Analyzing & ImplementingDelayed Deceleration Approaches
DISTRIBUTION STATEMENT A. Approved for public release: distribution unlimited. © 2017 Massachusetts Institute of Technology
12th USA/Europe ATM Research & Development Seminar, Seattle, WAJune 26-30, 2017
Tom G. Reynolds, Emily Clemons& Lanie Sandberg
R. John Hansman & Jacquie Thomas
DDA - 2TGR 5/5/17
Aircraft Operations Environment Assessment
• Initial scoping study to identify & evaluate operational techniques to reduce fuel burn and environmental impacts in the near/mid-term with minimal implementation barriers*
• Objectives: – Identification, evaluation
and prioritization of 60+options
– Detailed analysis of benefits &barriers of promising options
• Cruise Altitude and SpeedOptimization
• Delayed Deceleration Approaches
– Promote deployment of best practice operations• Socialization with stakeholders
• Integration strategies for current & future operations
Surface (S):16 mitigations
Departure (D):11 mitigations
Approach (A)& Landing (L)9 mitigations
Cruise (C):14 mitigations
Miscellaneous (M): 11 mitigations
ORIGINAIRPORT
DESTINATIONAIRPORT
*Marais, K., et al., “Evaluation of Potential Near-term Operational Changes to Mitigate Environmental Impacts of Aviation”, Journal of Aerospace Engineering, Vol. 227, No. 8.
DDA - 3TGR 5/5/17
• Keep aircraft “clean” for longer on approach when appropriate without impacting terminal area entry or final approach stabilization criteria– Between these
speed gates, opportunity for encouraging moreefficient approachspeed profiles
Delayed Deceleration Approach (DDA) Concept
Distance to touchdown
AirspeedTypicalConventional
Terminal areaentry speed
Final approachspeed
Sample flap 1
Sample flap 2
Runway
Delayed Decel.=> Low Power/
Low Drag
“Clean” configuration
“Dirty”configuration
230-250kts IAS
160-180kts IAS
Airspeed
Distance to Touchdown ≈10 NM≈30 NM
DDA - 4TGR 5/5/17
• Delayed Deceleration Approach (DDA) Concept
• DDA fuel burn and emissions reduction potential
• Analyzing speed profiles and barriers at US airports
• Noise analysis
• Implementing DDA via RNAV procedures
• Conclusions & Recommendations
Outline
DDA - 5TGR 5/5/17
DDA Benefits Potential
A320 performanceprofiles
European A320 Flight
Data Recorder Analysis
(similar results for B757 & B777)
30-50% fuel burn reduction potential from DDAs from 10,000 ft to touchdown
30-50% fuel burn reduction potential from DDAs from 10,000 ft to touchdown
• Lowest fuel burn flights (green profiles) associated with delayed deceleration
(NM)
(NM)
(NM)
(NM)
DDA - 6TGR 5/5/17
System-Wide DDA Benefit Potential
• Estimated system-wide fuel saving benefits potential of increased DDA utilization
y = 0.7465x + 89.752R² = 0.847
0
50
100
150
200
250
300
350
400
0 50 100 150 200 250 300 350 400
Maximum Gross Take-Off Weight (metric tons)
DD
A F
ue
l S
avin
gR
ela
tive
to
Ave
rag
e (
lbs
)
A320
B757
B777
RJ Small NB
Large NB Two Engine WB
Four Engine
WB
Based on FDR analysis
Aircraft Weight Class
Example Aircraft Types
DDASaving
per Approach
Approx # Flights
perDay
FuelReduc-
tion Benefit
Pool (gal/yr)
$ Annual Savings per 1% Inc. in DDAUse*
RJ CRJERJ 120 7500 49m $1.5m
Small NB A320 B737 146 14,400 115m $3.5m
Large NB B757 183 1,800 18m $0.5m
Two Engine
WB
A330 B777 276 3,900 59m $1.8m
Four Engine
WB
A340 B747 375 2,400 49m $1.5m
Totals 30,000 290m $8.8m
* FAA investment analysis recommended fuel price*FAA investment analysis recommended fuel price of $3.02/gal
DDA - 7TGR 5/5/17
• Delayed Deceleration Approach (DDA) Concept
• DDA fuel burn and emissions reduction potential
• Analyzing speed profiles and barriers at US airports
• Noise analysis
• Implementing DDA via RNAV procedures
• Conclusions & Recommendations
Outline
DDA - 8TGR 5/5/17
Fuel Burn Correlations with Other Observable Metrics
• Need to find correlations between fuel burn and states observable in US radar track data
• Correlation analysis identified Airspeed and Time with Flap1 as main drivers of fuel burn– Flap1 speed
180-210 kts for most “large” aircraft
Time flown below 180kts used as proxy for fuel burn for large weight category aircraft
DDA - 9TGR 5/5/17
• Analyzed speed profiles at range of US airports– Capacity-constrained standalone airports (ATL, LAX, BOS, CLT)– New York metroplex airports (EWR, JFK, LGA)– Washington DC metroplex airports (DCA, IAD, BWI)– Capacity-unconstrained standalone airports (STL, RIC, DFW)
• 9 months of radar archives from 2011 and 2015• Ground speed converted to airspeed using NARR wind data
Quantifying Speed Profiles at US Airports
Airspeed Estimation
DDA Analysis Metrics
Fuel Efficiency:Time Flown
Below
Throughput Efficiency: Minimum Approach Spacing
DDA Opportunity Evaluation
WindData
Radar Archives
DDA - 10TGR 5/5/17
ATL Approach Speed Analysis
Airspeeds█ <= 210KIAS █ <= 180KIAS
20 NM
ATL
“Large” aircraft arrivals from ZDC,4 sample days
DDA - 11TGR 5/5/17
ATL Approach Speed Analysis
• Time flown below 180 kts correlated most strongly with fuel burn for “large” aircraft type
• Cumulative curves of time flown below 180 kts used as key airport speed metric
Arrivals from ZDCJAN – SEP 2011
DDA - 12TGR 5/5/17
NYC Metroplex Approach Speed Analysis
• Earlier decelerations generally observed under IMC compared to VMC
• LGA under IMC has earliest decelerations
EWRJFK
LGA
EWR█ <= 210KIAS█ <= 180KIAS
LGA█ <= 210KIAS█ <= 180KIAS
JFK█ <= 210KIAS█ <= 180KIAS
15 mi
Arrivals from ZDC, 8 sample days 1 3 5 7 9 11 13 150
20
40
60
80
100
Time Flown Below 180 kt (min)
Perc
enta
ge o
f All
Land
ings
LGA VMC n = 10,530LGA IMC n = 1,600JFK VMC n = 9,070JFK IMC n = 1,048EWR VMC n = 4,435EWR IMC n = 775
Arrivals from ZDCJAN – SEP 2011
DDA - 13TGR 5/5/17
Airport Approach Speed Profile Comparison
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
DCA LGA EWR BOS IAD JFK BWI LAX ATL RIC STL
VMC IMC Weighted
Time F
lown
Belo
w 18
0 kts
for 5
0% o
f Flig
hts
(min
s) Arrivals from ZDCJAN – SEP 2011
Unconstrained standalone
Constrained metroplex
DDA - 14TGR 5/5/17
• Need to understand causes of differing speed profiles to identify opportunities for increased DDA operations– If primary drivers to encourage greater DDA usage are easily
modifiable (e.g., ATC training or procedures) => good target airports– More difficult to increase DDA-type procedures at airports where
primary drivers are elements such as airspace or airport constraints
• Created decision trees to find combinations of independent variables correlated with time flown below 180kts
• Independent Variables– Weather (VMC or IMC)– Hourly Airport Acceptance Rate (AAR)– Total arrival demand (15 min bins)
Analyzing Drivers of Speed Profiles
– Airport configuration– Airline
DDA - 15TGR 5/5/17
Classification Tree Approach
• Technique identified key drivers of approach speed profiles
1. Weather conditions (VMC vs. IMC)
2. Dominant operator3. Airport configuration4. Higher capacities
(AAR)
• Relative importance varies by airport
• Dominant carrier influence suggests airline procedural effect
Wx=VMC
Config=West flow
AAR >= 107.5
ArrDem >= 18.5
AAR >= 113 AAR >= 114.5
AAR >= 118.5
Airline=Delta
Condition
4
4
4
3
3 2
2
1
1
1: t < 1222: 122 <= t < 1693: 169 <= t < 2674: t >= 267
Time Flown Below 180kts (s)
ATL Example
AAR = Airport Acceptance Rate (per hr)ArrDem = Arrival Demand (per 15 mins)
DDA - 16TGR 5/5/17
• Delayed Deceleration Approach (DDA) Concept
• DDA fuel burn and emissions reduction potential
• Analyzing speed profiles and barriers at US airports
• Noise analysis
• Implementing DDA via RNAV procedures
• Conclusions & Recommendations
Outline
DDA - 17TGR 5/5/17
• Airframe and engine noise both important during approach & landing
DDA Noise Impacts
Landing gearnoiseEngine
noise
Airframenoise
Noise“hot spots”
Empirical & modeling studies conducted to understand DDA noise impacts
DDA - 18TGR 5/5/17
BOS Noise Measurement CampaignMeasurement Period: 11/13/15 – 1/25/16
Airport Selection For DDA Feasibility
DDA Opportunity Analysis
Noise Monitor Site Selection
Noise Measurement Campaign
Noise & Aircraft Track Analysis
Research Outputs:• Noise modeling validations• Noise as f(speed, configuration,
approach procedures, aircraft type)
Airline Standard Operating
Procedures, Flap Schedules, etc.
Radar Flight Track Data
50 100 150 200 250 300 350 400 450 500
50
100
150
200
250
300
350
400
450
500
BOS
Runway 22L/22R ArrivalsJan-Mar and Jun-Aug 2014
5 nmi 0
100
200
300
400
500
600
700
800
900
1000
No
. o
f R
ad
ar
Su
rve
illa
nc
e H
its
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
DCA LGA EWR BOS IAD JFK BWI LAX ATL RIC STL
VMC IMC Weighted
Tim
e Fl
own
Belo
w 1
80 k
ts fo
r 50%
of F
light
s (m
in)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
DCA LGA EWR BOS IAD JFK BWI LAX ATL RIC STL
VMC IMC Weighted
Tim
e Fl
own
Belo
w 1
80 k
ts fo
r 50%
of F
light
s (m
in)
DDA - 19TGR 5/5/17
• Slight negative trends indicate marginal decrease in noise with increasing airspeed on average
• Similar results for Lmax
Noise Measurement Results
Linear fit slope: -0.01 Linear fit slope: -0.03 Linear fit slope: -0.06
Linear fit slope: 0.00 Linear fit slope: -0.02 Linear fit slope: -0.05
Linear fit slope: -0.03 Linear fit slope: -0.02 Linear fit slope: -0.01
A320(n=135)
Monitor A
B737(n=163)
E190(n=58)
A320(n=269)
B737(n=295)
E190(n=112)
Monitor B Monitor CA320(n=365)
B737(n=352)
E190(n=153)
• 10-15 dBA variability in data– Not removed when correction for energy
change rate applied– Attributed to atmospheric differences
DDA - 20TGR 5/5/17
TASOPT, BADA4 & ANOPPModel Integration
DDA - 21TGR 5/5/17
• Modeled range of approaches with different aircraft types & profiles
Modeling of EnhancedDDA Operations
AirframeOnly
EngineOnly
Total Airframe& Engine
A320
Overall, negligible effect of DDA speed profiles on noise impacts on ground
DDA - 22TGR 5/5/17
• DDA fuel burn and emissions reduction potential
• Analyzing speed profiles and barriers at US airports
• Noise analysis
• Implementing DDA via RNAV procedures– Feasibility of RNAV procedures for DDA implementation– Design considerations for RNAV DDAs– Assessing RNAV Procedure Targets
• Conclusions & Recommendations
Outline
DDA - 23TGR 5/5/17
Assessing Feasibility of RNAV DDAs
• Biggest uncertainty in effective implementation of DDA: track distance to touchdown– PBN (RNAV/RNP) approach
procedures reduce uncertainty
• Simulated approaches with:– Same programmed
lateral/vertical route as published RNAV arrivals
– Different speed constraints– Different aircraft weights
• Utilized Lincoln FMS analysis capability– Pegasus FMS flight code– Integrated to B757-200
simulation
-84.4 -84.2 -84 -83.833.6
33.7
33.8
33.9
34
34.1
Longitude (deg)
Latit
ude
(deg
) 200K
200K
185K
175K
ATLZELOW20NM
BAMMM27NM
HAARY40NM
DIRTY49NM
150K
BAMBU10NM
160K 200K
230K
250K
250KATL DIRTY RNAV Arrival to Runway 26R
Late decel.profileEarly decel. profile
DDA - 24TGR 5/5/17
0
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400
600
800
1000
1200
1400
1600
1800
Scenario 1: Late decel.
Scenario 2: Medium decel.
Scenario 3: Early decel.
Aircraft Weight
Fuel
Bur
n In
side
TR
AC
ON
40 N
M to
50
ft A
GL
(lbs)
Light Medium Heavy
Simulated B757 ATL RNAV DDA Arrivals
• Early deceleration shown to use 54% more fuel in TRACON compared to late
• Late deceleration fuel burn shows the least sensitivity to aircraft weight
Deceleration Profile Late Medium Early
TRACON Duration 12 mins 14 mins 15 mins
TRACON Fuel Use 1030 lbs 1347 lbs 1588 lbs
TRACON Fuel Use Relative to Lowest - +31% +54%
DDA - 25TGR 5/5/17
Design Considerationsfor RNAV DDAs
• For RNAV DDA procedures to be practically useful, need to minimally modify existing procedures and be flyable by different types
• Evaluated speed envelope for range of representative profiles and aircraft types
• Significant differences in deceleration profiles observed between types
Based on BADA 4 analysis
Need to account for aircraft deceleration capabilities in RNAV DDA design
DDA - 26TGR 5/5/17
• Modeled fuel burn on BOS ROBUC2 RNAV arrival with four different speed profiles
• Significant difference between “B757 latest” and “a/c type latest”– Trade-off between procedure simplicity and fuel saving
Comparison of Fuel Saving with Different Speed Profiles for Different Types
0
200
400
600
800
1000
1200
A320 B737 B757 B777
Empirical earlyROBUC2 publishedB757 latestA/c type latest
23%-1% -15%
Ref19%
0%-23%
Ref
53%
-8%-8%Ref
35%
-24%-34%
Ref
Fuel
Bur
n R
OB
UC
to
Tou
chdo
wn
(kg)
Based on BADA 4 analysis
DDA - 27TGR 5/5/17
• Compared speed profiles of range of current RNAV arrivals compliant with– “As published” speed targets– Latest speed profile flyable by B757 reference aircraft
Assessment of Current RNAV Arrival Speed Targets
Distance to Touchdown (NM)
Indi
cate
d Ai
rspe
ed (k
ts)
BOS/ROBUC/4R/as publishedBOS/ROBUC/4R/B757 latestBOS/JFUND/15R/as publishedBOS/JFUND/15R/B757 latestCLT/FILPZ/36L/as publishedCLT/FILPZ/36L/B757 latestCLT/FILPZ/18R/as publishedCLT/FILPZ/18R/B757 latestRNAV procedure speed targets
Airport/RNAV proc/rwy/speed profile
DDA - 28TGR 5/5/17
• Area between lines indicates how close published procedure speed targets are to B757-optimized speed profile– Area comparison methodology proposed as a procedure efficiency
screening tool
Assessment of Current RNAV Arrival Speed Targets
Area
Bet
wee
n R
NAV
Spe
ed T
arge
t Com
plia
nt&
B75
7 La
test
Spe
ed P
rofil
e C
urve
s (N
M.k
ts)
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Incr
easi
ng R
NA
VFu
el E
ffici
ency
Dec
reas
eing
RN
AV
Fuel
Effi
cien
cy
DDA - 29TGR 5/5/17
• Delayed Deceleration Approach (DDA) Concept
• DDA fuel burn and emissions reduction potential
• Analyzing speed profiles and barriers at US airports
• Noise analysis
• Implementing DDA via RNAV procedures
• Conclusions & Recommendations
Outline
DDA - 30TGR 5/5/17
• DDA is a promising concept for reducing approach fuel & emissions
• Radar analysis and classification tree approach provides insight into airports with highest benefit potential and lowest barriers
• Noise analysis showed negligible effects of DDA on noise impacts on ground
• RNAV arrival procedures offer a promising implementation path
• Tools presented for identifying RNAV arrival procedure candidates for modified speed targets to gain DDA benefits
Conclusions
DDA - 31TGR 5/5/17
• Further promote DDA concept to relevant stakeholders– ATC facilities, Airlines/flight crews, Procedure designers
• Use proposed methodologies and tools to undertake:– Wider screening of existing procedures– Identify candidates for re-design process– Redesign, analyze and deploy appropriate modified procedures to
realize DDA benefits in operational system
• Assess human factors implications of DDA on ATC and flight crews
• Explore how new automation (e.g., TSS) could be leveraged to promote DDA
Recommended Next Steps
TSS = Terminal Sequencing and Spacing
DDA - 32TGR 5/5/17
Acknowledgments & Disclaimer
Many thanks for Chris Dorbian, Aniel Jardines, Stephen Merlin &James Hileman of the FAA Office of Environment & Energy forsupporting this work.
DISTRIBUTION STATEMENT A. Approved for public release: distribution unlimited. Thismaterial is based upon work supported by the Federal Aviation Administration under Air ForceContract No. FA8721-05-C-0002 and/or FA8702-15-D-0001. Any opinions, findings, conclusionsor recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the FAA.
© 2017 Massachusetts Institute of Technology.
Delivered to the U.S. Government with Unlimited Rights, as defined in DFARS Part 252.227-7013 or 7014 (Feb 2014). Notwithstanding any copyright notice, U.S. Government rights in thiswork are defined by DFARS 252.227-7013 or DFARS 252.227-7014 as detailed above. Use ofthis work other than as specifically authorized by the U.S. Government may violate anycopyrights that exist in this work.
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