Project manager: Pat Moran, FAA Principal Investigator: Juan J. Alonso, Stanford University Funded under FAA Award Nos.: 09-C-NE-SU, Amendment No. 002 09-C-NE-MIT, Amendment No. 005 09-C-NE-GIT, Amendment No. 012 Opinions, findings, conclusions and recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of PARTNER sponsor organizations. 19 th Advisory Board Meeting October 16-18, 2012 Arlington, VA
Transcript
Project manager: Pat Moran, FAA Principal Investigator: Juan J. Alonso, Stanford University
Funded under FAA Award Nos.: 09-C-NE-SU, Amendment No. 002 09-C-NE-MIT, Amendment No. 005 09-C-NE-GIT, Amendment No. 012
Opinions, findings, conclusions and recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of PARTNER sponsor organizations.
19th Advisory Board Meeting October 16-18, 2012
Arlington, VA
2
Team Members
• Interdisciplinary team assembled to cover all necessary aspects of this system-level study:
– Stanford University: Juan J. Alonso – MIT: John Hansman – Georgia Tech: Michelle Kirby – Booz-Allen-Hamilton: Philippe Bonnefoy – Volpe Center: David Senzig
• ICAO/CAEP report from Independent Experts on Fuel-Burn Reduction Technology Goals presented a preliminary assessment of potential fuel burn reductions resulting from changes in future aircraft design with different mission specifications:
• Significant fuel-burn savings are possible with today’s technology and such design changes could be used to minimize the risk inherent in the cost-effective realization of future technologies
4
Motivation
• However, the system-level impacts of such design changes are not clear.
• Can we quantify these impacts?
• Can we get a handle on any unintended consequences?
• How would such aircraft integrate into NextGen?
• Under which conditions could these aircraft be operated cost effectively?
5
Objectives
• Main Objective: Quantify the system-level impacts of mission specification changes in future aircraft designs so that information is available to better evaluate the potential of this approach to reduce fuel burn and aviation’s environmental impact
• Understand impact on airline operations / economics
• System-level cost/benefit analysis
• Impact on NAS operations and relationship with NextGen ConOps
6
Outcomes and Practical Applications
• Assessment of impact of aircraft mission changes (including degree of certainty) on fuel burn of different aircraft types
• Assessment of impacts of airline and airport operations and economics
• Fleet-wide models for future scenarios
• Assessment of impact on NextGen ConOps
• Low- and high-fidelity models for additional studies that may need to be pursued
• Identification of gaps to be filled for future studies that will leverage PARTNER tools
7
Approach
• Four tasks, each led by a member of our team: SU, GT, MIT, Booz-Allen Hamilton, with support from the Volpe Center
• Integrated milestones to account for interdependencies
• Meta model and high-fidelity models to guide system-level assessments
• Coordinated effort
8
Coordination between Tasks
Baseline Aircraft
Mission Spec Changes
Airline impacts of cruise and range changes!
Range"
Payl
oad"
Short-Range"(SR)!
Long-Range"(LR)!
Economic Analyses!
System-Level Propagation
System-Level Impacts
Future Fleet Models Environmental Impacts
Air-Traffic and Infrastructure Impacts
Accommodation potential / changes
Airport gates ATC
9
Schedule and Status
• 4 Tasks in Project 43 began in April-May 2011
• Official period of performance: April 1, 2011-March 31, 2013
• All tasks proceeding according to plan
10
Task 1 Status: Analysis of Aircraft Alternatives for Mission Specification Changes
• Fuel burn reduction possibilities, compared to baseline aircraft, has been predicted for current and 3 future technology scenarios TS1,TS2,TS3 for years 2020 and 2030.
• Variations in mission specifications also included: – R1 range (design range being discussed) – Cruise Mach number – Maximum allowable span
• Ongoing work includes the development of technology packages that integrate plausible technology choices (for each TS and time frame) onto different aircraft classes
Task 1 Status: Technology Scenarios
12
• Baseline aircraft (current tech) model construction and validation
• Mission specification definition, a combination of: – Cruise Mach number – R1 range – Maximum allowable span
• Full airframe / engine optimization for minimum fuel burn
• Assessment of resulting aircraft performance
• Parameter sweeps for input to Task 2
Task 1 Status: Aircraft Performance Assessment Process
from ICAO/CAEP LTTG Steering Group meeting report"
The following technology improvements were used in all aircraft redesigns"
14
FUEL BURN IMPROVEMENTS
B737-800!PARAMETER
VARIED BASELINE MACH RANGE SPAN MACH-RANGE SPAN-MACH
MACH(increased tolerance)
% Fuel burn reduc,on compared to baseline Technology
Level
Baseline
-‐5.62% S=117.02,M=0.799,
R=3933
-15.46%!S=117.02,M=0.720,R
=3933
-5.62%!S=117.02,M=0.799,
R=3740
-6.77%!S=134.98,M=0.799,
R=3933
-15.47%!S=117.02,M=0.724,
R=3936
-18.54%!S=146.72,M=0.684,
R=3937
-18.78%!S=146.70,M=0.680,
R=4637
TS1-2020
-‐24.69% S=117.02,M=0.799,
R=3933
-32.18%!S=117.02,M=0.719,R
=3933
-24.97%!S=117.02,M=0.799,
R=4715
-25.45%!S=129.37,M=0.799,
R=3933
-32.51!S=117.02,M=0.729,
R=4192
-34.31%!S=146.72,M=0.679,
R=3937
-35.32%!S=149.32,M=0.699,
R=5905
TS1-2030
-‐29.02% S=117.02,M=0.799,
R=3933
-35.95%!S=117.02,M=0.719,R
=3933
-29.49%!S=117.02,M=0.799,
R=4922
-29.77%!S=129.37,M=0.799,
R=3933
-36.44%!S=117.02,M=0.739,
R=5118
-37.92%!S=146.72,M=0.680,
R=3937
-39.20%!S=154.12,M=0.690,
R=6245
TS2-2020
-‐29.02% S=117.02,M=0.799,
R=3933
-35.95%!S=117.02,M=0.719,R
=3933
-29.49%!S=117.02,M=0.799,
R=4922
-29.775!S=129.37,M=0.799,
R=3933
-36.44%!S=117.02,M=0.739,
R=5118
-37.92%!S=146.72,M=0.680,
R=3937
-39.20%!S=154.12,M=0.690,
R=6245
TS2-2030
-‐33.62% S=117.02,M=0.799,
R=3933
-39.93%!S=117.02,M=0.729,R
=3933
-34.25%!S=117.02,M=0.799,
R=5305
-34.34%!S=129.37,M=0.799,
R=3933
-40.63%!S=117.02,M=0.739,
R=5501
-41.74%!S=147.021,M=0.69
0,R=3937
-43.34%!S=157.740M=0.689
,R=6679
TS3-2030
-‐42.80% S=117.02,M=0.799,
R=3933
-48.26%!S=117.02,M=0.709
,R=3933
-44.12%!S=117.02,M=0.799,
R=6287
-43.27%!S=129.37,M=0.799,
R=3933
-49.55%!S=117.02,M=0.740,
R=6300
-49.56%!S=141.14,M=0.680,
R=3937
-51.09%!S=140.87,M=0.75,
R=6687
Mach (increased tolerance) implies that the fuel burn is computed for a range of Mach numbers with the span and range values not constrained at all. SYMBOLS : S-SPAN(ft), M-MACH, R-RANGE(km)"
15
• Significant improvements are possible for baseline technology aircraft: – Cruise Mach number reductions (down to 0.65) can result in decreases in
fuel burn of approx 10% – Range variation is not very effective in reducing fuel burn for the B737-800 – Span changes alone are not very effective – Combinations of cruise Mach and span lead to 13.5% fuel burn reductions
• Combining mission specification changes with technology improvements, very significant fuel burn decreases are possible, on the order of 50% for the most aggressive technologies in 2030
• Note: results are purely aircraft designs whose mission spec parameters might not be economically feasible. Input to Task 2
• Relative impact (on fuel burn) of mission spec changes is only slightly diminished with more advanced aircraft technology
PARAMETER VARIED BASELINE MACH RANGE SPAN MACH-RANGE SPAN-MACH
MACH(increased tolerance)
% Fuel burn reduc,on compared to baseline
Technology Level
Baseline
-‐16.65% S=199.1,M=0.840,
R=10649
-28.46%!S=199.1,M=0.680,R
=10649
-22.84%!S=199,M=0.839 ,R
=5319
-16.65%!S=199.29,M=0.840,R
=10649
-34.23%!S=199.1,M=0.665,R
=4797
-30.45%!S=238.97,M=0.675,R
=10649
-33.77%!S=221.59,M=0.670,
R=5201
TS1-2020
-‐30.87% S=199.1,M=0.840,
R=10649
-40.33%!S=199.1,M=0.680,R
=10649
-34.27%!S=199,M=0.839,R
=5851
-30.87%!S=198.90,M=0.840,R
=10649
-43.27%!S=199.1,M=0.670,R
=6915
-42.09%!S=239.15,M=0.670,R
=10649
-44.33%!S=229.70,M=0.660,
R=5977
TS1-2030
-‐38.68% S=199.1,M=0.840,
R=10649
-47%!S=199.1,M=0.670,R
=10649
-40.86%!S=199,M=0.839,R
=6383
-38.68%!S=198.90,M=0.840,R
=10649
-48.32%!S=199.1,M=0.680,R
=7979
-48.63%!S=248.62,M=0.670,R
=10649
-49.94%!S=232.89,M=0.660,
R=7073
TS2-2020
-‐36.16% S=199.1,M=0.840,
R=10649
-44.75%!S=199.1,M=0.680,R
=10649
-38.72%!S=199,M=0.839,R
=5863
-36.16%!S=198.90,M=0.840,R
=10649
-46.71%!S=199.1,M=0.680,R
=7462
-46.49%!S=248.62,M=0.665,R=1
0649
-48.09%!S=232.63,M=0.660,
R=6698
TS2-2030
-‐43.37% S=199.1,M=0.840,
R=10649
-50.95%!S=199.1,M=0.680,R
=10649
-44.95%!S=199,M=0.839,R
=6915
-43.37%!S=198.90,M=0.840,R
=10649
-51.73%!S=199.1,M=0.680,R
=9042
-52.55%!S=248.62,M=0.665,R
=10649
-53.22%!S=234.65,M=0.660,
R=8073
TS3-2030
-‐48.15% S=199.1,M=0.840,
R=10649
-54.95%!S=199.1,M=0.680,R
=10649
-49.18%!S=199,M=0.840,R
=7462
-48.15%!S=198.90,M=0.840,R
=10649
-55%!S=199.1,M=0.695,R
=10127
-56.49%!S=248.62,M=0.665,R
=10649
-56.65%!S=243.83,M=0.660,
R=9060
Mach (increased tolerance) implies that the fuel burn is computed for a range of Mach numbers with the span and range values not constrained at all. SYMBOLS : S-SPAN(ft), M-MACH, R-RANGE(km)"
17
• Significant improvements are possible for baseline technology aircraft: – Cruise Mach number reductions (down to 0.65) can result in decreases in
fuel burn of approx 14% – Range variation is more effective in reducing fuel burn: 7.5% – Span changes alone are not very effective – Combinations of cruise Mach and range lead to 21% fuel burn reductions
• Combining mission specification changes with technology improvements, very significant fuel burn decreases are possible, on the order of 50% for the most aggressive technologies in 2030
• Note: results are purely aircraft designs whose mission spec parameters might not be economically feasible. Input to Task 2
• Relative impact (on fuel burn) of mission spec changes is only slightly diminished with more advanced aircraft technology
Task 2 Status: Implications of Mission-Related Changes on Airline Operations and Economics
Objective:
• Develop an understanding of key trades and net impacts of mission specification changes on airline operations and economics
• Identify segments of the fleet most likely to adopt aircraft with mission specification changes
Approach:
• Collect data for airlines’ economics and operations model including FAA Aviation System Performance Metrics (ASPM), U.S. Bureau of Transportation Form 41, On-Time, and other relevant databases and literature sources
• Develop airline operations and economics models
• Conduct sensitivity analyses of changes to mission specifications on airlines’ net benefits
Scope of the Investigation:
• Considered and scoped potential for improvement from five potential mission specification changes
• Focused on two mission specification changes: – Design cruise speed reduction – Single vs. multi-range variant fleet
19
Task 2 Status: Design Cruise Speed Reduction: Approach to Evaluating Costs vs. Benefits
Objective: Evaluate the impacts of design cruise speed reductions (CSR) on airline operations and economics
Approach/Methodology: • Developed a cost benefit analysis model to evaluate fuel burn benefits vs. resulting costs from CSR
• Developed an airline schedule optimization module (with connecting flight constraints) to mitigate and derive expected impacts of CSR
• Computed economics impacts (i.e. labor, maintenance, depreciation/rental/lease) using BTS, EuroControl method and other literature sources
• Fuel burn benefits derived from Task I output and actual operations
• Conducted sensitivity analysis of CSR on fuel burn benefits vs. costs
• Applied model to CRJ900, B737, and B777 (so far)
Overview of the Cruise Speed Reduction Model
20
-‐1.5%
-‐1.0%
-‐0.5%
0.0%
0.5%
1.0%
% Differen
ce in Cost
from
Base Ca
se
-‐2%
-‐1%
0%
1%
2%
-‐20% -‐15% -‐10% -‐5% 0%
% Differen
ce in Cost from Base Ca
se
% ReducAon in Cruise Speed
Task 2 Status: Evaluation of Costs vs. Benefits of Design Cruise Speed Reduction
Preliminary Results and Observations: • Reduction in Design Cruise Speed can yield net benefits (i.e. fuel cost
savings can outweigh increases in labor/maintenance costs) • Results are sensitive to aircraft level fuel burn performance.
Ben
efit
Cos
t
Large Twin Aisle (i.e. B777-200ER)
Ben
efit
Cos
t
Sensitivity to Cruise Speed Reduction
-‐2.0%
-‐1.0%
0.0%
1.0%
2.0%
-‐12% -‐10% -‐8% -‐6% -‐4% -‐2% 0%
% Differen
ce in Cost from Base Ca
se
% ReducAon in Cruise Speed
$3 per Gal Fuel
$4 per Gal Fuel
$5 per Gal Fuel
$6 per Gal Fuel
Illustration: Single Aisle (i.e. B737-800)
-‐1.0%
-‐0.5%
0.0%
0.5%
1.0%
% Differen
ce in Cost from
Base Case
Breakdown of Cost Impact (5% CSR, $3 per gallon)
21
Task 2 Status: Investigation of the Implications of Single vs. Multiple Maximum Range Aircraft Variants Motivation/Key Questions:
• What is the fuel efficiency benefit derived from a closer matching of aircraft capability with mission requirements?
• What are the operational and fleet planning implications?
Objectives:
• Evaluate the net benefits of multi-range fleet versus a single range fleet on airline fleet allocation flexibility and economics • Develop a fleet optimization and fleet assignment model to determine fleet planning and allocation
Range"
Payl
oad"
Short-Range"(SR)!
Aircraft Capability*!
Mission Stage Length"
Mission Requirements*!
% o
f Flig
hts"
Benefits vs. Costs from better matching!Aircraft Range
Capabilities to Mission Requirements?!
* P43 Task 1 Input "
* BTS, ASPM data"
Short- Stage Lengt
h"(S-SL)!
Long-Range"(LR)!
Long- Stage Lengt
h"(L-SL)!
22
Task 2 Status: Analysis of Single vs. Multi-Range Variants Approach:
• Decouple airline networks into (1) itineraries flown by long-range aircraft and (2) itineraries flown by short-range variants
• Compare fuel savings to other cost implication
Methodology:
• Use airline network structure from BTS/ASPM
• Set fleet availability assumptions i.e., number of SR and LR aircraft available
• Compute fuel savings (from Task I input) i.e. savings from flying a SR instead of a LR aircraft
• Run Multi-Variant Range Optimization Model to optimize fleet allocation and itineraries subject to minimization of total fuel costs (i.e. maximize fuel savings compared to baseline case)
• Compute fuel costs savings vs. increased ownership cost
• Run sensitivity analysis on fleet composition
Multi-Variant Range Optimization Model
Flight Information from BTS/ASPM database
010
2030
4050
60
0 1000 2000 3000 4000 5000 6000Stage Length (nmi)
Freq
uenc
y
Histogram of Stage Length15 short−range aircraft
Long−Range AircraftShort−Range Aircraft
A B C
0 5 10 15 20 25 30−4
−20
24
68
10Number of short−range aircraft
Cos
ts (i
n $1
00,0
00)
Cost SavingsAcquisition Costs
UAL − B777−200 − 3/20/2010 to 3/26/2010
Itineraries & Split btw Short and Long Range Aircraft
Fuel Cost Savings vs. Increased Ownership Cost
23
Task 2 Status: Exploration of Trade Space between SR and LR Aircraft: Illustration
# L
R
Num
ber
of L
ong
Ran
ge
Airc
raft
# SR Number of Short Range Aircraft
50
50
25
25
Baseline: Single Long-Range Fleet 0 short-range aircraft
010
2030
4050
60
0 1000 2000 3000 4000 5000 6000Stage Length (nmi)
Freq
uenc
y
Histogram of Stage Length0 short−range aircraft
Long−Range AircraftShort−Range Aircraft
010
2030
4050
60
0 1000 2000 3000 4000 5000 6000Stage Length (nmi)
Freq
uenc
y
Histogram of Stage Length5 short−range aircraft
Long−Range AircraftShort−Range Aircraft
010
2030
4050
60
0 1000 2000 3000 4000 5000 6000Stage Length (nmi)
Freq
uenc
y
Histogram of Stage Length10 short−range aircraft
Long−Range AircraftShort−Range Aircraft
010
2030
4050
60
0 1000 2000 3000 4000 5000 6000Stage Length (nmi)
Freq
uenc
y
Histogram of Stage Length15 short−range aircraft
Long−Range AircraftShort−Range Aircraft
Increasing Fleet Size
5 short-range aircraft
Mixed Short and Long-Range Fleet
10 short-range aircraft 15 short-range aircraft
010
2030
4050
60
0 1000 2000 3000 4000 5000 6000Stage Length (nmi)
Freq
uenc
y
Histogram of Stage Length30 short−range aircraft
Long−Range AircraftShort−Range Aircraft
30 short-range aircraft
0
24
Task 2 Status: Multi-Range Variant Model Preliminary Results Preliminary Results and Observations: • The number of flights flown by short-range aircraft increases with the number of short-range aircraft available
• Fuel costs decrease nonlinearly when LR aircraft are progressively replaced by SR aircraft
• After a critical number of SR aircraft, the addition of SR aircraft does not yield any fuel burn benefits
• The introduction of a second variant can yield substantial fuel cost savings
• Benefits can be captured without necessarily increasing the total fleet size
Next Steps:
• Extend multi-range analyses to broader sample of airlines/networks
• Extend model results and insights to multi-stage/dynamic model
• Investigate the benefits of introducing and using flexible fleet management practices
A B C
0 5 10 15 20 25 30
−4−2
02
46
810
Number of short−range aircraft
Cos
ts (i
n $1
00,0
00)
Cost SavingsAcquisition Costs
UAL − B777−200 − 3/20/2010 to 3/26/2010
Note: Assumption - Unit fuel price = $3 per gallon
“Close to Fuel Optimum & Robust” Fleet Mix
“Fuel Optimum” Fleet Mix Bene
fit
Cost
No increased fleet size Increased fleet size
0 5 10 15 20 25 30
020
4060
8010
0
Number of short−range aircraft
Num
ber o
f airc
raft
Minimal number of long−range aircraftMinimal fleet size
UAL − B777−200 − 3/20/2010 to 3/26/2010Trade Space between SR and LR Aircraft
Fuel Cost Savings vs. Increased Acquisition Costs
25
Task 3 Status: Recent Accomplishments
• Task 3 will model system-level impacts of the adoption of mission specification change aircraft with several tools: – Global and Regional Environmental Aviation Tradeoff tool (GREAT) – Aviation Environmental Design Tool (AEDT) – Airport Noise Grid Integration Method (ANGIM)
• Task 3 progress has focused on refining connectivity to other (ongoing) tasks to facilitate ongoing work and future analyses
• Connections requiring refinement to ensure compatibility of assumptions included: – Task 1 – pass vehicle attributes to EDS to model performance
characteristics required for GREAT – Task 2 – pass EDS vehicle economic characteristics and system-level
operations forecast to Task 2 for feasibility assessment (feedback) – Task 3 – pass vehicle performance characteristics to AEDT
• Testing successful ‘handshakes’ between tasks has ensured confidence in data handoffs to enable successful accomplishment of project goals
26
• Use GREAT tool (CO2 and NOX) and ANGIM (for noise)
• Use retirement curve assumptions from FESG
• GREAT contains entire tool chain (from aircraft to impact) that will be exercised for choices of aircraft and mission spec changes provided by Tasks 1 and 2
• Additionally, AEDT will be used for a number of system-level analyses
Task 3 Status: GREAT Tool Process
27
Task 3 Status: Connectivity With Tasks 1, 2
• Refined specific design rules and assumptions with Task 1 for common modeling of vehicle specification changes – MTOW sizing point (see next slide) – Cruise speed sizing rules – Wing span, sweep
• Agreed on common operations forecast for Task 2 and Task 3 fleet level assessments – FAA TAF, using CAEP 6 weeks as datum operations, no
international arrivals, linear forecast extrapolation beyond 2030
• Confirmed aircraft economic attributes to pass to Task 2
28
Task 3 Status: MTOW Sizing
• It is not possible to maintain the exact same Payload–Range envelope as we incorporate technologies (i.e. the slope of a MTOW limit line is directly affected by fuel efficiency from fundamental physics)
• R1 and Design Point (max range at full cabin loading) were compared to identify which is more appropriate for MTOW sizing when we want to best isolate technology impacts from vehicle specification changes
• Design Point appears to be better than R1, which may increase P-R envelope and MTOW significantly
OEW" MTOW"FB"
600nm"FB"
1200nm"FB"
1800nm"
% C
hang
e re
lativ
e to
bas
elin
e"
Payl
oad
(lbs)"
Range (nm)"
Performance Improvements!by 2030 TS3 Technology!
Limited by Max Payload"
Limited by "
Fuel Volume"
full cabin loading"
R1"
29
Task 3 Status: Recent Accomplishments and Contributions
• Generic baseline and Reduced Mach Seat Class 3 (~150 passenger) aircraft generated with the Environmental Design Space (EDS) tool
• EDS aircraft data transferred to the FAA’s Aviation Environmental Design Tool (AEDT)
• For the U.S. domestic fleet used in the FAA’s 2010 Benefits inventory, the baseline and Reduced Mach aircraft were run in place of the existing Seat Class 3 aircraft
• Reduced Mach aircraft showed 1.7% fuel consumption reduction for this Seat Class (320 kilo-tonnes in the study year)
30
Task 4 Status: Impact of Increased Wingspan on Gate Infrastructure
• Objective : Investigate the impact of increased aircraft wingspan on airport gate infrastructure!
• Approach: Using operations data and gate information for 7 airports selected from the OEP 35 list, the potential for wingspan expansion for group III aircraft was investigated under two scenarios!– Expanding wingspan to use the full width of available gates"– Expanding wingspan to utilize available one or two adjacent gates "
• Results: !– Most airports provide the
opportunity for group III sized aircraft to increase wingspan to 124ft or 225ft depending on the scenario used"
– The ability to increase wingspan is limited by infrastructure at LGA and DCA, which are both perimeter resisted airports and provide very limited opportunity for increasing aircraft wingspan"
0"
20"
40"
60"
80"
100"
0" 50" 100" 150" 200" 250"
Usa
ble
Gat
es (%
)!
Wingspan (ft)!
Usable Gates vs. Wingspan: Determined by Flightstats.com!
BOS"LGA"DFW"JFK"DCA"
Gro
up I"
Gro
up II
I"
Gro
up IV"
Gro
up V"
Gro
up V
I"
Gro
up II"
31
Task 4 Status: Impact of Changes in Aircraft Speed on Air Traffic Control Conflicts
• Objective: Understand the impact of decreasing aircraft speed on the number of air traffic control conflicts
• Approach: NASA’s FACET was used to model and 8% reduction in speed for following fleet scenarios – Fraction of flights of all US flights over 24 hours – Fraction of flights by an airline over 24 hours – Fraction of flights by an aircraft class over 24 hours – Fraction of flights by an aircraft type over 24 hours
• Results"– A majority of the conflicts
observed are overtake conflicts"
– The number of conflicts increases as the speed mix in the overall US fleet increases"
– The largest observed increase in conflicts occurred when 80% of US flights were slowed down by 8%. Conflicts increased by 4.94% which resulted in 0.230 conflicts per flight, up from 0.217 conflicts per flight in the baseline case"
32
Task 4 Status: Impact of Reduced Design Range on Air Transportation System
• Objective: Understand the system level impacts of reducing commercial aircraft design range and utilizing Intermediate Stop Operations (ISO) for refueling where necessary or advantageous.
• Approach – Identification of potential ISO aircraft-level benefits for existing
and future fleet – Identification of potential ISO airline-level benefits through case
studies – Development of a network model to fly existing and future
schedules using ISO • Interaction with task 2 to incorporate potential costs
– Identification of system level impacts • Airport congestion / development • Sector traffic • Passenger quality of service
33
Task 4 Status: Benefits and Penalties from ISO
– Long range flight has only 1 TOL; ISO has 2+ – Two types of multi-segment flight penalties
• LTO penalty accounts for energy loss from multiple ascents
• Diversion penalty accounts for increased route distance
– However, carrying less fuel on each flight leg can result in an overall fuel benefit.
34
Task 4 Status: Identification of Aircraft-Level Benefits
• Utilizing ISO with the existing fleet leads to benefits up to aircraft-level benefits up to 15%
• Benefits for each aircraft are a function of the mission range – Intercept between
3,500km – 9,000km
• Maximum benefit is a function of design range
• Does not include re-designed aircraft
*ISO: 1 stop exactly halfway along great circle distance"
35
Task 4 Status: Pareto Front of Potential Benefits for Existing Aircraft
• Existing global aircraft fleet and 2006 schedule (flights >= 5,000km)
are flown using ISO operations – Flights are allowed to stop exactly halfway along GC-route, even if
no airport exists – Scenarios are filtered based on aircraft-level fuel savings for a given
