Post on 30-Jun-2018
Demand Patterns; Geometric Design of AirfieldProf. Amedeo Odoni
Airport Planning and Management
Module 4
January 2016
Istanbul Technical University
Air Transportation Management
M.Sc. Program
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Demand Patterns; Geometric Design of Airfield
q Objective:
– Review (a) Airport Demand Patterns and (b) Geometric
Design Specifications, as important background to
lectures on Airport Planning
q Topics:
– Airport Demand Patterns
• Variability of demand
• Some key observations
• Converting annual forecasts into monthly, daily and
hourly ones
– Geometric Design Specifications
• ICAO and FAA Reference Codes
• Practical observations
• Examples of specifications and their rationale
Page 3
OutlineAirport Demand Patterns
• Variability of demand
• Some key observations
• Converting annual forecasts into monthly,
daily and hourly ones
q Geometric Design Specifications
• ICAO and FAA Reference Codes
• Practical observations
• Examples of specifications and their
rationale
Airport Capacity Management: General Framework
q Capacity management refers to the steps that an
airport must take in order to offer sufficient capacity
to match demand and provide an adequate Level of
Service (LOS)
q Demand management refers to interventions aimed
at modifying demand; such interventions may be
necessary if available capacity is not sufficient to
ensure adequate LOS
q To provide and manage capacity, it is necessary to
understand well the characteristics of both demand
and capacity on both airside and landside
q The issues and the measures of LOS on airside
and on landside are quite different Page 4
Variability of Airport Demand: Time-of-Day
All airports experience time-of-day variability in demand
intensity, for a number of reasons:
– Preference of travelers for certain times of the day
(especially true for business travel)
– “Natural” times for flying on certain long-haul routes
(e.g., most flights from Eastern United States to Europe
depart between 4 PM and 11 PM)
– Curfews (typically due to noise restrictions)
At all airports, the composition of demand (arrivals vs.
departures, domestic vs. international, short-haul vs. long-
haul, business vs. leisure) also varies by time-of-day
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Variability of Airport Demandq Significant variability in demand may also exist with
respect to:
– Day of the week (e.g., in the US, Saturday is the
lowest day, Sunday is second lowest, while
weekdays are similar to one another and have the
highest demand)
– Month and season (e.g., summer vs. winter, high
and low months, influence of religious or other
holidays)
– Special events (e.g., sports, expos, etc.)
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OutlineAirport Demand Patterns
• Variability of demand
• Some key observations
• Converting annual forecasts into monthly,
daily and hourly ones
q Geometric Design Specifications
• ICAO and FAA Reference Codes
• Practical observations
• Examples of specifications and their
rationale
Two Key Observations
At “mature” airports (= those that have been operating for
some years and have a relatively stable set of airline
customers:
Peaking patterns and demand variability at
busy airports are typically very consistent
from year to year, over periods of many years
“Flattening” of daily and seasonal demand patterns:
As annual demand grows, the “peaks” and
“valleys” of daily demand profiles and
seasonal demand profiles become less sharp
At a few extremely congested airports (LHR, FRA, LGA)
demand profiles are completely “flat” because of limits
imposed by capacity constraints Page 8
Daily Demand Profile: Newark Aircraft Movements
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Daily Demand Profile: Newark Aircraft Movements
(% of Daily Movements)
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Stability of Monthly Patterns: Total Movements
at the 3 New York Airports
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Stability of Monthly Patterns: No. of Passengers at NY JFK
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Monthly Pax and Movements: Athens, 2008-2012
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Source: AIA (2012)
0
10
20
30
40
50
60
70
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
IST Total Demand: 2013 vs. 2011
Total: 2011: 950 movts; 2013: 1151 movts (+21%) [LHR=1350]
Peak hour: 2011: 65 movts; 2013: 64 movts (-1%)
Peaking factor for the day (2013):
64/1151= 0.056 or 5.6%
For 2011: 65/950= 0.068 or 6.8%
0
5
10
15
20
25
30
35
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
IST Arrivals Demand: 2013 vs. 2011
Totals: 2011: 461 arrs; 2013: 572 arrs (+24%)
Peak hour: 2011: 33 arrs; 2013: 33 arrs (0%)
Peaking factor for the day (2013):
33/572= 0.058 or 5.8%
2011: 33/461= 0.072 or 7.2%
0
5
10
15
20
25
30
35
40
45
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
IST Departures Demand: 2013 vs. 2011
Totals: 2011: 489 deps; 2013: 579 deps (+18%)
Peak hour: 2011: 42 deps; 2013: 36 deps (-14%)
Peaking factor for the day (2013):
36/579= 0.062 or 6.2%
2011: 42/489= 0.086 or 8.6%
Athens: Pax in Peak Hours of the Year as % of
Annual Pax
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Source: AIA (2012)
Another Observation Business passenger trips least variability over a year
International personal leisure trips highest variability
Domestic less variable than international
Example: New York’s Airports, 2011
*Monthly peaking = (Average no. per day during peak month)/
Average no. per day during entire year)
Question: Why is peaking of passengers sharper than peaking
of movements?
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Airport Monthly
Peaking*
Passengers
Monthly
Peaking*
Movements
LaGuardia [high business] 1.082 1.047
Newark [mostly domestic] 1.177 1.072
JFK International [mostly intern’l] 1.193 1.117
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OutlineAirport Demand Patterns
• Variability of demand
• Some key observations
• Converting annual forecasts into monthly,
daily and hourly ones
Geometric Design Specifications
• ICAO and FAA Reference Codes
• Practical observations
• Examples of specifications and their
rationale
Converting Annual ForecastsTypically airport demand forecasts provide
estimates of future annual number of passengers
and annual number of movements
For airport planning, design and management
purposes, it is necessary to convert these annual
forecasts into forecasts of
– Peak monthly demand
– Peak daily demand
– Peak hourly demand
This can be done by developing “conversion
coefficients” using historical data and our two key
observations. [See Reference 2 for details.]Page 20
Converting Annual Forecasts [2]
The value of the conversion coefficients depends
on many things, such as:
– Overall size of demand
– Seasonality of traffic
– “Peakiness” of daily traffic
– Presence or absence of curfew hours
– Geographical location and time zone of airport
One must also exercise judgment about
potential changes in peaking as demand
increases and circumstances change
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Example: VERY ROUGH Calculation
q Peak hour departing passengers when the New Airport will be
handling 100 million passengers per year:
50 million x (1/365) x (1.19) x 0.062 = 10,107 10,000 dep pax
1.19 = hypothetical peaking factor for 30th busiest day (based
on 2013 data for IST)
0.062 = hypothetical daily peaking factor (based on 2013 data
for IST)
q The conversion coefficient in this example is:
(1/365) x (1.19) x 0.062 = 0.000202 [or 0.0202%]
Note: Total passengers in a peak day for a 100 million airport
will exceed 300,000! [100 million x (1/365) x (1.19) = 326,000]
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Detailed Recordsq Airport operators should
– Collect and maintain detailed historical records
of operations
– Perform statistical analyses with the data
– Perform data mining to identify significant
patterns and trends
q Large databases developed by air navigation
service providers (ANSP) and airlines are
becoming increasingly common
– often available to airport operators and
sometimes to researchers or the general
publicPage 23
References
1. de Neufville, R. and A. Odoni (2013) Airport
Systems: Planning, Design and Management,
2nd Edition, McGraw-Hill Education. [Chapter
21]
2. ACRP, Airport Cooperative Research Program
(2012), Guidelines for Preparing Peak Period
and Operational Profiles, Guidebook Report 03-
12, prepared by HNTB in association with Oliver
Wyman & TransSolutions, LLC., Transportation
Research Board, Washington, DC.
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OutlineAirport Demand Patterns
• Variability of demand
• Some key observations
• Converting annual forecasts into monthly,
daily and hourly ones
q Geometric Design Specifications
• ICAO and FAA Reference Codes
• Practical observations
• Examples of specifications and their
rationale
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Airfield Design Specifications The two most-commonly used sources of
geometric specifications for airfield design are:
1. ICAO Annex 14 (“Aerodromes”) [latest 2013,
6th Edition] and many associated documents,
esp. Aerodrome Design Manual, Parts 1 + 2
2. FAA Advisory Circular 150/5300-13 (“Airport
Design”) [latest: Sept. 2012]
FAA updates of specifications are usually
developed earlier than updates to ICAO Annex
14 (e.g., Group VI standards)
Runway length requirements: AC 150/5325-4B
Reference: de Neufville and Odoni, Ch. 9, Secs. 2-
3, 5-9
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ICAO Aerodrome Reference Code
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FAA Runway Design Code (RDC)
Aircraft Approach
Category (AAC)
Approach Speed (AS)
A: < 91 knots
B: 91 – <121 knots
C: 121 – <141 knots
D: 141 – <166 knots
E: 166+ knots
Airplane Design Group (ADG)
Wingspan (WS) Tail Height (TH)
I: < 49 ft <20 ft
<15 m <6 m
II: 49 – <79 ft 20 – <30 ft
15 – <24 m 6 – <9 m
III: 79 – <118 ft 30 – <45 ft
24 – <36 m 9 – <13.5 m
IV: 118 – <171 ft 45 – <60 ft
36 – <52 m 13.5 – <18.5 m
V: 171 – <214 ft 60 – <66 ft
52 – <65 m 18.5 – <20 m
VI: 214 – <262 ft 66 – <80 ft
65 – <80 m 20 – <24.5 m
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A380 vs. B747-400
(72.2 m)
(79.8 m)
(24.1 m)
(64.4 m)
(70.6 m)
(19.4 m)
(560 tons) (396 tons)
Airport Reference Code (ARC)
Determined by the “most demanding” aircraft (or
“design aircraft”, or “critical aeroplane”) that the
airport is designed to serve
The design aircraft need NOT be
– An aircraft which is currently using the airport
– An existing aircraft (can be a hypothetical future
aircraft)
Different runways may have different Runway
Design Codes (RDC): ARC of entire airport will then
be determined by the “highest” RDC available
– E.g., if RDC of Runway 1 is 4-E and of Runway 2
4-C, then ARC is 4-E Page 30
Page 31
OutlineAirport Demand Patterns
• Variability of demand
• Some key observations
• Converting annual forecasts into monthly,
daily and hourly ones
Geometric Design Specifications
• ICAO and FAA Reference Codes
• Practical observations
• Examples of specifications and their
rationale
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Remarks: ICAO and FAA Airport Reference Codes
Practically all major commercial airports belong to the ICAO Code #4 class
In practice, Outer Main Gear Wheel Span (ICAO) is “dominated” by Wing Span
Similarly, Tail Height (FAA) is “dominated” by Wing Span
ICAO Code Letters A-F Wing Spans correspond exactly to FAA Airplane Design Groups I-VI wingspans
Most geometric specifications for airports are determined by the Wing Span of the most demanding aircraft
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●787-8
● ●A350-800A350-900
●747-8
Reference Codes of Wide-Body Aircraft
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Wide-Body Aircraft: Range vs. Seating Capacity
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Examples of Geometric Specifications (ICAO Annex 14)
C D E F
Runway width 45 45 45 60
Taxiway width 18 23 23 25
Runway centerline to taxiway
centerline
168 176 182.5 190
Runway centerline to holdline 90 90 90 107.5
Taxiway centerline to taxiway
centerline
44 66.5 80 97.5
Taxiway centerline to object 26 40.5 47.5 57.5
Taxilane centerline to object 24.5 36 42.5 50.5
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• Code #4 aircraft; distances are in meters; assumes
instrument runway at sea level
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OutlineAirport Demand Patterns
• Variability of demand
• Some key observations
• Converting annual forecasts into monthly,
daily and hourly ones
Geometric Design Specifications
• ICAO and FAA Reference Codes
• Practical observations
• Examples of specifications and their
rationale
Rationale for Dimensional Specifications
The rationale for many of the dimensional
specifications in the ICAO Annex 14 is provided
in the Aerodrome Design Manual, Doc 9157
(Part 1: Runways, Part 2: Taxiways)
The Aerodrome Design Manual can also be used
to estimate dimensional specifications for
accommodating future aircraft development (e.g.,
Code Letter G)
The rationale for some of the FAA’s dimensional
specifications can be found in Appendices 8
(Runways) and 9 (Taxiways) of older versions
(e.g., 1989) of the FAA’s Airport Design advisory
circular (AC 150/5300-13) Page 38
ICAO: Taxiway Centerline to Taxiway Centerline
Page 39
S = WS + C + Z
For Code F, WS=80 m, C=4.5 m, Z=13 m; therefore
S=97.5 m
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Single lane vs. dual lane access to stands
Note as well:
• Taxiway centerline to taxiway centerline: 1.2x(wingspan of
most demanding a/c) + 10 ft (3m)
• Taxiway centerline to object: 0.7x(wingspan of most
demanding a/c) + 10 ft (3m)
Source: FAA AC 150/5300-13 (1989 edition)
Questions? Comments?
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