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Identification of Operative Problems using a model-based ap Identification of Operative Problems using a model-based ap

Identification of Operative Problems using a model-based ap - PowerPoint Presentation

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Identification of Operative Problems using a model-based ap - PPT Presentation

Miguel Mujica Mota Paolo Scala Nico de Bock Aviation Academy Amsterdam University of Applied Sciences 1 International Conference on Air Transport 2015 INAIR15 Development of a Multi ID: 475171

holding aircraft scenario airport aircraft holding airport scenario number lelystad model results turns configuration tma pattern diverted incoming amp

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Slide1

Identification of Operative Problems using a model-based approach for Lelystad Airport

Miguel Mujica Mota, Paolo Scala, Nico de BockAviation Academy, Amsterdam University of Applied Sciences

1

International Conference on Air Transport

2015 (INAIR’15)Slide2

Development of a Multi-

Airport System

Including:

Rotterdam

Airport

Eindhoven

Airport

Lelystad

Airport

importance

2Slide3

Lelystad AirportSlide4

Research questions for Lelystad

What is the most attractive configuration?

What is the best cost/effective configuration from Airport and Airline perspective?Potential problems?

How to make it flexible enough?

4Slide5

Challenges and Objectives

Develop a model to assess the future performanceVerify that attractive PIs can be obtained by the AirportIdentify potential problems for the future airport and/or airspaceIdentify the capacity of the systemAnalyze the impact of uncertainty within the system

5Slide6

Approach: Model-based analysisSlide7

Ground MODEL CHARACTERISTICS

7Slide8

Configuration A

Gate 1

Gate 16

Configuration A:

L-shaped linear terminal with partial parallel taxiway (original), runway configuration 05

8Slide9

Configuration B

Gate 1

Gate 16

9

Configuration

B: Linear

terminal with

parallel taxiway. Nose In-Nose outSlide10

Configuration c

Gate 1

Gate 16

10

Configuration C

: Linear

terminal with

parallel taxiway. Taxi In- Taxi OutSlide11

11

Experimentall designSlide12

Results (1)

12Slide13

Results (2)

13Slide14

AIRSPACE MODEL CHARACTERISTICS

TAT Vehicles

- 1 fueling truck

- 1 bus for boarding

- 1 bus for

deboarding

- 2 stairs (for dual boarding)

- 1 water truck

- 1 cleaning truck

- 1 baggage cart for baggage in and out

14

Separation

minima(NM) ICAO

Aircraft

speed

rangeSlide15

Description of the Simulation model of Lelystad airport TMA

15Lelystad Airspace (TMA)

The airport is included in the Schiphol TMA 1 (Class A, Max FL 095-Min 1500 AMSL) Aircraft fly below it.

Incoming(outgoing) flow of aircraft come(go) from(to) east, aircraft fly in the NW Milligen TMA (Class B, Max FL065-Min 1500 AMSL)Slide16

Description of the Simulation model of Lelystad airport TMA

16

Routes

for RWY 23 and 05

taken

into

account in the model

Alders H., ”Presentatie en toelichting van de in het MER te onderzoeken routevarianten”

Routes in the TMASlide17

Description of the Simulation model of Lelystad airport TMA

17Holding pattern procedure

Aircraft are diverted into the holding patter due to congestion (number of aircraft on the ground and along the route) or disruption (crosswind)

Multiple layers (stack) separated vertically by a safe distance (1000 ft)

Used as a

congestion indicator:

Number of aircraft in the holding

Average number of turns by Aircraft

Holding pattern Entry point/IAF

Holding pattern

Holding pattern Slide18

Description of the Simulation model of Lelystad airport TMA

18Ground operations assumptions

They refer to the number of gates*,Taxiing times, runway occupancy time and turnaround

time

*

Schiphol

Group, ”

Ondernemingsplan Lelystad

Airport”, March 2014In the simulation model, ground side was modeled with a server object with:

Initial Capacity (number of gates) Processing time (Taxiing times, runway occupancy time and turnaround time) Slide19

Scenario&Results

19Scenarios were based on the volume of incoming aircraft, and they take into account peak hours at Schiphol airport (Original flight schedule)*

scenario

2° scenario

3° scenario

60 % Original flight schedule

Original

flight schedule

(Schiphol peak hours)

200% Original flight schedule

Experiments:One day of operations

10 replications*Schiphol Group, ”Ondernemingsplan Lelystad Airport”, March 2014

These three scenarios were evaluated in order to test how the TMA can absorb different amount of traffic

In the first scenario a limited amount of traffic was tested

In the third scenario a higher volume of traffic was tested

Slide20

Scenario&Results

20Results obtained:Total number of incoming/outgoing aircraft

Number of aircraft diverted into the holding pattern

Number of turns made into the holding pattern

Average number of turns made in the holding pattern for each aircraft

1° Scenario

ATMs

Aircraft diverted into the HPSlide21

Scenario&Results

21Results obtained:Total number of incoming/outgoing aircraft

Number of aircraft diverted into the holding pattern

Number of turns made into the holding pattern

Average number of turns made in the holding pattern for each aircraft

2° Scenario

ATMs

Aircraft diverted into the HPSlide22

Scenario&Results

22Results obtained:Total number of incoming/outgoing aircraft

Number of aircraft diverted into the holding pattern

Number of turns made into the holding pattern

Average number of turns made in the holding pattern for each aircraft

3° Scenario

ATMs

Aircraft diverted into the HP

Number of turns into the HPSlide23

Scenario&Results

23In average 9 aircraft diverted into the holding pattern, 41% of the cases betweeen 5 and 15 aircraft delayed into the holding pattern

Average number of turns made in the holding pattern for each aircraft (1,33), 11% of the cases 1 turn and 89% 2 turns

Results from scenario 3 (High volume of incoming aircraft)Slide24

24

Response

surface with Apron’s enteringmode fixed at level 1 (Left-Right)

Surface

REsponseSlide25

25

Response

surface with Apron’s enteringmode fixed at level 2 (

Center

-Out)

Surface

REsponseSlide26

26

Lessons learned&Future workGROUND

The stability of the system impacts the performance on the airport

Taxi-in Taxi-out (

Config

. C) has good potential when using an efficient allocation

algorithm if not segregated operation will be more stable.

Airspace

We could identify tresholds for good performance of the systemScenario 1 and 2 are not congested

Scenario 3 starts to be congestedCapacity limit of the system is found between scenario 2 and 3Slide27

Thank

you for your

attention!

Identification of Operative Problems using a model-based approach for Lelystad Airport

Miguel Mujica Mota, Paolo Scala, Nico de Bock

(a)

Aviation Academy,

Amsterdam University of Applied Sciences

Aviation

Academy

www.hva.nl/aviation