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28 This chapter shows how to use the Toolbox to define and estimate the design day from current or forecast annual data. The chapter includes sample problems and provides some comments and cautions on the use of the data. This chapter provides approaches to estimating design day operations and passengers based on a user-defined design day. 4.1 Aircraft Operations 4.1.1 Existing Design Day Operations A simple approach to estimating existing design day aircraft operations is provided in Exhibit 4.1. The first step is to decide on the design day definition. See Section 2.2 for a discussion of the purpose of the design day. For example, if the design day is intended to represent activity that equals or exceeds activity in all but five percent of the year, the 18th busiest day of the year (5% multiplied by 365 days) should be selected. Note that the design day does not need to be limited to a single definition; the same data can be used to calculate multiple definitions of the design day. Likewise, this approach can be used to calculate design day levels for different categories of aircraft operationsâprovided information on these operations by category is available on a daily basis. In the United States, the ADPM is most commonly used to represent the design day for facility planning. Depending on the seasonal and weekly distribution of activity at the airport, the ADPM can translate to a broad range of busy day percentages. For example, the ADPM can represent a design day representing the 5th percent busiest day at a highly seasonal airport, or the 40th percent busiest day at an airport with very low seasonality. Calculation of design day operations requires data on the number of aircraft operations by day for a calendar year or contiguous 12-month period. This information is available at towered airports and can be obtained from the FAA website at http://aspm.faa.gov/. See Appendix B for more detail on data sources. 4.1.2 Future Design Day Operations Future design day operations can be calculated once existing design day operations have been estimated. Exhibit 4.2 provides an approach to projecting future design day operations. 4.1.3 Use of Toolbox The operations module of the Toolbox provides a quick method of estimating design day operations. The following sample problem shows how to use the Toolbox to calculate design day operations. C h a p t e r 4 Preparation of Design Day Forecasts
preparation of Design Day Forecasts 29 Rank Days by # of Aircraft Operations Select Day Corresponding to Design Day definition User Defined Design Day (s) Design Day Operations Operations by Day Data Input User Determined Assumptions Intermediate Output Final Output Exhibit 4.1. Process for estimating existing design day aircraft operations. Calculate Ratio of Design Day Operations to Annual Operations Apply Ratio to Forecast of Annual Operations Future Design Day Operations Existing Design Day Operations Forecast of Annual Operations Existing Annual Operations Data Input User Determined Assumptions Intermediate Output Final Output Exhibit 4.2. Process for estimating future design day aircraft operations.
30 preparing peak period and Operational profilesâGuidebook In this case, an airport planner needs to estimate fuel farm requirements in 2020. The planner wants to ensure the capacity is adequate to meet demand 95 percent of the time. Based on analysis in a recent master plan for the airport, the fuel farm must be sized to provide 150 gal- lons of capacity (including reserves) for each design day operation. The planner enters the scenario name (A), 2025 annual aircraft operations (B), operations type (C), and design day definition (D) in the B. User Selected Parameters worksheet of the Operations Module as in Exhibit 4.3. Sample Problem 4.1 Problem Statement: Estimate Fuel Farm Requirements Airport: General Aviation Airport in Central Time Zone Planning Factor: Gallons per Design Day Operation Forecast Element: Design Day Operations Toolbox Module: Operations Exhibit 4.3. Process for estimating existing design day operations.
preparation of Design Day Forecasts 31 Although planning for the five percent busiest day, the planner includes other design definitions to provide additional background and context. Since peak period information is not required for this problem, peak period input parameters are ignored. In the C. Base Year Data worksheet of the Module (Exhibit 4.4) the planner inputs annual operations by day for 2009, which in this instance was obtained from the FAA Enhanced Traffic Management System Counts (ETMSC) website. Base year schedule data is not required since peak period forecasts are not needed for this problem. The design day forecast is provided in the D. Design Day worksheet (Exhibit 4.5). As shown, projected design day operations are 538 with a 5 percent design day definition. With a planning factor of 150 gallons per design day operation, this translates to a fuel farm capacity requirement of 80,700 gallons (538 design day operations multiplied by 150 gallons per design day operation = 80,700 gallons). The planner notes that design day operations at the one and two percent levels are much higher than at the five percent level and makes a note to inform the Airport Authority that there would be a risk of a significant fuel capacity shortfall on extremely busy days. The planner also notes that if the traditional ADPM criterion had been used, the design day operations would Exhibit 4.4. Process for estimating future design day operations.
32 preparing peak period and Operational profilesâGuidebook have been 345 operations, which would have resulted in a fuel farm capacity of 51,750 gallons (345 design day operations multiplied by 150 gallons per design day operation = 51,750 gallons), and that demand would have exceeded capacity 120 days of the year. 4.2 Passengers 4.2.1 Existing Design Day Passengers The general approach to estimating existing design day passengers is similar to the approach for estimating design day operations. Since daily data on passenger levels is typically unavailable, additional steps are required for the estimate. Exhibit 4.6 shows the typical approach for estimating design day passengers. Scheduled seat arrival and departure data on a daily basis can be obtained from sources such as the Official Airline Guide (OAG) (see Appendix B for more detail). Passengers can be esti- mated from the seat data by applying load factors. These load factors can vary by month and Exhibit 4.5. D. design day worksheet.
preparation of Design Day Forecasts 33 by day-of-the-week. Monthly load factors can be obtained from the U.S.DOTâs T-100 database (see Appendix B for more detail) or can be calculated by dividing airport data on monthly pas- sengers by scheduled seat departures for that month. Day-of-the-week data should be collected from the airlines if possible, but default day-of-week load factor adjustment ratios are provided in Appendix C if that is not possible. Once the passenger level for each day in the base year is estimated, the days can be sorted, and the passenger level that corresponds to the user definition of design day (5 percent, 10 percent, etc.) becomes the design day passenger level. The same process can be used to estimate enplaning, deplaning, or total passenger design day levels. Also, if the ratio of originating passengers to total passengers is known, design day O&D levels can be estimated. 4.2.2 Future Design Day Passengers Exhibit 4.7 provides an approach for estimating future design day levels that is very similar to the approach for estimating future design day aircraft operation levels. 4.2.3 Use of Toolbox The passenger module of the Toolbox provides a quick method of estimating design day passengers. Sample Problem 4.2 shows how to use the Toolbox to calculate design day passengers. Exhibit 4.6. Process for estimating existing design day passengers. Rank Days by Number of Passengers Select Day Corresponding to Design Day Definition Existing Design Day Scheduled Seat Arrivals/Departures by Day Load Factor Adjustment by Day of Week Load Factor by Month Estimate Passengers for Each Day in Year Estimate Load Factor for Each Day in Year User Definition of Design Day Data Input User Determined Assumptions Intermediate Output Final Output
34 preparing peak period and Operational profilesâGuidebook In Sample Problem 4.2, an airport planner needs to estimate automobile parking requirements for 2025. The planner wants to ensure the parking capacity is adequate for 90 percent of the time. From a previous analysis specific to the plannerâs airport, the planner also knows that 0.26 on-airport parking spaces must be provided for each design day O&D passenger. Inputs are provided for the 2025 annual passenger enplanements (A), arrival/departure designation (B), and design day definition (C) as shown below in the B. User Parameters worksheet (Exhibit 4.8). The planner chooses a 10 percent definition for design day, but includes several other definitions in the analysis to determine how much the design day definition will affect his answer. The planner also adds data on enplanements by month (D), and estimates day-of-week load factor adjustments (E) from Appendix C as shown in Exhibit 4.9. The final input parameters are the O&D selection (F) and the ratio of originations to enplane- ments (G) as shown in Exhibit 4.10. Peak period definitions and lead and lag factors are not required to estimate design day passengers so those inputs can be left blank. The airport planner then adds scheduled seat arrivals and departures by day for the base year in the C. Base Year Data worksheet (Exhibit 4.11). The Schedule Data for Representative Day can be left blank since it isnât required to calculate design day passengers. Sample Problem 4.2 Problem Statement: Estimate Automobile Parking Requirements Airport: Large Passenger Airport in Pacific Time Zone Planning Factor: Parking Spaces per Design Day Passenger Forecast Element: Design Day Passengers Toolbox Module: Passenger Exhibit 4.7. Process for estimating future design day passengers. Calculate Ratio of Design Day Passengers to Annual Passengers Apply Ratio to Forecast of Annual Passengers Future Design Day Passengers Existing Design Day Passengers Forecast of Annual Passengers Existing Annual Passengers Data Input User Determined Assumptions Intermediate Output Final Output
preparation of Design Day Forecasts 35 Exhibit 4.8. User parameter worksheet. The design day passenger forecast is provided in the D. Design Day worksheet (Exhibit 4.12). As shown, projected design day O&D passengers are 86,639. With a planning factor of 0.26 parking spaces per design day O&D passenger, this translates to a parking requirement of approximately 22,500 parking spaces. He notes that design day O&D passengers at the two and five percent levels are not much higher than at the 10 percent level, and therefore feels confident that overflow demand on days that exceed the 10 percent threshold will not be extreme. 4.3 Average Annual Day For some analyses, such as noise analyses, the design day is defined as the AAD. To estimate AAD activity, divide annual operations by 365 days to obtain AAD operations and divide annual passengers to obtain AAD passengers. This approach works for both current and future year AAD estimates. Both the Operations and Passenger Modules provide estimates of the AAD in the D. Design Day worksheets.
36 preparing peak period and Operational profilesâGuidebook Exhibit 4.9. Data on enplanement by month. Exhibit 4.10. User selected parameters.
preparation of Design Day Forecasts 37 Exhibit 4.11. Best year data worksheet.
38 preparing peak period and Operational profilesâGuidebook 4.4 Comments and Cautions When preparing design day estimates the following caution should be noted: ⢠The monthly and day-of-week load factors are based on averages and may not accurately represent absolute peaks, such as those that occur around major holidays. Therefore, results for passenger design day definitions representing the top one or two percent levels should be viewed with caution. As a cross-check for representing an absolute worst case, scheduled seats for a holiday travel-day can be collected and a 100 percent load factor can be applied. This will over-represent the actual level of passenger activity but can serve as an effective upper limit. Exhibit 4.12. Design day worksheet.
