1. IDENTIFICATION OF OPERATIVE PROBLEMS USING A MODEL-BASED APPROACH FOR LELYSTAD AIRPORT Miguel Mujica Mota, Paolo Scala, Nico de Bock Aviation Academy, Amsterdam University of Applied Sciences 1 International Conference on Air Transport 2015 (INAIR’15)

2. Development of a Multi-Airport System Including: Rotterdam Airport Eindhoven Airport Lelystad Airport IMPORTANCE 2

3. Lelystad Airport

4. 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? 4

5. CHALLENGES AND OBJECTIVES Develop a model to assess the future performance Verify that attractive PIs can be obtained by the Airport Identify potential problems for the future airport and/or airspace Identify the capacity of the system Analyze the impact of uncertainty within the system 5

6. APPROACH: MODEL-BASED ANALYSIS

7. GROUND MODEL CHARACTERISTICS 7

8. CONFIGURATION A Gate 1 Gate 16 Configuration A: L-shaped linear terminal with partial parallel taxiway (original), runway configuration 05 8

9. CONFIGURATION B Gate 1Gate 16 9 Configuration B: Linear terminal with parallel taxiway. Nose In-Nose out

10. CONFIGURATION C Gate 1 Gate 16 10 Configuration C: Linear terminal with parallel taxiway. Taxi In- Taxi Out

11. 11 EXPERIMENTALL DESIGN

12. RESULTS (1) 12

13. RESULTS (2) 13

14. 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 range

15. DESCRIPTION OF THE SIMULATION MODEL OF LELYSTAD AIRPORT TMA 15 Lelystad 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)

16. 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 TMA

17. DESCRIPTION OF THE SIMULATION MODEL OF LELYSTAD AIRPORT TMA 17 Holding 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

18. DESCRIPTION OF THE SIMULATION MODEL OF LELYSTAD AIRPORT TMA 18 Ground operations assumptions They refer to the number of gates*, Taxiing times, runway occupancy time and turnaround time *Schiphol Group, ”Ondernemingsplan Lelystad Airport”, March 2014 In 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)

19. SCENARIO&RESULTS 19 Scenarios were based on the volume of incoming aircraft, and they take into account peak hours at Schiphol airport (Original flight schedule)* 1° scenario2° scenario3° scenario 60 % Original flight scheduleOriginal 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

20. SCENARIO&RESULTS 20 Results 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 HP

21. SCENARIO&RESULTS 21 Results 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 HP

22. SCENARIO&RESULTS 22 Results 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 HP

23. SCENARIO&RESULTS 23 In 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)

24. 24 Response surface with Apron’s entering mode fixed at level 1 (Left-Right) SURFACE RESPONSE

25. 25 Response surface with Apron’s entering mode fixed at level 2 (Center-Out) SURFACE RESPONSE

26. 26 LESSONS LEARNED&FUTURE WORK GROUND 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 system Scenario 1 and 2 are not congested Scenario 3 starts to be congested Capacity limit of the system is found between scenario 2 and 3

27. 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