Impact of a new type of aircraft on ATM

Impact of a new type of aircraft on ATM Study of the low & slow concept Cyril Allignol ATM in smart and efficient air transport systems Workshop in Oslo, 31st May 2017

Introduction 1 / 25 Low & Slow concept Aimed at short/medium-haul flights Fly lower (FL200 to FL300) and slower (M0.6 to M0.7) Positive impacts expected on Fuel burn Contrails

Introduction 1 / 25 Low & Slow concept Aimed at short/medium-haul flights Fly lower (FL200 to FL300) and slower (M0.6 to M0.7) Positive impacts expected on Fuel burn Contrails Impact on ATM? Reduction or increase of traffic complexity? Which altitude and speed to choose?

Introduction 1 / 25 Low & Slow concept Aimed at short/medium-haul flights Fly lower (FL200 to FL300) and slower (M0.6 to M0.7) Positive impacts expected on Fuel burn Contrails Impact on ATM? Reduction or increase of traffic complexity? Which altitude and speed to choose? Study realised in the context of the NECTAR project (Airbus-ONERA-ENAC)

Contents 2 / 25 1 CATS: a Complete Air Traffic Simulator Principle Performance model Inputs Conflict detection and resolution Outputs 2 Experiments Assumptions Scenarios 3 Insight into the results Impact of replacement ratio Impact of cruise altitude

CATS: a Complete Air Traffic Simulator Principle 3 / 25 Complete Air Traffic Simulator Fast-time simulator Developped in the late 90 s and used in many research projects at ENAC Discrete time model (time step is δt) Airspace Flight plans Performance model CATS 4D Trajectories Conflicts Maneuvers

CATS: a Complete Air Traffic Simulator Performance model 4 / 25 Performance model Eurocontrol BADA 400+ aircraft models CATS uses performance tables derived from the total energy model Lower computation times CRUISE CLIMB DESCENT AS fuel AS ROC fuel AS ROD fuel lo nom hi lo nom hi nom nom nom FL290 487 222.4 251.5 273.6 487 1593 999 717 370.8 459 1987 39.2 FL310 499 220.6 250.7 273.6 499 2013 1245 792 348.2 473 2024 37.4 FL330 494 206.9 239.9 264.9 494 1789 1022 576 321.3 488 1952 35.7 FL350 490 195.0 231.0 258.4 490 1747 777 337 294.6 490 2835 34.0 FL370 488 184.9 224.5 254.6 488 1312 462 70 268.6 488 2504 32.3 FL390 488 176.9 220.5 253.7 488 1024 200 0 243.2 488 2485 30.5 Source: Eurocontrol - BADA, A380 performance table

CATS: a Complete Air Traffic Simulator Performance model 5 / 25 Performance model Assumptions Take-off operated at nominal mass Mass is not updated in the simulation Performances are interpolated between 2 available altitudes Still, trajectories are very close to those obtained with the full BADA model

CATS: a Complete Air Traffic Simulator Inputs 6 / 25 Inputs Airspace data Airports Beacons Routes Control sectors Traffic data Flight plans (initial, regulated by NMOC, realised) 20 AF101NR LFBO LFPO 9710 0 A320 0 21 255 280 490 22 O N N O 31 LFBO 32AW T0U FISTO DPRE PERIG DIBAG TUDRA BEVOL AMB CAD VAORL ODRAN PO 32 255 255 255 263 263 268 272 277 280 283 289 289 292 298 33 0 140 152 280 280 280 280 270 270 260 156 152 110 40 41 AW TA X1 R1 OG OY OT OA 42 236 253 253 256 257 257 270 270 43 260 261 262 268 277 283 284 300

CATS: a Complete Air Traffic Simulator Conflict detection and resolution 7 / 25 Conflict detection Notation (p k+1 (p k, tk ), t k+1 ), k t k+1 t k = δt

CATS: a Complete Air Traffic Simulator Conflict detection and resolution 8 / 25 Conflict detection 5 NM Conflict dh (p k, p j ) < N h and 1000 ft d (p k, p j ) < N For en-route: N h = 5 NM N = 1000 ft (RVSM)

CATS: a Complete Air Traffic Simulator Conflict detection and resolution 8 / 25 Conflict detection 5 NM Conflict dh (p k, p j ) < N h and 1000 ft d (p k, p j ) < N j j For en-route: N h = 5 NM N = 1000 ft (RVSM) α L j L j Detection of zones of conflicts Size of the zone depends on speeds and angle

CATS: a Complete Air Traffic Simulator Conflict detection and resolution 9 / 25 Influence of time step on detection m x N h D 2 m x δt m x δt = 15 s

CATS: a Complete Air Traffic Simulator Conflict detection and resolution 10 / 25 Conflicts resolution Automatically find maneuvers to avoid detected conflicts O t 0 t 1 α D Algorithms Centralized genetic algorithm 1 against n A algorithm Clusters are handled independently

CATS: a Complete Air Traffic Simulator Outputs 11 / 25 Outputs 4D Trajectories For each flight sectors entry and exit times, times over beacons for each time step: position, speed, climb rate

CATS: a Complete Air Traffic Simulator Outputs 11 / 25 Outputs 4D Trajectories For each flight sectors entry and exit times, times over beacons for each time step: position, speed, climb rate Conflicts Aircraft involved, altitudes, speeds, headings, start/end times, sector

CATS: a Complete Air Traffic Simulator Outputs 11 / 25 Outputs 4D Trajectories For each flight sectors entry and exit times, times over beacons for each time step: position, speed, climb rate Conflicts Aircraft involved, altitudes, speeds, headings, start/end times, sector Resolution maneuvers Deviation angle, start/end times and altitudes, sectors at begin and end of maneuver

Contents Experiments 12 / 25 1 CATS: a Complete Air Traffic Simulator Principle Performance model Inputs Conflict detection and resolution Outputs 2 Experiments Assumptions Scenarios 3 Insight into the results Impact of replacement ratio Impact of cruise altitude

Experiments 13 / 25 Experiments Objective Assess the impact of new operations (low & slow) on ATM Process Replace part of the aircraft with the new aircraft model to be tested Run simulations with the new aircraft Measure the complexity of the traffic (conflicts, necessary maneuvers, densities, etc.) Comparison with reference scenario

Experiments Assumptions 14 / 25 Assumptions Assumptions inherent to the use of CATS simulator Conflict detection is only active above FL100 (leaving out Terminal Contral Areas, which have different procedures) Replaced aircraft are shifted around the design FL (not all aircraft on the same FL) 450 400 350 300 Reference traffic 50% short haul replaced No specific new FL preference is taken into account FL 250 200 150 100 0 200 400 600 800 1000 1200 1400 Number of flights

Scenarios Experiments Scenarios 15 / 25 French airspace

Scenarios Experiments Scenarios 15 / 25 French airspace Traffic: three days with different volumes Low traffic (14th January 2012) Medium traffic (31st March 2012) High traffic (6th July 2012) 5689 flights 7688 flights 9798 flights

Scenarios Experiments Scenarios 15 / 25 French airspace Traffic: three days with different volumes Low traffic (14th January 2012) Medium traffic (31st March 2012) High traffic (6th July 2012) 5689 flights 7688 flights 9798 flights Aircraft replaced by new model Airbus A320 family: A318, A319, A320, A321 Boeing B737 family: B737-200 to B737-900 Replacement ratios: 0 %, 20 %, 50 %, 80 % and 100 %

Scenarios Low & Slow aircraft Experiments Scenarios 16 / 25 Cruise speeds M0.65 for the most likely low & slow concept M0.75 for a low-only concept M0.60 to question the opportunity of slowing down even more Cruise altitudes FL210 for the most likely low & slow concept FL350 for a slow-only concept FL290 for an intermediate solutions

Insight into the results 17 / 25 Contents 1 CATS: a Complete Air Traffic Simulator Principle Performance model Inputs Conflict detection and resolution Outputs 2 Experiments Assumptions Scenarios 3 Insight into the results Impact of replacement ratio Impact of cruise altitude

Insight into the results Impact of replacement ratio 18 / 25 Impact of replacement ratio on conflicts AC210 3000 Low traffic Medium traffic High traffic 2500 Number of conflicts 2000 1500 1000 500 0% 20% 40% 60% 80% 100% Short haul aircraft replaced

Insight into the results Impact of replacement ratio 19 / 25 Impact of replacement ratio on conflicts AC290 3000 Low traffic Medium traffic High traffic 2500 Number of conflicts 2000 1500 1000 500 0% 20% 40% 60% 80% 100% Short haul aircraft replaced

Insight into the results Impact of replacement ratio 20 / 25 Impact of replacement ratio on conflicts AC350 3000 Low traffic Medium traffic High traffic 2500 Number of conflicts 2000 1500 1000 500 0% 20% 40% 60% 80% 100% Short haul aircraft replaced

Insight into the results Impact of cruise altitude 21 / 25 Impact of cruise altitude Number of conflicts 700 Low traffic Medium traffic High traffic Number of additional conflicts w.r.t. reference 600 500 400 300 200 100 210 290 350 Optimal flight level of new aircraft

Insight into the results Impact of cruise altitude 22 / 25 Impact of cruise altitude Number of conflicts for AC210 450 Reference traffic 80% short haul replaced 400 350 300 FL 250 200 150 100 0 50 100 150 200 250 300 350 Number of conflicts

Insight into the results Impact of cruise altitude 23 / 25 Impact of cruise altitude Number of conflicts for AC350 450 Reference traffic 50% short haul replaced 400 350 300 FL 250 200 150 100 0 100 200 300 400 500 Number of conflicts

Conclusions and further work 24 / 25 Conclusions and further work Conclusions Use of FTS to evaluate a new concept of aircraft operations Low & Slow concept has a slightly negative impact on ATM (more interventions from ATC for conflict resolution) Further works Finish analysis of the results Simulations with other types of aircraft Enrich CATS with other complexity metrics Possibility to use the simulator as an input of an optimization algorithm?

25 / 25 Thank you for your attention Questions?