Demand Patterns; Geometric Design of Airfield Prof. Amedeo Odoni

Transcription

1 Demand Patterns; Geometric Design of Airfield Prof. Amedeo Odoni Istanbul Technical University Air Transportation Management M.Sc. Program Airport Planning and Management Module 4 January 2016

2 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 2

3 Outline Airport 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 Page 3

4 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

5 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. longhaul, business vs. leisure) also varies by time-of-day Page 5

6 Variability of Airport Demand q 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.) Page 6

7 Outline Airport 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 Page 7

8 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

9 Daily Demand Profile: Newark Aircraft Movements Page 9

10 Daily Demand Profile: Newark Aircraft Movements (% of Daily Movements) Page 10

11 Stability of Monthly Patterns: Total Movements at the 3 New York Airports Page 11

12 Stability of Monthly Patterns: No. of Passengers at NY JFK Page 12

13 Monthly Pax and Movements: Athens, Source: AIA (2012) Page 13

14 IST Total Demand: 2013 vs Peaking factor for the day (2013): 64/1151= or 5.6% For 2011: 65/950= or 6.8% Total: 2011: 950 movts; 2013: 1151 movts (+21%) [LHR=1350] Peak hour: 2011: 65 movts; 2013: 64 movts (-1%)

15 IST Arrivals Demand: 2013 vs Peaking factor for the day (2013): 33/572= or 5.8% 2011: 33/461= or 7.2% Totals: 2011: 461 arrs; 2013: 572 arrs (+24%) Peak hour: 2011: 33 arrs; 2013: 33 arrs (0%)

16 IST Departures Demand: 2013 vs Peaking factor for the day (2013): 36/579= or 6.2% 2011: 42/489= or 8.6% Totals: 2011: 489 deps; 2013: 579 deps (+18%) Peak hour: 2011: 42 deps; 2013: 36 deps (-14%)

17 Athens: Pax in Peak Hours of the Year as % of Annual Pax Source: AIA (2012) Page 17

18 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 Airport Monthly Peaking* Passengers Monthly Peaking* Movements LaGuardia [high business] Newark [mostly domestic] JFK International [mostly intern l] *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? Page 18

19 Outline 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 19

20 Converting Annual Forecasts Typically 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

21 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 Page 21

22 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 = 10,107 10,000 dep pax 1.19 = hypothetical peaking factor for 30 th busiest day (based on 2013 data for IST) = hypothetical daily peaking factor (based on 2013 data for IST) q The conversion coefficient in this example is: (1/365) x (1.19) x = [or %] 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] Page 22

23 Detailed Records q 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 public Page 23

24 References 1. de Neufville, R. and A. Odoni (2013) Airport Systems: Planning, Design and Management, 2 nd 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. Page 24

25 Outline Airport 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 Page 25

26 Airfield Design Specifications The two most-commonly used sources of geometric specifications for airfield design are: 1. ICAO Annex 14 ( Aerodromes ) [latest 2013, 6 th Edition] and many associated documents, esp. Aerodrome Design Manual, Parts FAA Advisory Circular 150/ ( 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- Page 26 3, 5-9

27 ICAO Aerodrome Reference Code Page 27

28 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 Page 28

29 A380 vs. B (79.8 m) (72.2 m) (24.1 m) (64.4 m) (70.6 m) (19.4 m) (560 tons) (396 tons) Page 29

30 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

31 Outline 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 31

32 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 Page 32

33 787-8 A A Page 33

34 Reference Codes of Wide-Body Aircraft Page 34

35 Wide-Body Aircraft: Range vs. Seating Capacity Page 35

36 Examples of Geometric Specifications (ICAO Annex 14) C D E F Runway width Taxiway width Runway centerline to taxiway centerline Runway centerline to holdline Taxiway centerline to taxiway centerline Taxiway centerline to object Taxilane centerline to object Code #4 aircraft; distances are in meters; assumes instrument runway at sea level Page 36

37 Outline 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 37

38 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/ ) Page 38

39 ICAO: Taxiway Centerline to Taxiway Centerline S = WS + C + Z For Code F, WS=80 m, C=4.5 m, Z=13 m; therefore S=97.5 m Page 39

40 Single lane vs. dual lane access to stands Source: FAA AC 150/ (1989 edition) 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) Page 40

41 Questions? Comments? Page 41