Development of Flight Inefficiency Metrics for Environmental Performance Assessment of ATM

Transcription

1 Development of Flight Inefficiency Metrics for Environmental Performance Assessment of ATM Tom G. Reynolds 8 th USA/Europe Air Traffic Management Research and Development Seminar Napa, California, 29 June-2 July 2009

2 2 Motivation ATM has important role in reducing environmental impacts of aviation: ATM affects ALL aircraft Increasing efforts to quantify ATM s current impact IPCC Concept of Flight Inefficiency commonly used This study designed to complement these activities

3 3 Outline 1. Identify sources of Flight Inefficiency 2. Describe Flight Inefficiency metric options 3. Analyse data with key Flight Inefficiency metrics 4. Discuss insights enabled through this approach

4 4 Outline 1. Identify sources of Flight Inefficiency 2. Describe Flight Inefficiency metric options 3. Analyse data with key Flight Inefficiency metrics 4. Discuss insights enabled through this approach

5 5 Flight Inefficiency Sources Constraints to aircraft flying their 4D optimal trajectory Departure fix Departure procedures Standard routes, Altitudes and Speeds Restricted airspace Adverse weather Expensive airspace En Route Airspace Congested airspace Arrival procedures Landing Arrival fix Holding Take-off Taxi-out Taxi-in Arrival Terminal Airspace Departure Terminal Airspace

6 Sample Inefficiencies: Terminal Airspace Standard Procedures 6 Departures Departure fix Arrivals Arrival fix 50 nm terminal area

7 Sample Inefficiencies: En Route Airspace 7 SEA BOS SFO DEN ORD LAX DFW ATL MCO Restricted areas 29 August 2005 Hurricane Katrina

8 8 Holding absorbs delay & maximises runway capacity Vectoring for spacing and sequencing on final approach Sample Inefficiencies: Arrival Terminal Airspace Heathrow Vectoring for final approach 50 nm terminal area range ring Holding stacks

9 9 Outline 1. Identify sources of Flight Inefficiency 2. Describe Flight Inefficiency metric options 3. Analyse data with key Flight Inefficiency metrics 4. Discuss insights enabled through this approach

10 10 Concept commonly used as ATM performance indicator Flight Inefficiency Metrics Quantify difference between ideal and actual performance Focus has been on average route extension over great circle (26.4 nm) Flight inefficiency metric: Actual-Optimal 100% Optimal Source: (A-D) (D-G)

11 11 Flight Inefficiency Metrics Route extension is simple and compatible with current surveillance systems, but neglects effects in other flight dimensions Fuel-based metrics (e.g. excess fuel burn) capture these effects and directly relate to emissions, but are more challenging due to need to determine optimum fuel burn and access to more aircraft info

12 Metrics in Different Flight Dimensions Dimension Sample actual Sample optimal Advantages Disadvantages Lateral Flown ground distance Great circle distance Simple No info from other flight dimensions Vertical or Speed Average cruise altitude or speed Optimal en route altitude or speed Captures vertical or speed elements More complex & No info from other flight dimensions Fuel Average block fuel Optimal block fuel Proportional to emissions More complex 12

13 13 Outline 1. Identify sources of Flight Inefficiency 2. Describe Flight Inefficiency metric options 3. Analyse data with key Flight Inefficiency metrics 4. Discuss insights enabled through this approach

14 14 European Flight Data Summary Flight data from European airline A320 family during early 2008 Lateral & fuel-based analysis 50 nm terminal area n=4420

15 15 Lateral Analysis: Route Extension D Turn D TO θ Departure TA Departure fix DDepart R TA D En_route_actual D En_route_GC En Route Sample lateral path Shortest lateral path Arrival fix D Arrival D Hold D Downwind Arrival TA D Base φ D Final GTE DepTA = (D TO + D Turn + D Depart ) R TA GTE En_route = D En_route_actual D En_route_GC GTE ArrTA = (D Arrival + D Hold + D Downwind + D Base + D Final ) R TA

16 16 Fuel Analysis: Aircraft Performance Modelling FDR data used to validate candidate aircraft performance models to determine optimum fuel burn Fuel Burn (Relative to FDR Total Fuel) Climb Take-off Taxi-out Cruise Taxi-in Landing Descent Actual data (FDR) Model data (Piano-X) Model data (BADA) Track Distance (nm) Piano-X can be better tailored to observed operations

17 Fuel Analysis: Optimum Fuel Burn Challenges Function of many variables: Aircraft type Weight Route length Winds Centre of gravity Temperature Operator cost index, i.e. ratio of time-related costs to fuel-related costs Block Time (mins) Block Fuel (kg) Typical narrow-body mission Minimum time (high cost index) Long-Range Cruise Minimum fuel (low cost index) Minimum time (high cost index) Long-Range Cruise Minimum fuel (low cost index) Aircraft Weight (kg) 17

18 18 Lateral analysis Average TGTE: 51 nm/13% Lateral & Fuel Inefficiency Comparison Arrival TA 26 nm (51%) Dep. TA 9 nm (18%) En route 16 nm (31%) n=1794, A320 European flights only. Average great circle distance 403 nm

19 19 Lateral analysis Average TGTE: 51 nm/13% Lateral & Fuel Inefficiency Comparison Fuel analysis Average excess fuel burn * : 645 kg/23% Arrival TA 26 nm (51%) Dep. TA 9 nm (18%) En route 16 nm (31%) Arrival TA 161 kg (25%) En route 300 kg (46%) Departure TA 184 kg (29%) n=1794, A320 European flights only. Average great circle distance 403 nm *Relative to minimum theoretical fuel burn

20 Lateral & Fuel Inefficiency Comparison Lateral analysis Average TGTE: 51 nm/13% Arrival procedures 13 nm (25%) Holding & vectoring 13 nm (25%) Departure procedures 9 nm (18%) Stnd rts & res. airspc 8 nm (16%) Congestion & adverse wx 8 nm (16%) Arr trk ext 19 kg (3%) Holding & vectoring, sub-optimal arrival altitude profile 132 kg (20%) Fuel analysis Average excess fuel burn * : 645 kg/23% Taxi-in 10 kg (2%) Standard cruise altitude & speed 225 kg (35%) Taxi-out 20 kg (3%) Departure track extension 150 kg (23%) Sub-opt dep alt/spd profile 24 kg (3%) Std rtes/rest airspace, adverse wx & congestion 75 kg (12%) n=1794 (A320 European flights only), Average great circle distance 403 nm * Relative to minimum theoretical fuel burn 20

21 21 Outline 1. Identify sources of Flight Inefficiency 2. Describe Flight Inefficiency metric options 3. Analyse data with key Flight Inefficiency metrics 4. Discuss insights enabled through this approach

22 ATM Evolution Implications Helps prioritize ATM evolution concepts and technologies Pushback ORIGIN AIRPORT Taxi- Out Departure/Climb Take-Off Cruise Descent/Approach Landing DESTINATION AIRPORT Taxi-In Optimised lateral, vertical, speed profiles Displaced FUTURE Strategic de-confliction thresholds OPERATIONAL Steeper CONCEPTS FOR Single-engine e.g. wind- Single-engine Optimised Engine glideslope IMPROVED optimal taxi optimised optimal taxi push-back time power e.g. e.g. full angles LATERAL/FUEL- routing with no ground track routing with no and sequence optimisation Continuous Continuous BASED holding at optimal Runway holding Climb Descent ENVIRONMENTAL cruise allocation for Departures Approach PERFORMANCE altitude & optimal taxi speed routing 4D trajectory management algorithms Runway Push-back Taxi Take-off (G,A) allocation Taxi ENABLING optimisation optimisation power optimisation Advanced Communication: Datalink (G-A) algorithms (G) TECHNOLOGIES algorithms (G) algorithms (G) manage- algorithms (G) Datalink (G-A) ment (A) Advanced Navigation: P-RNAV (A) Datalink (G-A) Datalink (G-A) Datalink (G-A) Advanced Surveillance: ADS-B (G,A) P-RNAV (A) Airspace re-design Modified standard operating OTHER Modified standard operating procedures Modified standard operating procedures procedures ENABLERS CDM/CEM CDM/CEM CDM/CEM Key: 22 (G) = Ground, (A) = Aircraft, (G-A) = Ground to Aircraft, ADS-B = Automatic Dependent Surveillance-Broadcast, CDM = Collaborative Decision Making, CEM = Collaborative Environment Management, P-RNAV = Precision Area Navigation,

23 23 Environmental Implications Findings affect aviation environmental impact predictions IPCC scaling factors of 1.15 on fuel burn, falling to 1.05 in 2015 to account for ATM inefficiencies and their improvement Source: Sausen et al., 2005, Aviation Radiative Forcing in 2000: An Update on IPCC, Meteorol. Z., 14 (4), pp

24 24 Environmental Implications Findings affect aviation environmental impact predictions Location of non-co 2 emissions affects climate response Methane Ozone Radiative forcings due to changes in ozone, methane & methaneinduced ozone as a function of the altitude of a 5% NO x perturbation Methaneinduced ozone Net forcing Much more work needs to be done: Climate scientists and ATM researchers must collaborate Source: Köhler et al., 2008, Impact of Perturbations to Nitrogen Oxide Emissions from Global Aviation, J. Geophysical Research, Vol. 113, D11305

25 25 Conclusions ATM has an important part to play in aviation environmental impact mitigation Flight inefficiency metrics effective at quantifying ATM performance Importance of considering terminal area operations Differences between track extension & excess fuel burn Note: not all inefficiencies should be attributed to ATM Analysis provides important insights into: ATM evolution priorities Environmental impact assessment

26 26 Acknowledgements Funding bodies: Forthcoming publications at ATIO: Effects of airspace charging on airline route selection More detailed assessment of fuel inefficiency analysis Further information: Tom G. Reynolds: