Sustainable Aviation, Air Traffic Management and Avionic Systems Research at RMIT University Dr Roberto Sabatini FRIN, SMAIAA, SMIEE, MRAeS, MCGI Aviation Team Leader UAS Research Team Member Avionics & ATC/ATM Theme Leader Sir Lawrence Wackett Aerospace Research Centre School of Aerospace, Mechanical and Manufacturing Engineering Tel: +61 3 9925 8015 Email:
[email protected]
Turin, 11-12 March 2014
Sir Lawrence Wackett Aerospace Research Centre
Aviation Research Focus Area 1: Sustainable Aviation and Systems for Green Operation
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Introduction to Aviation Sustainability The main ‘actors’ in aviation sustainability: • Organisations for international cooperation − United Nations, Organisation for Economic Cooperation & Development (OECD), Intergovernment Panel on Climate Change (IPCC), European Commission (EC) • −
International aviation organisations ICAO, FAA, International Air Traffic Association (IATA), ACARE, etc.
• −
Air transport operators: airports, air traffic control & airlines Melbourne airport, Air Services Australia, Qantas, etc.
•
−
Aerospace manufacturers: aircraft, engines, avionics & other equipment Boeing, Airbus, Rolls Royce, Thales, BAe Systems, etc.
• −
Non-Government organisations & lobby groups ‘Green’ groups etc.
•
Users: passengers & freight shippers
•
Research & scientific organisations
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Sustainability: Environmental Management •
Environmental management in the broadest sense involves oceans, freshwater systems, land and atmosphere.
•
Aviation is mostly concerned with the environmental management of the atmosphere: atmospheric pollution/noise and of the land: airports and ground operations.
•
Aircraft environmental management includes: − Use of non-renewal resources (e.g., fossil fuels, materials) − Greenhouse gases (e.g., CO2) − Nitrogen oxides − Sulphur oxides − Volatile organic compounds − Particulate matter − Contrails − Noise
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Sustainability: Environmental Management •
Airport environmental management includes: − Contaminated land (ground & surface water at airports arising from jet fuels) − Aircraft de-icing − Waste generation − Land take − Terminal buildings − Ground transport (e.g., terminal buses)
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Introduction to Sustainability: Pollution •
Atmospheric pollution caused by aircraft is becoming recognised as the most serious sustainability issue for aviation.
•
Pollution includes carbon dioxide, nitrogen oxide, contrails, all of which contribute to global warming.
•
It is estimated that aviation industry contribution to global warming is currently 2-3%, although may increase 10-20% by 2050 due to growth in air transport.
•
In addition, ground-level emissions at airports (from aircraft, buildings & surface vehicles) are increasing.
•
Technology advances have been successful in reducing atmospheric and ground emissions from aircraft, but this is offset by growth in aviation.
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Introduction to Sustainability: Pollution Impact of aviation on climate change is complex and we will examine the key elements in this course.
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Introduction to Sustainability: Pollution Major progress on developing more efficient aircraft: lower fuel consumption (cost-saving) & less greenhouse emissions. We will examine how these improvements have been achieved. Comet
Percentage of Base-Line Comet
100
80
engine fuel consumption
60
40 aircraft fuel burn per seat
20
0 1950
1960
1970
1980
1990
2000
2010
Year of Introduction © RMIT University
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Introduction to Sustainability: Pollution Historic trends in fuel burn for new jet aircraft (1960-2008).
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Introduction to Sustainability: Pollution CO2 Emission Projections
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Introduction to Sustainability: Pollution Inverting the CO2 emission trend with new technologies
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Introduction to Sustainability: Noise
•
120
Public opposition to aviation tends to focus on (airport) noise. Modern aircraft are quieter than their predecessors. However, the increase in aircraft traffic compounds public exposure to noise (particularly people living close to airports).
115
105
Noise can dominate the relationship between airports and local residents, and can lead to local operating regulations constraining aircraft operations.
B707-320
100 B747-200
95
•
B707-120
110
Aircraft Noise (dB)
•
A300 B777
90
A380 B787
A350
85
80 1960 1970 1980 1990 2000 2010 2020
Year of First Flight 10 dB reduction = 50% less noise
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Introduction to Sustainability: Noise •
We will examine noise reduction for aircraft (engine, airframe and operations).
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•
We will discover that some technology evolutions are driven by contradicting forces (e.g. open rotor or NOx vs. CO2).
•
This is where sound engineering judgement is needed.
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Sustainable Aviation Technologies ATM Systems and Procedures
Aircraft Structures, Propulsion and Systems
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Airport Design and Operations
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Sustainable Aviation Technologies ATM Technologies Development of innovative ground-based and airborne Communications, Navigation and Surveillance (CNS) systems needed to enable the 4DTrajectory (4DT) optimisation, negotiation and validation features required in the future ATM context. Current research addresses the design of innovative ground-based ATM system for 4DT Planning, Negotiation and Validation (4-PNV) with the Next Generation of Flight Management Systems (NG-FMS).
The 4-PNV system receives multiple options of 4DT intents from each aircraft equipped with NG-FMS. These 4DT intents are based on performance weighting adhering to uplinked airspace constraints and meeting the operational objectives by enhancing the economic efficiency, environmental sustainability and minimising disruptions caused by unexpected events.
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Sustainable Aviation Technologies ATM Technologies (cont.) These novel ATM systems validate the aircraft trajectory intents by implementing adequate separation and flow optimisation methods, establishing an optimal and safe solution for each aircraft. The overall aim is to increase the efficiency and effectiveness of ATM by increasing the level of automation (negotiation and validation schemes) enhancing the decision making process, improving operations efficiency and safety.
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Sustainable Aviation Technologies Aircraft Technologies Weight gains: • Lighter materials and structures. • Use of composites and new metals to reduce mass.
Aerodynamic gains: • Novel aircraft shapes and architectures (e.g., blended wing, flying wing, morphing wings, smart high-lift devices). Gaseous emission gains: • Novel propulsion systems (e.g., high bypass ratio, open rotor, distributed propulsion). • Bio-fuels / Hydrogen / sustainable fuels.
Noise emission gains: • flight paths / new engines / configurations.
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Sustainable Aviation Technologies Aircraft Technologies Energy management gains: •
Evolution of aircraft systems to increase fuel economy and reduce spurious offtakes from the engine to improve engine performance.
•
This includes the on-board fuel system and how it controls and manages fuel efficiently.
•
The most appropriate choice of hydraulic, electrics and bleed air as a source of power for systems actuation and the impact on engine off-take.
Operational gains: •
Next generation avionics systems connected with highly automated groundbased CNS/ATM systems (Network-centric ATM).
•
The future aircraft are “moving” nodes in a network with Pilots and ATCO’s providing high-level decision making.
• •
3D and 4D trajectory optimisation in the presence of PBN requirements Prognostics and health monitoring – Systems that detects degrading performance of the aircraft systems and can be used to predict failures and poor performance to improve maintenance planning.
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Sustainable Aviation Technologies Airport Technologies • • • • •
Airport-level noise mitigations Reductions at source. Land use planning and management. Noise abatement operational procedures. Airport operating restrictions (limiting access to given airports). Noise Charges.
Air quality and climate change mitigations • Air quality problem: − Particulate matter (PM)/smoke. − Nitrogen oxides (NOx). − Unburned hydrocarbons (UHCs). − Ozone (O3). − Carbon monoxide (CO).
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Direct health effects
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Sustainable Aviation Technologies Airport Technologies Air quality and climate change mitigations
•
Measuring air quality and assessing its impacts − Concentration-response functions (CRFs), taking into account concentration levels and exposure times to observe health response (e.g, epidemiological studies). − Air pollution sensors (ground/airborne) and emission models. − Computer models for emission and dispersion (e.g., ICAO, FAA, EUROCONTROL and UK DoT models).
•
Possible mitigations: − Operational procedures (e.g., APU use limitations, restrictions on engine run-up for test, restrictions on thrust reverse). − Emission charges. − Airport authority policies (e.g., cleaner ground transportation, highoccupancy, hybrid and electric vehicles).
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Sustainable Aviation Technologies Airport Technologies Airport water quality impact mitigations
•
De-icing fluids amount, collection and disposal
•
Fuel and other chemical leaks and spills reductions (reliable storage and distribution, secondary containment and cleanup procedures)
•
Stormwater runoff
Airport wildlife impact mitigations •
Reducing wildlife dangers to aircraft and vice versa
•
Vegetation management
•
Controlling the establishment of landfills and waste disposal sites
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Airport fencing
•
Animal distress calls
•
Loud sounds (?), chemical repellents (?)
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Sustainable Aviation Organisations
http://www.icao.int/Pa ges/default.aspx
http://www.sustainabl eaviation.co.uk/
www.sesarju.eu/
www.cleansky.eu/
www.faa.gov/nextgen/
http://www.aeron autics.nasa.gov/i srp/era/
http://www.icao.int/publ ications/journalsreports /2013/6802_en.pdf
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www.sesarju.eu/envir onment/aire http://www.faa.gov/nextgen/impleme ntation/programs/aire/
http://www.cleansky.eu/categ ory/tags/skyline
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Experience in Sustainable Aviation Technology • Deliver active wing technologies and new aircraft configuration for breakthrough, new products.
• Low-weight aircraft using smart structures, • Low external noise configurations and • Integration of technology developed in other ITDs, such as engines, energy management and new system architectures. Co-led by: Alenia and EADS-CASA
• Design and build five engine demonstrators to integrate technologies for low noise and lightweight low pressure systems, high efficiency, low NOx and low weight cores and novel configurations. Co-led by: Rolls-Royce and Safran
Evaluation platform: Assesses the environmental impact of the technology developed by the ITDs.
Co-led by: Airbus and SAAB
• Innovative rotor blades and engine installation for noise reduction, • Lower airframe drag, • Integration of diesel engine technology and • Advanced electrical systems for elimination of noxious hydraulic fluids and fuel consumption reduction. Co-led by: Eurocopter and AugustaWestland
Co-led by: DLR and Thales
• Focus on more/all-electrical aircraft equipment and systems architectures, thermal management, capabilities for "green" trajectories and mission and improved ground operations to give any aircraft the capability to fully exploit the benefits of the Single European Sky.
• Focus on green design and production, withdrawal, and recycling of aircraft, by optimal use of raw materials and energies thus improving the environmental impact of the whole products life cycle. Co-led by: Dassault and Fraunhofer Institute
Co-led by: Thales and Liebherr
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Experience in Sustainable Aviation Technology Clean Sky SGO Management of Trajectory and Mission (MTM)
• Aircraft will be able to fly greener trajectories throughout the various flight phases, thanks to technologies which allow a reduced fuel consumption, avoidance of meteorological hazards and tailoring of the flight path to known local conditions. • The silent and agile aircraft will generate a reduced noise footprint during departure and approach, with significant benefits for the population. • The synergies between Clean Sky and SESAR are exploited in the MTM domain. © RMIT University
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Experience in Sustainable Aviation Technology
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Experience in Sustainable Aviation Technology Clean Sky – SGO ITD Department of Aerospace Engineering and Department of Power & Propulsion Dr Roberto Sabatini PM WP3.1 and WP3.2 CNS/ATM Research Team Leader E:
[email protected] T: +44 1234 75 8290
Greener Aircraft Trajectories under ATM Constraints (GATAC) Aircraft will fly greener trajectories throughout the various flight phases, thanks to technologies which allow a reduced fuel consumption, avoidance of meteorological hazards and tailoring of the flight path to known local conditions. The silent and agile aircraft generates a reduced noise footprint during departure and approach
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Experience in Sustainable Aviation Technology Dr Roberto Sabatini PM Clean Sky SGO WP3.1 and WP3.2 CNS/ATM Research Team Leader E:
[email protected] T: +44 1234 75 8290
Airborne Laser Systems for Atmospheric Sounding in the Near Infrared Innovative Technique for Atmospheric Propagation Measurements, allowing a direct determination of atmospheric extinction, and, through suitable inversion algorithms, the indirect measurements of important natural and man-made atmospheric constituents, including Carbon Dioxide (CO2)
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Experience in Sustainable Aviation Technology ENDEAVOUR Project Next Generation ATM Systems – 4D Trajectory Planning, Negotiation and Validation
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Experience in Sustainable Aviation Technology ENDEAVOUR Project Next Generation Flight Management Systems for Manned and Unmanned Aircraft
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Current Research Evolutions
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CNS+A Roadmap Key Targets and Enablers
• 4-Dimensional Trajectories • Collaborative Planning and Decision Making • System Wide Information Management • Performance Based Operations • Free Routing (User Defined Trajectories)
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Operational Concepts
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Operational Concepts Key SESAR/NextGen concepts: •
Moving from Airspace to Trajectory/Intent Based Operations
•
Collaborative planning so that all parties involved in the flight management can participate to the enhancement of the overall performance that the system will deliver
•
Dynamic airspace management (civil/military coordination) and dynamic tactical allocation of airspace resources
•
Migration from voice-based to data-driven communications
• Humans as central decision-makers •
Improved HMI2, interoperability and overall automation
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SESAR Evolutionary Roadmap
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Enabling the CNS+A Concept • Multi-Objective 4D Trajectory Optimisation (MOTO-4D) • Next Generation Flight Management System (NG-FMS) • 4DT Planning, Negotiation and Validation (4-PNV) • Next Generation Airborne Data Link (NG-ADL)
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CNS+A Operational Tasks Time Domain EMERGENCY
TACTICAL ONLINE
STRATEGIC ONLINE
10 minutes before hazard 20 minutes before hazard
CNS+A Systems are conceived for the ONLINE phase and focus on the STRATEGIC and TACTICAL scenarios TACTICAL OFFLINE
STRATEGIC OFFLINE
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NG-FMS Concept Next Generation Flight Management System (NG-FMS)
The NG-FMS development is focused on 4-Dimensional Trajectory functionalities and air-ground trajectory negotiation/validation capabilities, including: • Multi-Objective 4D Trajectory Optimisation
• 4D Trajectory Monitoring • Real-time rerouting and information updating • 4D Trajectory Negotiation/Validation
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Multi-Objective Trajectory Optimisation Engine and Emissions Model
Operational Business Model
Airframe Systems Model
ATM Model
Demographic Database
Multi Objective 3D/4D Trajectory Optimisation Globally Optimal Green Trajectories
Noise Model
2D
Terrain Database Weather Model © RMIT University
Aircraft Dynamics Model
Contrails Model
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NG-FMS General Architecture Integrity Flag
TRAJECTORY VALIDATION GroundInitiated Negotiation
Updated Trajectories
AircraftInitiated Negotiation
PATH CORRECTOR
PSE
TRAJECTORY MONITOR
Estimated/Predicted Manoeuvre & PSE
Constraints, Flyable Path
4DT Intent
TRAJECTORY PLANNER/OPTIMISER 4DT Optimiser Constraint Pool
Model Pool
ATM Operational Constraints/ Flight Plan Constraints
Aircraft Performance and Motion Constraints
Airspace Condition Constraints
Airline Constraints Performance Weightings
Aircraft Performance Model Earth Model Atmospheric Model
Cost Functions Min. Fuel/Emission Min. Cost
Min. Contrail
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Min. Time Min. Noise
Noise Model
Trajectory Uncertainty Buffer (RNP Manager) PDE
NSE
PSE
Error Aggregation yes
Contrail Model
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< 2xRNP?
no
Trajectory Optimisation and Flight Phases Green cruise
Green departure
T/O
Climb
Cruise
Green approach
Descent
Approach
Noise NOx Contrails CO2 Fuel
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NG-FMS Functions and Objectives CO2 emissions reduction -1 to 2% during cruise No persistent condensation trails formation
Noise reduction -2dB for low altitude segment
NOx emissions: any reduction, to assess
CO2 emissions reduction 15% during climb phase
Optimised multi step
Noise reduction -3dB for low altitude segment CO2 emissions reduction 10% during descent and approach phases NOx emissions: any reduction, to assess
NOx emissions: any reduction, to assess
Improved CDA
MCDP
T/O
Climb
Cruise
Descent
Approach
Env. Performance targets broken down into function objectives
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NG-FMS 4D Trajectory Optimisation •
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NG-FMS 4D Trajectory Optimisation Priority
Weightings Kfuel
Ktime
Knoise
Kweather
cell
Priority 1
Kfuel1
Ktime1
Knoise1
Kweather
cell1
Priority 2
Kfuel2
Ktime2
Knoise2
Kweather
cell2
Priority 3
Kfuel3
Ktime3
Knoise3
Kweather
cell3
•
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NG-FMS Dynamics Models • Both 6-DOF and 3-DOF flight dynamics models with variable mass can be used to propagate the aircraft state vector • The different flight phases (and associated manoeuvres) are considered: Climb, Cruise and Descent
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NG-FMS 3-DOF Error Propagation wx Lon Rt wy Lat Rm wh
h
n phi
Hdg FPA
g CL rho
K CD CDz
D
V
S
C
5 fuel consumption coefficients P
State variables
T
m
12 thrust coefficients
Control variables Other parameters
Parametric Uncertainty Propagation
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wx: along-track wind velocity Rt: Transverse radius of curvature wy: cross-track wind velocity Rm: Meridional radius of curvature wz: vertical wind velocity n: load factor phi: bank angle g: gravity CL: lift coefficient K: drag factor CDz: lift-independent drag S: gross wing area P: engine power setting rho: air density D: drag c: specific-fuel consumption T: thrust h: altitude FPA: flight path angle Hdg: heading V: velocity m: aircraft mass Lat: Latitude Lon: Longitude
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NG-FMS 4D Trajectory Optimisation For validation, an AIRBUS A380 aircraft taking off from London Heathrow airport (EGLL) and landing at Atlanta International Airport (KATL) is simulated Item
Latitude
Longitude
Radius
N 51o 29’ 8.41”
W 0o 28’ 0.01”
-
NFZ 1
N 51o 54’ 0”
W -2o 15’ 0”
4.3 NM
NFZ 2
N 51o 44’ 58”
W -1o 10’ 0”
2.7 NM
Weather Cell 1
N 38o 5’ 0”
W -70o 0’ 0”
80 NM
Weather Cell 2
N 40o 0’ 0”
W -38o 0’ 0”
80 NM
PCFR 1
N 43o 0’ 0”
W -50o 0’ 0”
350 NM
PCFR 2
N 45o 0’ 0”
W -20o 0’ 0”
350 NM
N 33o 38’ 12.01”
W -84o 25’ 43.79”
-
Initial Waypoint
Final Waypoint
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NG-FMS 4D Trajectory Optimisation Trajectory Reference No.
Time (s)
Fuel Burn (KG)
CO2 (KG)
NOx (KG)
Trac-1-cl (min-time)
725.0
6091.4
19066.08
85.89
Trac-2-cl (0.1*fuel+0.9*time)
728.5
5486.7
17173.37
77.36
Trac-3-cl (0.2*fuel+0.8*time)
739.9
5434.9
17011.24
76.63
Trac-4-cl (0.3*fuel+0.7*time)
746.2
5415.9
16951.77
76.36
Trac-5-cl (0.4*fuel+0.6*time)
750.2
5407.5
16925.48
76.25
Trac-6-cl (0.5*fuel+0.5*time)
755.7
5400.6
16903.88
76.15
Trac-7-cl (0.6*fuel+0.4*time)
758.9
5398.0
16895.74
76.11
Trac-8-cl (0.7*fuel+0.3*time)
760.0
5395.5
16887.92
76.08
Trac-9-cl (0.8*fuel+0.2*time)
764.6
5395.1
16886.66
76.07
Trac-10-cl (0.9*fuel+0.1*time)
766.5
5388.6
16866.32
75.98
Trac-11-cl (min-fuel)
766.0
5387.4
16862.56
75.96
Fuel reduction : Minimised CO2: 2204 Kg – Minimised and Nox: 10 Kg Time required for each trajectory generation :