conflict Start Coordinates [degree]

Conflict End Coordinates [degree]

Flight 1 Flight 2 Flight 1 Flight 2 Flight 1 Flight 2

FDX5083 M UPS218 H 02:29:10 02:29:22 48.997 2.557 49.000 2.595 48.996 2.570 49.006 2.587

ABR2CL M BCS6848 M 02:36:05 02:36:07 49.026 2.562 49.021 2.571 49.026 2.562 49.022 2.571

AWE754 H EZY2DA M 05:17:26 05:17:38 48.992 2.539 49.013 2.527 48.996 2.549 49.006 2.523

LOT334 M TSC488 H 05:32:17 05:32:27 49.006 2.576 48.991 2.606 49.010 2.586 48.997 2.599

AAL146 M AFR1000 M 05:33:43 05:33:48 49.004 2.501 49.024 2.522 49.003 2.506 49.024 2.517

3.2.5 Conflict Resolution

There are different possibilities to handle the conflict resolution. One possible way is to implement a vertical separation level segment. First results from the conflict detection showed, that most of the conflicts occur shortly after departure. In this phase it is not possible to implement an additional separation level and therefore this method is not applicable.

Hence, a trivial method was used to solve the conflicts by deleting one of the conflict partners. As some flights are involved in more than one conflict, an algorithm deletes that one of a conflicting pair that has more following conflicts than the other one.

/****************************************************************************** / Conflicts / Lateral_Sep: requested lateral separation / Level_Vertical_Sep: requested vertical separation in case both / aircraft are in level / Vertical_Speed_Vertical_Sep: requested vertical separation in case at least / one aircraft has a vertical speed / Lower_Alt_Threshold consider only trajectory data above / /****************************************************************************** LOAD endless_runway_scenario.tin CALC_CONFLICTS Lateral_Sep: 1.5 NM Level_Vertical_Sep: 1000.0 ft Vertical_Speed_Vertical_Sep: 500.0 ft Lower_Alt_Threshold: 5.0 fl

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For the final scenario, the traffic was simulated conflict-free with a separation of 1.5 NM lateral or 500 ft vertical. The conflicts have been resolved by an algorithm that identifies the flights with the most conflicts and deletes it. Afterwards the iterative process starts the analysis again, until all conflicts are resolved. By the use of this method as few as necessary flights were deleted.

Another resolution algorithm developed by DLR [7]postpones one of the conflict partners for few seconds up to a maximum of +/- 5 minutes. However, this would possibly result in a conflict on the runway. Therefore and because of a high effort, a deconflicting by the use of this advanced algorithm was not possible in the frame of the Endless Runway project but could be lead to optimized capacity values in possible further investigations.

3.2.6 Extensible Workflow Management for Simulations

Due to the concept of shifting of runway segments when the originally planned is blocked, it is interesting to study the effect in flight distance, flight duration and fuel consumption. For the reporting of fast time simulation data the evaluation environment “Extensible Workflow Management for Simulations” (EWMS), developed by the DLR, was used. The EWMS-Software streamlines and simplifies simulation data management significantly to reduce the effort required to analyze simulation results. It provides a large number of validated analysis algorithms [9]. The best way to investigate trajectories generated by the TrafficSim offers the implemented concept for determination and visualization of significant trajectory parameters. The concept was modified for the Endless Runway concept to generate useful quantitative (diagrams) as well as qualitative (geospatial imaging) visualizations. For the representation of scalar values, charts generated by JFreeChart-Tool [10] are suitable. NASA World Wind [11] is used for the geographical visualization of trajectories.

3.3 Ground A third component for the simulation of the Endless Runway is the ground movement. In D2.2 [2] the design of the airport layout has been developed defining the infrastructure available for aircraft ground traffic. The ground simulation is intended to give an indication on how a specific airport configuration is able to accommodate the requested traffic from prior simulations.

As shown in Figure 6 the ground movement simulation uses data from the runway scheduler, the taxiway/stand layout and the ground movement concept as major inputs. Combined with specific aircraft taxi performance parameters, a simulation in Simmod PRO! has been prepared. The chosen software tool uses rule-based simulation algorithms that allow a straightforward handling of each flight movement phase.

In principle, the approach of the ground movement simulation can be described as follows:

1. Aircraft movements will be specified in the simulation as they are delivered by the runway scheduler (arriving traffic = end of segment booking; departing traffic = specified amount of time prior to begin of segment booking).

2. Aircraft will move along taxi routes as defined in D4.2 with respect to the circulation map, which reflects the taxiway usage concept.

3. Aircraft will be parked at a preselected stand to release/pick up passengers or freight, refuel etc. for a specific time (based on required minimum time or linked turnaround flight information if available).

3.3.1 Taxiway Usage

The layout and the rules for using the taxiways of the endless runway were specified in D4.2 and correspondingly implemented in the simulation. At this point parameters concerning aircraft’s performance were added. Regardless of the aircraft type a standard taxi speed of 15 kts was set for all taxiway segments of the airport, exceptional high-speed exits that are used at an average speed of 35 kts. Another special

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procedure has to be considered with the push-back since all stands are designed as terminal positions. In this case a taxi speed of 3 kts was used combined with an additional duration of 90 s modelling the release of the tug. Thereby the concerned aircraft are pushed back onto the outer taxiway of the inner apron area.

3.3.2 Turnaround Modelling

For the evaluation of the ground structure the knowledge of the turnarounds is important. Arrivals and departures are connected as one physical aircraft blocking ground resources for specific time windows. Especially the required number of gates depends heavily on the turnaround times of the flights. Not only the hourly departure and arrival numbers are relevant but also the number of aircraft that stay on the ground during this period due to longer turnaround times or overnights.

For the runway scheduler and the TMA simulation Eurocontrol’s ´s06´ were used. As there is no rotation information in the file, linking arriving and departing aircraft at an airport, turnaround information have to be worked out separately. To establish the link between an arrival at and a departure from the same gate, it will be necessary to use additional. One possibility was to use the aircraft registration, as this is a unique identifier. For this reason the ‘exp2’ data file (part of the Eurocontrol DDR - Demand Data Repository – see Appendix B) was analyzed. This file type contains aircraft registrations and can be easily matched with existing ‘so6’ files.

Thus, whenever possible, the aircraft registration number was used to match arriving and departing flights at the Endless Runway Airport (TERA). The following results could be achieved for the analyzed traffic sample (see Table 5).

Table 5 - Aircraft registration analysis results

Movements at TERA (Runway Scheduler Demand 1.0)

Detected registrations (exp2 data)

Matched flight pairs at TERA

Departure Arrival Departure Arrival Departure -> Arrival 1

Arrival -> Departure 2

802 768 402 393 59 353 1: Departure -> Arrival: ‘reverse turnaround’: Aircraft registration departs from TERA, stays somewhere and returns to TERA once. 2: Arrival -> Departure: Aircraft registration arrives at TERA, stays there and departs at a specific time.

As indicated in the detected registrations column of Table 5, only for 50% of the flights aircraft registration data were available. Therefore a considerable number of unmatched flights are left, that needed further investigation. In this context a heuristic algorithm using other information e.g. aircraft type and company was developed to improve the hit ratio.

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3.3.3 Stand Selection

The ground movement concept proposes a 4-Terminal-Layout offering an overall number of 294 stands. Each stand in the simulation is designed as a triple aircraft position that can either be used by one Code E or F aircraft or two smaller aircraft simultaneously (see red dots in Figure 20, taxiways in grey).

Figure 20 - Endless Runway available aircraft stands in ground simulation

Beyond that the ATM operational concept determines that aircraft taxiing times shall be minimized. So, a first task to be solved is to find a suitable stand for each aircraft. Based on the assumptions above the initial approach was to park aircraft next to the point they are exiting/entering the runway. Since most of the flights are linked turnaround flights and towing is not considered a stand can either be optimized for the arrival or departure part of a flight. For this study the runway exit point was chosen as the reference (for departure without prior arrival = runway entry point).

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Simulation results and analyses 4.DOW

Simulations will be carried out. As much as possible recordings will be made, including those of internal events, to enable analysis of the results and to measure the effect of new operations. This will be the base for the impact considerations in WP5.

4.1 Runway The output of the runway scheduler is a flight plan, with a detailed description of the every single flight. With increasing demand, the runway system is not able to handle the traffic anymore without delaying some of the flights. This delay is recorded and can be used as a parameter to determine the runway capacity. When a defined delay value is exceeded the runway capacity is reached. Different traffic scenarios were used in the simulation leading to the following results:

Table 6 - Average and maximum delay encountered by aircraft for various input traffic

Traffic ratio

Number of flights

Max fligts per hour

Average delay with wake rule (h:min:s)

Max delay with wake rule (h:min:s)

100.0% 1570 110 00:00:21 00:04:16

110.0% 1727 121 00:00:33 00:07:18 120.0% 1887 127 00:01:16 00:09:23 130.0% 2042 131 00:03:41 00:20:11 140.0% 2198 146 00:12:53 00:41:58

150.0% 2365 150 00:27:31 01:04:09 200.0% 3140 179 02:37:43 05:11:33

It can already be seen that exceeding 110 movements per hour is not acceptable in terms of delays if it is required that delays should not exceed 5 minutes. Therefore, from the runway point of view, the maximum capacity is established at 110 movements per hour.

In addition, the distribution of the delay over the day gives a clear indication of the problem with the increasing demand. Figure 21 presents the delay for the Traffic scenarios 1.0, 1.5 and 2.0.

• The 1.0 delay is o very low o almost constant over the day o is 0 at the end of the (all flights have been handled)

• The 1.5 delay is o significantly higher than 1.0 o is increasing during the day with a peak at 1pm o is decreasing in the second half of the day o is 0 at the end of the (all flights have been handled)

• The 2.0 delay is o Extremely higher than 1.0 and 1.5 o Is increasing during the day with a peak at 8 pm o Is decreasing in the evening hours o Is still at 200 minutes at the end of the day (some of the flights have to be moved to the next

day)

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Figure 21 - Traffic scenario

4.2 TMA

4.2.1 Conflicts

As described in 3.2.4 a script has been developed that checks whether the scenario includes conflicts based on the trajectory and parameter settings. Three separation criteria are applied, leading to a different number of conflicts. The criteria are applied to three scenarios ranking from the current-day LFPG demand to double this demand.

To sum up the findings, Table 7 shows the number of conflicts within the TMA for the traffic scenarios 1.0, 1.5 and 2.0 for three different separation setups.

Table 7 - Number of conflicts in TMA with different separation standards

#Conflicts inside 9NM radius

Separation [2NM; 1000ft]


Separation [1.5NM; 1000ft]


Separation [1.5NM; 500ft]

Demand 1.0 955 491 393

Demand 1.5 2218 1181 931

Demand 2.0 2641 1382 1090

The following figures demonstrate the conflicts in the given scenarios. Figure 22 shows the double-demand scenario where all flights during the simulation run are visualized through a line in the figure. Conflicts between flights are highlighted in red. Figure 23 shows a limited number of flights where one conflict situation between a departing and an arrival aircraft has been highlighted.

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Figure 22 - Traffic scenario (increased 2.0) with visualization of the conflicts (separation 1.5 NM or 1000 ft)

Figure 23 - Representative example of arrival-departure conflict

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As described in 3.2.5 flights have been deleted that causing conflicts. As some of the flights causing more than one conflict the number of conflicts and the number of deleted flights are different.

The following Table 8 summarizes this correlation.

Table 8 - Number of deleted flights to resolve the conflicts

Traffic scenario Number of conflicts Number of deleted flights

Demand 1.0 393 289

Demand 1.5 931 615

Demand 2.0 1090 721

The deletion of flights leads to a conflict free flight plan in TMA but reduces the number of flights and therefore the capacity values.

4.2.2 Capacity

Capacity analyses have been performed to get an indication, if the Endless Runway can handle comparable traffic as today’s airports. To get the results different demand scenarios have been setup and used in the simulations. It should be stated, that the results are only a first indication. A full capacity evaluation is much more complex, as different capacity values exist.

With the simulation setup described in chapter 3, three simulation runs have been performed. First a traffic demand that is the same as LFPG (Scenario 1.0), then a 1.5 fold increased demand (Scenario 1.5) and finally a 2 fold demand (scenario 2.0). The additional demand was generated by cloning original flights from the Eurocontrol data for LFPG.

The following figure presents the generated demand distribution for the three scenarios.

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Figure 24 - Traffic Demand Chart

Figure 25 - Traffic Demand Data Table

Hour

Scenario 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Sum

1.0 6 11 27 26 35 74 98 68 110 107 90 79 111 71 90 78 87 98 78 93 59 42 18 14 1,570

1.5 8 17 39 34 57 110 150 98 177 153 137 126 163 113 129 110 138 150 123 136 82 62 31 22 2,365

2.0 17 21 60 50 69 132 197 128 222 213 182 174 215 141 187 156 173 194 152 174 127 91 35 30 3,140

The busiest hour (from 08:00 to 9:00) has 110 movements. The additional generated traffic leads to a demand of 177 for the 1.5 scenario and 222 for the 2.0 scenario. This demand is used as an input to the runway scheduler. Following the steps described in chapter 3 the runway scheduler delivers a conflict free flight plan by optimizing the traffic demand to the available runway resources. The following figure presents an overview of the traffic distribution after the runway scheduler tool.

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Figure 26 - Runway Schedule Chart

Figure 27 - Runway Schedule Data Table

Hour

Scenario 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Sum

1.0 6 11 27 26 35 73 99 68 109 105 93 79 110 72 90 78 87 98 78 93 59 42 18 14 1,570

1.5 8 17 39 34 57 106 148 103 130 124 128 122 126 132 125 141 145 142 141 118 129 96 32 22 2,365

2.0 17 21 60 50 69 110 154 160 136 132 114 122 104 123 131 127 132 126 138 134 150 137 139 122 2,708

In the 1.0 scenario (blue line) the demand can be handled by the runway. During the highlighted time interval (8:00 to 9:00), the runway scheduler plans 109 movements with a demand of 110 (see Figure 24). The situation changes with the increased traffic scenario. The demand of 177 and 222 (see Figure 24) movements cannot be handled anymore in this hour and has to be delayed. Due to the higher traffic demand in the previous hours flights have to be shifted in time. The timely distribution of the peaks is also changing.

The runway scheduler produces a runway conflict free flight plan that is used as the input for the TMA simulation. As described before, this flight plan leads to conflicts in the TMA. Removing flights to get a conflict free flight plan in the TMA also, results in a reduced number of movements for the TMA. Figure 28presents the results from the TMA simulation with the TrafficSim tool.

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Figure 28 - TMA Simulation Chart

Figure 29 - TMA Simulation Data Table

Hour

Scenario 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Sum

1.0 6 12 24 27 35 59 73 55 83 89 72 68 83 58 75 60 68 74 63 80 49 36 18 14 1,281

1.5 8 17 33 34 53 80 102 77 94 89 94 93 92 91 93 98 97 102 99 92 95 67 29 21 1,750

2.0 17 22 53 50 55 84 105 111 97 87 93 87 76 98 97 88 94 89 100 93 100 97 99 40 1,932

For the selected time interval the number of movements changes from 109 to 83 for the 1.0 scenario, from 130 to 94 in the 1.5 scenario and from 136 to 97 in the 2.0 scenario. As a rough estimation a reduction of 25% occurs.

The following chart summarizes the capacity analyses. For the three traffic scenarios the values for demand, runway scheduler and TMA simulation are combined. All blue line colors are related to the 1.0 scenario, the orange colors to the 1.5 scenario and the green colors to the 2.0 scenario.

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Figure 30 - Runway Schedule Chart

In Appendix F some more detailed graphs are available, separating the number of movements into departures and arrivals. In addition a slightly different approach is taken for calculating the numbers. In the previous figures a one hour interval was used for calculation for easier presentation. Besides this, an analysis in a moving time interval was conducted. The capacity was calculated every five minutes with a one hour time interval. With this approach a more smoothed curve of the capacity graph could be reached.

4.2.3 Flight Distance and Duration

As a basic idea for the Endless Runway is was considered, that flights can have the most direct flight profile from and to the ER-airport. The runway segments for landing and take-off are selected to have the shortest flight distance. As the runway scheduler optimizes the runway capacity also by shifting flights from blocked to available segments, this approach is not valid in all cases. With the shifting flight distance and flight duration may change. To get a first estimate on the effects a number of flights have been analyzed in detail.

Five different flights from the Endless Runway Airport (TERA) to Frankfurt (EDDH) via a direct route from TMA Exit point to Frankfurt airport have been investigated. As presented in Figure 31, all flights have different departure segments. The green line is used as the reference trajectory as it represents the optimal situation. The last booked segment of this flight is segment 8. This means that the aircraft departs at segment 7 and flies the shortest route of the selected flights. The red lines are the trajectories of the comparison flights, where the departure segments have been shifted by the runway scheduler.

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Figure 31 - Flights from the endless runway Airport to Frankfurt (Top view)

Figure 32 - Flights from the endless runway Airport to Frankfurt (3D and vertical profile view)

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Using the EWMS the following flight distances have been calculated (Figure 33):

Figure 33 - Flight Distance from endless runway to Frankfurt in NM

In addition to the flight distance the flight duration can be calculated by using aircraft performance data (Figure 34).

Figure 34 - Flight Duration of Flights to Frankfurt in seconds

481.73

474.81

447.26

466.56

459.37

430.0

440.0

450.0

460.0

470.0

480.0

490.0

DLH8F DLH5J ABR6TR DLH2J_2 DLH2F

Flig

ht D

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ce [N

M]

Callsign

Flights TERA to EDDF

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The increased flight duration responds to the aircraft type of ABR6TR. While all other flights are operated by jet aircraft this one is a turboprop.

In addition to flight distance and flight duration the fuel flow was calculated.

The following Table 9 recaps the results of the investigation.

Table 9 - Summary of different parameters

Callsign Aircraft Type Last Booked

Segment

Distance [NM]

Duration [mm:ss]

Fuel [kg]

DLH8F A319 14 261 45:27 1,957

DLH5J A319 13 257 44:55 1,933

DLH2J_2 A319 3 253 44:17 1,905

DLH2F A319 4 249 43:43 1,881

ABR6TR ATR72 8 447 60:02 652

For better comparison the flight ABR6TR was then replaced by an A319 aircraft and simulated again, leading to the following values:

Callsign Aircraft Type Last Booked

Segment

Distance [NM]

Duration [mm:ss]

Fuel [kg]

DLH2F_3 A319 8 242 42:46 1,839

Comparing DLH8F and the new DLH2F_3 flight, a difference of 19NM, 02:41 minutes and 118kg of fuel is calculated. The increased values of the not optimal trajectory have to be assessed against the shifting of segments.

4.3 Ground The ground simulation has been run with the traffic scenario 1.0. The following figure Figure 35 presents the simulation with the ground movement concept as a background image and the aircraft objects moving along the taxiways or at the stand.

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Figure 35 – Screenshot of the SIMMOD simulation.

First results of the simulation showed, that the ground movement is also very complex and aircraft movements interfere. Especially pushbacks lead sometimes to blockings that cause delays during taxiing.

In WP 2 calculations about the required number of gates have been conducted [2]. From the theoretical perspective the airport layout and the number of gates have been expected to be sufficient. Taking into account the results from the turnaround modeling it seems that the number of gates is not enough for the traffic demand from LFPG.

Table 10 - Stands occupied by time

Time 05:00:00 08:00:00 12:00:00 14:00:00

No. stands occupied 45 158 111 120

Due to long turnarounds and blocking of gates, there might be no gate available for arriving aircraft. As Table 10 indicates, at 8 o’clock in the morning 158 stands are already occupied. As the number of available stand depends on the aircraft type, this can lead to problems. During peak hours with a high number of long haul flights only 96 stands for aircraft code E or F are available. A more detailed analysis was carried out confirming the lack of stand capacity. The following Figure 36 presents the results, clearly indicating, that in the time frame from 6 o’clock to 11 o’clock more stands are required than available.

Aircraft at the Gate

Arrivals moving along the taxiways according to the concept

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Figure 36 – Stand usage analysis

A check on the available stands at LFPG indicated that the number at LFPG is significantly higher. From this perspective the selected LFPG scenario is not directly adaptable to the provided endless runway ground infrastructure concept.

One solution could be to use some space in the inner airport area for additional stands and move some of the airport facilities to the outside. In [2] future airport expansion possibilities are addressed and approaches for additional stands are presented.

Using the 1.0 traffic scenario and the implemented turnaround model the ground simulation with SIMMOD could not be executed successfully. The limited number of stands lead to the effect, that aircraft had to wait for parking on the taxiway system, blocking other ground movements. Finally deadlock situations occurred causing the simulation to freeze. With this situation no further evaluation was possible.

To overcome this problem different approaches have been thought of. While some of them would require a complete new iteration of all conceptual work and simulations (e.g. redesign of the airport) some others could be realized with acceptable modifications. Finally it was decided to modify the 1.0 scenario. Analyses have shown that the number of heavy aircraft is consuming a high number of the gate capacity and might be the main reason for the problems. Therefore a very pragmatic approach was taken by replacing all heavy aircraft with medium type aircraft. Even this is not acceptable in terms of the chosen scenario it helps to gather some information on the taxiway system. It is assumed, that the behavior of movements of heavy and medium aircraft are comparable while moving on the ground. With this configuration the simulation was successful and could be run without interruption. Based on this adaption it can be summarized, that the concept of the taxiway rings and the inner circulation setup seems to be feasible and not a limiting factor.

-100

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50

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200

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

num

ber o

f sta

nds

Time

Stand usage for non Code E/F prioritized allocationoccupied by other occupied by code E/F available for Code E/F

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The following results for taxi times have been obtained from the ground simulation runs.

Figure 37 – Taxi Times distribution – see also Annex F for charts

Figure 37 illustrates the distribution of the taxi times. Two values are presented. One is the overall taxi time (including stoppings) and the other one the net taxi time which represents only the time the aircraft is moving. While taxi-in times (blue lines) do not vary very much between overall and net there are significant differences for taxi-out times (red lines). In addition the following Table 11 presents minimum, maximum and average values for the given taxi-in and taxi-out times.

Table 11 – Taxi Times

Min. Time [s] ([min])

Max. Time [s] ([min])

Avg. Time [s] ([min])

Taxi-out overall 325 (5.4) 1.423 (23.7) 684 (11.4) net 235 (3.9) 745 (12.4) 506 (8.4)

Taxi-in overall 89 (1.5) 730 (12.2) 360 (6.0) net 86 (1.4) 600 (10) 350 (5.8)

The taxi-in times are in a good range. An average of 6 minutes for the overall time is a very good value. The maximum taxi-in time is 12.2 minutes but most of the flights do not exceed a 10 minutes limit. As already mentioned, taxi-out times for total and net are significantly different. While the average taxi times still provide good values, the maximum time is quite high. In addition, the high taxi times have a significant frequency so they cannot be neglected as a special situation.

Analyzing the results, the allocation algorithm that is used in SIMMOD is one important factor. For arrivals the stand is selected, that is available and can be reached at the first possible time. For departures the stand, the runway entry segment and the runway entry time is fixed by the simulation and the traffic scenario. Therefore only the taxi-out route can be adapted by the simulation. As a result the stand optimization is based on the inbound traffic leading to higher taxi-out times compared to taxi-in.

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One critical step in the simulation setup is the off-block time of the departure traffic. While usually the off- block time is given as a parameter and the runway lineup results in the addition of the taxi time, the situation with the runway scheduler is different. Relevant is the time, the scheduler has blocked the requested runway segments. At this time the departure has to be ready for line-up. This would result in a backward calculation for the requested off-block time, possibly provided by a surface management tool. As this is not available in the SIMMOD environment the off-block time had to be defined by a fixed value of 15 minutes before line-up. As discovered from the net taxi-out times this was assumed to be an acceptable time buffer for all aircraft to be at the runway entry in time. If the lineup position is reached to early the aircraft will wait for the scheduled take off time at the entry segment. In some circumstances this had led to the effect that the sequence for a specific runway segment was mixed up. Due to shorter taxi distances (other stand) the number two aircraft arrived first at the segment. As the number one aircraft cannot overtake it is blocked and has to wait. Even both aircraft would have arrived the lineup position in time, the earlier scheduled flight cannot use the segment and discovers a stopping delay which leads to the high taxi delays.

As a second result it has been observed, that the simulation mainly uses the ring behind the outer terminal stands for departures as this is the fastest route. Due to pushback operations to this ring, stoppings occur, that have a negative effect to the taxi-out time. Experimenting with cost functions to force different usages had no significant effect. Other routes were used but the overall taxi times did not change.

The most inner ring was implemented in the simulation as a taxiway only, with no connections to the gates. The intention was to allow aircraft, heading for the opposite area of the airport, to pass by when pushbacks are in progress. During the simulation runs it became clear, that the most inner ring was not used at all with this setup. Obviously operations that are directly heading for the outer rings are favored. Based on the chosen setup the most inner taxiway ring can be left out, allowing more space in the inner area of the airport. To get benefit of the most inner ring the simulation setup needs to be changed. The stands have to be connected and the taxiway usage concept as to be adapted. This was not possible in the remaining time of the project.

An overall optimization, covering the planned arrival and departure segment for a flight, should be in place to optimize taxi times. This would be directly related to the benefits of the Endless Runway concept and the proposed ground structure. Due to time and budget constraints this optimization algorithm could not be implemented at this stage.

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Conclusion 5.This document contains the simulation and analyses of the Endless Runway. It has been set up based on the ATM concept developed in Tasks 4.1 and 4.2 of WP4 and in coordination with the work that is performed in WP2 and WP 3 of the project. The document describes the simulation approach, the scenario setup, the simulation tools and the results obtained by running the simulations.

Scenario definition

Two scenarios have been defined for operating the Endless Runway. A low wind scenario (winds below 20 kts) where all segments of the runway can be used for arrival and departure operations. This is the most demanding case as the system operates at the limits. In the high wind use case (wind above 20kts) some segments are not available for all operations anymore. The Endless Runway is then operated as a runway system with two parallel runways. For the simulations only the high wind case is considered as it was not possible to implement both use case with their different operational concepts into the simulation.

As a base for the scenarios, real flight data from Eurocontrol were used. Paris Charles de Gaulle was selected as a comparable airport in terms of traffic demand in hub airport operations. Flight plans for the endless runway have been processed and artificially increased by adding virtual flights to evaluate the capacity limits of the Endless Runway.

Modelling and simulation framework

In accordance with D4.2 three areas have been evaluated: the runway, the TMA and the ground movement area. For each of them a separate simulation tool was selected, as one single tool cannot handle all required concept elements. The developed runway scheduler has been defined as the master, providing the optimized and conflict free flight plan (related to the runway) for the simulations of TMA and ground. Standardised BADA data have been used for aircraft performance characteristics. Some of the parameters have been adapted by results of WP3. Especially landing and Take-Off distances need to be corrected because of the banked nature of the runway. TMA and ground simulation take the flight plan and simulate the traffic with the given time and segment restrictions.

The DLR TrafficSim tool has been used for the TMA simulation. The conceptual elements of the route structures and TMA entry and exit points have been integrated. Additional routing points have been implemented to allow the aircraft to enter the TMA at the entry points correctly.

For ground operations Simmod Pro! was used. All related elements of the airport layout, like taxiways and stands have been implemented and the ground movement concept for the low wind scenario has been setup. Special attention has been taken to the modelling of the turnaround, which was not available from the original data files. The turnaround (rotation) of physically the same aircraft has a significant effect on the capacity of the ground structure as stands may be blocked for longer times.

Simulation and analyses

The runway scheduler provides a conflict free scenario for the low wind case. For different traffic demands the resulting delay was calculated. With increasing demand the delay increases significantly. While the delay stays in acceptable limits for the 1.0 scenario (corresponding to today’s Charles de Gaulle traffic), it exceeds the defined 5 minute threshold already with a 10% traffic increase. The capacity from the runway part is therefore set to the maximum hourly movements of the 1.0 scenario, which is 110.

The TMA simulation was run with three traffic scenarios. The 1.0 traffic demand, the 1.5 fold increase and the doubled traffic scenario. The separation criteria have been set to 1.5NM lateral and 500ft vertical. Because of the complex crossing route structure in the TMA a number of conflicts between flights occur. A straight forward method was used, to eliminate the conflicts by deleting on of the flights of a conflicting pair. This leads to conflict free scenarios in TMA but reduces the number of movements that have been handled. The

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maximum number of movements per hour in the TMA was handled with the 2.0 traffic demand as an input reduced by the conflicting flights. A number of around 110 movements could be achieved also in the TMA under best circumstances. This is comparable to the runway limit.

The ground simulation has only been run with the traffic scenario 1.0 which is the original traffic from Paris Charles the Gaulles. As a first result the number of stands might be a problem as the ground simulation shows blockings and deadlocks for moving aircraft. Long turnarounds block the stands and limit the number of available stand for new arrivals. A solution could not be found so far. One option would be to make room for additional stands in the centre of the airport and move some facilities to the outside. To obtain any result of the ground simulation, the traffic scenario was changed. All heavy aircraft have been replaced by medium types and the simulation could be run successfully. As a result, taxi in and taxi out times could be analysed. All values are comparable to today’s operations or even better (especially hub airports).

All simulations of the Endless Runway from the ATM perspective have given a first indication that the concept is generally feasible but could be limited compared to today’s high traffic operation. A few assumptions in terms of separation had to be made, to allow the multiple use of the runway.

The chosen traffic demand of Paris Charles de Gaulle with a number of 1570 movements per day and a maximum of 110 movements per hour seems to be close to the limits of the Endless Runway. A higher number of movements tend to not acceptable delays for flights and a high number of conflicts in the TMA.

The selected framework with different simulations was the only possible approach within the frame of the project. A consistent simulation environment with optimization taking into account runway, TMA and ground, could probably lead to a harmonized traffic and better results.

The simulations and analyses presented here will be the base for the evaluation of the impact of the Endless Runway that will be carried out in WP5.

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References 6.[1] The Endless Runway DoW, Hesselink, H.H., [2] D2.2 The Endless Runway Airport Infrastructure, Remiro Albert, et.al., version 1, August 2013 [3] D3.2 The Endless Runway Aircraft Aspects, Schmollgruber Peter, et.al., version 1, August 2013 [4] D4.2 The Endless Runway ATM Concept, Loth Steffen, et.al., version 2, September 2013 [5] Witt, G.A.A., Well-rounded Improvement of Airport Capacity, analysing the Endless Runway Concept,

Amsterdam, May 2013, NLR-TR-2013-183 [6] User manual for the Base of Aircraft Data (BADA), Report No. 2010-003, revision 3.8, Eurocontrol

Experimental Centre [7] Kuenz, Alexander, Efficient Conflict Detection and Resolution for 4D Air Traffic Management, German

Aerospace Center (DLR), Braunschweig, 2012. [8] Edinger, Christiane, Angela Schmitt, Rapid Prototyping for ATM operational concepts development,

German Aerospace Center (DLR), Braunschweig, 2012. [9] Scharnweber, Alexander, S. Schier, Automated Simulation Data and Process Management for

Heterogeneous Air Traffic Management Simulations, German Aerospace Center (DLR), Braunschweig, 2011.

[10] Gilbert, David, The JFreeChart Class Library – Developer Guide, Object Refinery Limited, United Kingdom, 2009.

[11] Hogan, Patrick, NASA World Wind Java Software Development Kit, NASA Ames Research Center, 2009, http://worldwind.arc.nasa.gov.

[12] DDR Reference Manual Version 1.5.8, Eurocontrol, 2010 [13] Urban B., Rudolph F., Helm, S. M., Development of an HMI to Monitor and Predict Passenger Progress

in the Landside Process Chain for a Holistiv Airport Management, Deutscher Luft- und Raumfahrtkongress 2013 – Proceedings, Berlin 2012.

http://worldwind.arc.nasa.gov/

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Appendix A Data extraction from the BADA files

BADA OPF file (example for the A320):

CCCCCCCCCCCCCCCCCCCCCCCCCCCCCC A320__.OPF CCCCCCCCCCCCCCCCCCCCCCCCCCCC/ CC / CC AIRCRAFT PERFORMANCE OPERATIONAL FILE / CC / CC / CC File_name: A320__.OPF / CC / CC Creation_date: Apr 30 2002 / CC / CC Modification_date: Mar 30 2011 / CC / CC / CC====== Actype ======================================================/ CD A320__ 2 engines Jet M / CC A320-231 with V2500 engines wake / CC / CC====== Mass (t) ====================================================/ CC reference minimum maximum max payload mass grad / CD .64000E+02 .39000E+02 .77000E+02 .21500E+02 .43250E+00 / CC====== Flight envelope =============================================/ CC VMO(KCAS) MMO Max.Alt Hmax temp grad / CD .35000E+03 .82000E+00 .41000E+05 .33295E+05 -.3136E+03 / CC====== Aerodynamics ================================================/ CC Wing Area and Buffet coefficients (SIM) / CCndrst Surf(m2) Clbo(M=0) k CM16 / CD 5 .12260E+03 .14041E+01 .79242E+00 .00000E+00 / CC Configuration characteristics / CC n Phase Name Vstall(KCAS) CD0 CD2 unused / CD 1 CR CLEAN .14050E+03 .26659E-01 .38726E-01 .00000E+00 / CD 2 IC 1 .11800E+03 .23000E-01 .44000E-01 .00000E+00 / CD 3 TO 1+F .11210E+03 .33000E-01 .41000E-01 .00000E+00 / CD 4 AP 2 .10510E+03 .38000E-01 .41900E-01 .00000E+00 / CD 5 LD FULL .10130E+03 .96000E-01 .37100E-01 .00000E+00 / CC Spoiler / CD 1 RET / CD 2 EXT .00000E+00 .00000E+00 / CC Gear / CD 1 UP / CD 2 DOWN .38000E-01 .00000E+00 .00000E+00 / CC Brakes / CD 1 OFF / CD 2 ON .00000E+00 .00000E+00 / CC====== Engine Thrust ===============================================/ CC Max climb thrust coefficients (SIM) / CD .14231E+06 .51680E+05 .56809E-10 .10138E+02 .88710E-02 / CC Desc(low) Desc(high) Desc level Desc(app) Desc(ld) / CD .10847E+00 .13603E+00 .29831E+05 .15749E+00 .39566E+00 / CC Desc CAS Desc Mach unused unused unused / CD .31000E+03 .78000E+00 .00000E+00 .00000E+00 .00000E+00 / CC====== Fuel Consumption ============================================/ CC Thrust Specific Fuel Consumption Coefficients / CD .75882E+00 .29385E+04 / CC Descent Fuel Flow Coefficients / CD .89418E+01 .93865E+05 / CC Cruise Corr. unused unused unused unused / CD .96358E+00 .00000E+00 .00000E+00 .00000E+00 .00000E+00 / CC====== Ground ======================================================/ CC TOL LDL span length unused / CD .21900E+04 .14400E+04 .34100E+02 .37570E+02 .00000E+00 / CC====================================================================/ FI /

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BADA OPF file (example for the A340-300):

CCCCCCCCCCCCCCCCCCCCCCCCCCCCCC A343__.OPF CCCCCCCCCCCCCCCCCCCCCCCCCCCC/ CC / CC AIRCRAFT PERFORMANCE OPERATIONAL FILE / CC / CC / CC File_name: A343__.OPF / CC / CC Creation_date: Apr 30 2002 / CC / CC Modification_date: Feb 17 2009 / CC / CC / CC====== Actype ======================================================/ CD A343__ 4 engines Jet H / CC A340-313 with CFM56 5C4 engines wake / CC / CC====== Mass (t) ====================================================/ CC reference minimum maximum max payload mass grad / CD .21000E+03 .13100E+03 .27500E+03 .43000E+02 .11079E+00 / CC====== Flight envelope =============================================/ CC VMO(KCAS) MMO Max.Alt Hmax temp grad / CD .33000E+03 .86000E+00 .41000E+05 .30330E+05 -.1013E+03 / CC====== Aerodynamics ================================================/ CC Wing Area and Buffet coefficients (SIM) / CCndrst Surf(m2) Clbo(M=0) k CM16 / CD 5 .36160E+03 .12905E+01 .63080E+00 .00000E+00 / CC Configuration characteristics / CC n Phase Name Vstall(KCAS) CD0 CD2 unused / CD 1 CR Clean .14200E+03 .21718E-01 .35123E-01 .00000E+00 / CD 2 IC 1 .11700E+03 .32090E-01 .37330E-01 .00000E+00 / CD 3 TO 1+F .10800E+03 .43270E-01 .35020E-01 .00000E+00 / CD 4 AP 2 .10400E+03 .53980E-01 .35520E-01 .00000E+00 / CD 5 LD FULL .10100E+03 .76640E-01 .33020E-01 .00000E+00 / CC Spoiler / CD 1 RET / CD 2 EXT .00000E+00 .00000E+00 / CC Gear / CD 1 UP / CD 2 DOWN .27000E-01 .00000E+00 .00000E+00 / CC Brakes / CD 1 OFF / CD 2 ON .00000E+00 .00000E+00 / CC====== Engine Thrust ===============================================/ CC Max climb thrust coefficients (SIM) / CD .38118E+06 .56784E+05 .14767E-10 .98968E+01 .77097E-02 / CC Desc(low) Desc(high) Desc level Desc(app) Desc(ld) / CD .56674E-01 .10050E+00 .92790E+04 .22198E+00 .34628E+00 / CC Desc CAS Desc Mach unused unused unused / CD .30000E+03 .80000E+00 .00000E+00 .00000E+00 .00000E+00 / CC====== Fuel Consumption ============================================/ CC Thrust Specific Fuel Consumption Coefficients / CD .62965E+00 .10209E+04 / CC Descent Fuel Flow Coefficients / CD .31094E+02 .75361E+05 / CC Cruise Corr. unused unused unused unused / CD .92082E+00 .00000E+00 .00000E+00 .00000E+00 .00000E+00 / CC====== Ground ======================================================/ CC TOL LDL span length unused / CD .27650E+04 .18300E+04 .60300E+02 .63600E+02 .00000E+00 / CC====================================================================/ FI /

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Initial approach, final approach and climb speed calculation

We take the example of the A340-300. For the initial approach, final approach and climb speed calculation, we read the BADA .PTF file.

BADA PERFORMANCE FILE Apr 01 2010 AC/Type: A343__ Source OPF File: Feb 17 2009 Source APF file: Mar 05 2009 Speeds: CAS(LO/HI) Mach Mass Levels [kg] Temperature: ISA climb - 250/290 0.80 low - 157200 cruise - 250/300 0.80 nominal - 210000 Max Alt. [ft]: 41000 descent - 250/300 0.82 high - 275000 ========================================================================================== FL | CRUISE | CLIMB | DESCENT | TAS fuel | TAS ROCD fuel | TAS ROCD fuel | [kts] [kg/min] | [kts] [fpm] [kg/min] | [kts] [fpm] [kg/min] | lo nom hi | lo nom hi nom | nom nom ========================================================================================== 0 | | 145 1941 1519 1127 274.2 | 136 717 94.2 | | | 5 | | 146 1930 1507 1114 272.0 | 137 729 93.5 | | | 10 | | 148 1919 1495 1101 269.9 | 143 764 93.1 | | | 15 | | 154 2018 1572 1162 268.9 | 155 755 59.7 | | | 20 | | 155 2007 1560 1148 266.7 | 187 883 60.8 | | | 30 | 230 64.6 81.0 107.8 | 178 2382 1854 1385 267.0 | 230 991 29.9 | | | 40 | 233 64.7 81.2 108.1 | 212 2847 2207 1663 269.6 | 233 1007 29.4 | | | 60 | 272 74.8 88.1 109.6 | 272 3428 2522 1792 272.1 | 272 1230 28.6 | | | 80 | 280 75.1 88.5 110.2 | 280 3316 2427 1707 263.1 | 280 1266 27.8 | | | 100 | 289 75.5 89.0 110.9 | 334 3241 2396 1721 262.9 | 345 1612 27.0

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V(initial approach)

V(initial approach) = average TAS(DESCENT) between FL 080 and FL 030

As there is no value for the FL 090, we interpolate twice.

𝑽(𝒊𝒏𝒊𝒕𝒊𝒂𝒍 𝒂𝒑𝒑𝒓𝒐𝒂𝒄𝒉) =𝑇𝐴𝑆𝐷𝐸𝑆𝐶𝐸𝑁𝑇,𝐹𝐿 100 + 𝑇𝐴𝑆𝐷𝐸𝑆𝐶𝐸𝑁𝑇,𝐹𝐿80

2 + 𝑇𝐴𝑆𝐷𝐸𝑆𝐶𝐸𝑁𝑇,𝐹𝐿 030

2=𝟐 𝑻𝑨𝑺𝑫𝑬𝑺𝑪𝑬𝑵𝑻,𝑭𝑳 𝟎𝟑𝟎 + 𝑻𝑨𝑺𝑫𝑬𝑺𝑪𝑬𝑵𝑻,𝑭𝑳 𝟏𝟎𝟎 + 𝑻𝑨𝑺𝑫𝑬𝑺𝑪𝑬𝑵𝑻,𝑭𝑳𝟖𝟎

𝟒

𝑉(𝑖𝑛𝑖𝑡𝑖𝑎𝑙 𝑎𝑝𝑝𝑟𝑜𝑎𝑐ℎ 𝐴340 − 300) ==2 × 230 + 280 + 345

4≅ 271 𝑘𝑡𝑠

V(final approach)

V(final approach) = average TAS(DESCENT) between FL 030 and FL 0

𝑽(𝒇𝒊𝒏𝒂𝒍 𝒂𝒑𝒑𝒓𝒐𝒂𝒄𝒉) =𝑻𝑨𝑺𝑫𝑬𝑺𝑪𝑬𝑵𝑻,𝑭𝑳 𝟎𝟑𝟎 + 𝑻𝑨𝑺𝑫𝑬𝑺𝑪𝑬𝑵𝑻,𝑭𝑳 𝟎

𝟐

𝑉(𝑓𝑖𝑛𝑎𝑙 𝑎𝑝𝑝𝑟𝑜𝑎𝑐ℎ 𝐴340 − 300) =136 + 230

2= 183 𝑘𝑡𝑠

V(climb)

V(climb) = average TAS(CLIMB) between FL 0 and FL090

𝑽(𝒄𝒍𝒊𝒎𝒃) =𝑇𝐴𝑆𝐶𝐿𝐼𝑀𝐵,𝐹𝐿 100 + 𝑇𝐴𝑆𝐶𝐿𝐼𝑀𝐵,𝐹𝐿80

2 + 𝑇𝐴𝑆𝐶𝐿𝐼𝑀𝐵,𝐹𝐿 0

2=𝟐 𝑻𝑨𝑺𝑪𝑳𝑰𝑴𝑩,𝑭𝑳 𝟎 + 𝑻𝑨𝑺𝑪𝑳𝑰𝑴𝑩,𝑭𝑳 𝟏𝟎𝟎 + 𝑻𝑨𝑺𝑪𝑳𝑰𝑴𝑩,𝑭𝑳𝟖𝟎

𝟒

𝑉(𝑐𝑙𝑖𝑚𝑏 𝐴340 − 300) =2 × 145 + 280 + 334

4= 226 𝑘𝑡𝑠

V(initial take off)

For the initial take-off speed, we read the Bada .OPF file corresponding to the A340-300 aircraft.

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𝐕(𝐢𝐧𝐢𝐭𝐢𝐚𝐥 𝐭𝐚𝐤𝐞 𝐨𝐟𝐟) = V2 = 𝟏.𝟐 𝐕𝐬𝐭𝐚𝐥𝐥𝑻𝑶

V(initial take off A340 − 300) = 1.2 × 108 ≅ 130 kts

We note that this value is slightly lower than the TAS in the climb phase at FL0 (=145 kts).

CCCCCCCCCCCCCCCCCCCCCCCCCCCCCC A343__.OPF CCCCCCCCCCCCCCCCCCCCCCCCCCCC/

CC /

CC AIRCRAFT PERFORMANCE OPERATIONAL FILE /

CC /

CC /

CC File_name: A343__.OPF /

CC /

CC Creation_date: Apr 30 2002 /

CC /

CC Modification_date: Feb 17 2009 /

CC /

CC /

CC====== Actype ======================================================/

CD A343__ 4 engines Jet H /

CC A340-313 with CFM56 5C4 engines wake /

CC /

CC====== Mass (t) ====================================================/

CC reference minimum maximum max payload mass grad /

CD .21000E+03 .13100E+03 .27500E+03 .43000E+02 .11079E+00 /

CC====== Flight envelope =============================================/

CC VMO(KCAS) MMO Max.Alt Hmax temp grad /

CD .33000E+03 .86000E+00 .41000E+05 .30330E+05 -.1013E+03 /

CC====== Aerodynamics ================================================/

CC Wing Area and Buffet coefficients (SIM) /

CCndrst Surf(m2) Clbo(M=0) k CM16 /

CD 5 .36160E+03 .12905E+01 .63080E+00 .00000E+00 /

CC Configuration characteristics /

CC n Phase Name Vstall(KCAS) CD0 CD2 unused /

CD 1 CR Clean .14200E+03 .21718E-01 .35123E-01 .00000E+00 /

CD 2 IC 1 .11700E+03 .32090E-01 .37330E-01 .00000E+00 /

CD 3 TO 1+F .10800E+03 .43270E-01 .35020E-01 .00000E+00 /

CD 4 AP 2 .10400E+03 .53980E-01 .35520E-01 .00000E+00 /

CD 5 LD FULL .10100E+03 .76640E-01 .33020E-01 .00000E+00 /

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Appendix B Eurocontrol Demand Data Repository – File Types

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Appendix C Ouput files of the runway scheduler

Figure 38 – Extraction of a Runway scheduler output showing the sequencing of traffic demand on the Endless Runway

Type

Depa

rtur

e ai

rpor

tAr

rival

ai

rpor

tO

ther

airp

ort n

ame

Calls

ign

ICAO

Co

deAi

rcra

ft m

odel

Wak

e ca

tego

ryRF

LCl

oses

t cr

uise

lat.

(°)

Clos

est

crui

se lo

ng

(°)

Airc

raft

be

arin

g (°

)

Endl

ess

Runw

ay

segm

ent

(ass

umin

g co

unte

r-cl

ockw

ise)

Roll

leng

th

(m)

Num

ber

of ro

ll se

gmen

ts

Num

ber

of b

uffe

r se

gmen

ts

Stal

l sp

eed

(m/s

)

Initi

al

appr

oach

sp

eed

(m/s

)

Fina

l ap

proa

ch

spee

d (m

/s)

Initi

al

take

off

spee

d (m

/s)

Clim

b sp

eed

(m/s

)

Firs

t re

ques

ted

segm

ent

Last

re

ques

ted

segm

ent

Nb

segm

ents

Book

ing

dura

tion

(s)

Requ

este

d bo

okin

g st

art

Requ

este

d bo

okin

g en

d

Firs

t bo

oked

se

gmen

t

Last

bo

oked

se

gmen

tDe

lay

(s)

Effe

ctiv

e bo

okin

g st

art

Effe

ctiv

e bo

okin

g en

dCo

mm

ent

ARRI

VAL

EDDM

LFPG

Mun

ich

Inte

rnat

iona

l Airp

ort

AFR1

423

A318

AIRB

US A

318

M36

050

.053

618.

6372

225

317

1528

31

47.8

138.

191

.664

.211

6.4

015

454

08:5

9:07

09:0

0:02

96

32.6

8980

608

:59:

4009

:00:

34Fo

llow

s AFR

3539

. Wak

e tu

rbul

ence

(H, M

): 3

min

DEPA

RTUR

ELF

PGLF

BOTo

ulou

se-B

lagn

ac A

irpor

tAF

782U

MA3

20AI

RBUS

A32

0M

350

47.5

852.

2911

118

714

2190

41

57.7

139.

594

.469

.212

0.8

1713

588

09:0

0:50

09:0

2:18

115

0.0

09:0

0:50

09:0

2:18

Shift

ed fr

om 1

7 to

1 (2

-seg

men

t shi

ftin

g).

ARRI

VAL

CYUL

LFPG

Mon

trea

l / P

ierr

e El

liott

Tru

deau

AFR

349

B744

BOEI

NG

747-

400

H39

049

.715

-4.6

2305

101

1021

484

160

.714

1.1

99.8

84.0

131.

611

75

5909

:01:

2409

:02:

2411

70.

009

:01:

2409

:02:

24Re

ques

t gra

nted

with

out m

odifi

catio

nDE

PART

URE

LFPG

EGLL

Lond

on H

eath

row

Airp

ort

BAW

307

A321

AIRB

US A

321

M24

049

.048

052.

715

728

2280

51

60.7

139.

594

.972

.812

2.6

127

687

09:0

1:50

09:0

3:17

1712

28.2

9199

309

:02:

1809

:03:

45Fo

llow

s AF7

82UM

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Appendix D Segment and TMA Coordinates

Table 12 - Coordinates departures (Rwy, TMA Exit points) Table 13 - Coordinates arrivals (TMA Entry, Rwy points)

Departure from

RWY Take Off (start of segment)

TMA Exit Point

Arrival to

TMA Entry Point

RWY Touch Down (end of segment)

Segment Lat Long Lat Long Segment Lat Long Lat Long 0 49.0269 2.5462 48.9995 2.3113 0 48.9995 2.7887 49.0269 2.5538 1 49.0269 2.5538 49.0539 2.3187 1 48.9468 2.7674 49.0252 2.5610 2 49.0252 2.5610 49.1033 2.3539 2 48.9019 2.7200 49.0220 2.5668 3 49.0220 2.5668 49.1419 2.4128 3 48.8703 2.6521 49.0177 2.5706 4 49.0177 2.5706 49.1650 2.4885 4 48.8559 2.5719 49.0128 2.5719 5 49.0128 2.5719 49.1697 2.5719 5 48.8605 2.4890 49.0079 2.5706 6 49.0079 2.5706 49.1552 2.6526 6 48.8834 2.4136 49.0035 2.5668 7 49.0035 2.5668 49.1235 2.7207 7 48.9219 2.3546 49.0003 2.5610 8 49.0003 2.5610 49.0784 2.7679 8 48.9712 2.3191 48.9986 2.5538 9 48.9986 2.5538 49.0255 2.7888 9 49.0255 2.3112 48.9986 2.5462

10 48.9986 2.5462 48.9712 2.7809 10 49.0784 2.3321 49.0003 2.5390 11 49.0003 2.5390 48.9219 2.7454 11 49.1235 2.3793 49.0035 2.5332 12 49.0035 2.5332 48.8834 2.6864 12 49.1552 2.4474 49.0079 2.5294 13 49.0079 2.5294 48.8605 2.6110 13 49.1697 2.5281 49.0128 2.5281 14 49.0128 2.5281 48.8559 2.5281 14 49.1650 2.6115 49.0177 2.5294 15 49.0177 2.5294 48.8703 2.4479 15 49.1419 2.6872 49.0220 2.5332 16 49.0220 2.5332 48.9019 2.3800 16 49.1033 2.7461 49.0252 2.5390 17 49.0252 2.5390 48.9468 2.3326 17 49.0539 2.7813 49.0269 2.5462

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Appendix E Traffic Scenario Movements

Scenario 1.0 (100% traffic)

Table 14 - Hourly traffic 1.0 separated in arrival and departure flights

Traffic Demand 1.0 Runway Scheduler 1.0 TMA Simulation 1.0 Hour Arr Dep Total Arr Dep Total Arr Dep Total

0 (00:00- 01:00) 0 6 6 0 6 6 0 6 6 1 (01:00- 02:00) 4 7 11 4 7 11 5 7 12 2 (02:00- 03:00) 4 23 27 4 23 27 3 21 24 3 (03:00- 04:00) 23 3 26 23 3 26 24 3 27 4 (04:00- 05:00) 22 13 35 22 13 35 22 13 35 5 (05:00- 06:00) 33 41 74 33 40 73 28 31 59 6 (06:00- 07:00) 64 34 98 64 35 99 46 27 73 7 (07:00- 08:00) 45 23 68 45 23 68 35 20 55 8 (08:00- 09:00) 43 67 110 43 66 109 33 50 83 9 (08:00- 10:00) 51 56 107 50 55 105 40 49 89 10 (10:00- 11:00) 41 49 90 42 51 93 26 46 72 11 (11:00- 12:00) 26 53 79 26 53 79 23 45 68 12 (12:00- 13:00) 55 56 111 54 56 110 38 45 83 13 (13:00- 14:00) 38 33 71 39 33 72 30 28 58 14 (14:00- 15:00) 31 59 90 31 59 90 23 52 75 15 (15:00- 16:00) 49 29 78 49 29 78 40 20 60 16 (16:00- 17:00) 47 40 87 47 40 87 34 34 68 17 (17:00- 18:00) 51 47 98 51 47 98 41 33 74 18 (18:00- 19:00) 34 44 78 34 44 78 24 39 63 19 (19:00- 20:00) 37 56 93 37 56 93 31 49 80 20 (20:00- 21:00) 36 23 59 36 23 59 27 22 49 21 (21:00- 22:00) 28 14 42 28 14 42 24 12 36 22 (22:00- 23:00) 6 12 18 6 12 18 6 12 18 23 (23:00- 24:00) 0 14 14 0 14 14 0 14 14

768 802 1,570 768 802 1,570 603 678 1,281

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0 (00:00- 01:00) 0 8 8 0 8 8 0 8 8 1 (01:00- 02:00) 6 11 17 6 11 17 7 10 17 2 (02:00- 03:00) 8 31 39 8 31 39 6 27 33 3 (03:00- 04:00) 30 4 34 30 4 34 30 4 34 4 (04:00- 05:00) 38 19 57 38 19 57 34 19 53 5 (05:00- 06:00) 52 58 110 50 56 106 39 41 80 6 (06:00- 07:00) 98 52 150 94 54 148 63 39 102 7 (07:00- 08:00) 64 34 98 69 34 103 52 25 77 8 (08:00- 09:00) 76 101 177 62 68 130 46 48 94 9 (08:00- 10:00) 77 76 153 48 76 124 31 58 89 10 (10:00- 11:00) 66 71 137 72 56 128 46 48 94 11 (11:00- 12:00) 45 81 126 55 67 122 37 56 93 12 (12:00- 13:00) 77 86 163 41 85 126 23 69 92 13 (13:00- 14:00) 61 52 113 67 65 132 39 52 91 14 (14:00- 15:00) 47 82 129 63 62 125 44 49 93 15 (15:00- 16:00) 68 42 110 60 81 141 39 59 98 16 (16:00- 17:00) 77 61 138 89 56 145 58 39 97 17 (17:00- 18:00) 81 69 150 74 68 142 58 44 102 18 (18:00- 19:00) 52 71 123 74 67 141 45 54 99 19 (19:00- 20:00) 51 85 136 38 80 118 28 64 92 20 (20:00- 21:00) 49 33 82 62 67 129 44 51 95 21 (21:00- 22:00) 43 19 62 66 30 96 45 22 67 22 (22:00- 23:00) 13 18 31 13 19 32 13 16 29 23 (23:00- 24:00) 1 21 22 1 21 22 1 20 21

1,180 1,185 2,365 1,180 1,185 2,365 828 922 1,750

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0 (00:00- 01:00) 2 15 17 2 15 17 2 15 17 1 (01:00- 02:00) 6 15 21 6 15 21 8 14 22 2 (02:00- 03:00) 12 48 60 12 48 60 9 44 53 3 (03:00- 04:00) 43 7 50 43 7 50 43 7 50 4 (04:00- 05:00) 45 24 69 45 24 69 34 21 55 5 (05:00- 06:00) 60 72 132 45 65 110 37 47 84 6 (06:00- 07:00) 126 71 197 93 61 154 70 35 105 7 (07:00- 08:00) 87 41 128 112 48 160 77 34 111 8 (08:00- 09:00) 92 130 222 67 69 136 43 54 97 9 (08:00- 10:00) 100 113 213 55 77 132 32 55 87 10 (10:00- 11:00) 83 99 182 50 64 114 38 55 93 11 (11:00- 12:00) 61 113 174 62 60 122 34 53 87 12 (12:00- 13:00) 104 111 215 48 56 104 28 48 76 13 (13:00- 14:00) 78 63 141 49 74 123 38 60 98 14 (14:00- 15:00) 62 125 187 42 89 131 27 70 97 15 (15:00- 16:00) 98 58 156 64 63 127 38 50 88 16 (16:00- 17:00) 89 84 173 78 54 132 58 36 94 17 (17:00- 18:00) 105 89 194 47 79 126 24 65 89 18 (18:00- 19:00) 65 87 152 52 86 138 35 65 100 19 (19:00- 20:00) 70 104 174 85 49 134 58 35 93 20 (20:00- 21:00) 81 46 127 81 69 150 58 42 100 21 (21:00- 22:00) 62 29 91 72 65 137 54 43 97 22 (22:00- 23:00) 11 24 35 70 69 139 47 52 99 23 (23:00- 24:00) 2 28 30 47 75 122 18 22 40

1,544 1,596 3,140 1,327 1,381 2,708 910 1,022 1,932

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Appendix F Result charts


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Taxi Times

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D4.3 Simulation - the Endless Runway · [1]: “This work package will cover all aspects of the...

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