Flexible Airport Simulation (FLAPS)

FLAPS is a complete Monte Carlo simulation model that can be used to analyze runway capacity and delays. This stochastic, event-driven simulation models aircraft from the approach fix to the runway exit and from the runway departure queue to the departure fix. Easily adaptable to any geometry, FLAPS produces detailed statistical outputs on runway capacity and utilization, aircraft delays, exit use, and runway queues. Due to its computational efficiency and simple input structure, FLAPS is characterized by a very low cost per computer run compared to other similar airport simulation packages. The model is written in the C++ computer language and operates on any IBM-compatible PC. Its advantages over other simulation models are the result of three key features:

    • Monte Carlo simulation: The stochastic nature of the FLAPS model produces not only an assessment of capacity, delay, runway use, and exit utilization, but also a statistical output that indicates the potential variation in these results.
       
    • Dynamic operating conditions: In addition, the model can easily simulate dynamic (as opposed to static) airport environments. For example, the model can simulate changes in runway configurations (and reassignment of landings and takeoffs to different runways) due to weather or aircraft changes; changes in separation requirements due to weather; or controller-initiated changes in runway assignments aimed at equalizing runway usage. 
    • Modeling of the complete landing process: The simulation of the landing process is based on a physical model of aircraft performance characteristics. All phases of approach, flare, touchdown, and braking are considered, creating an accurate representation of an aircraft’s potential to utilize an exit. It is therefore possible to explore the effects on runway capacity and delays of new runway exits, high-speed exits, wet runway conditions, or runway surfaces designed for improved braking.

FLAPS requires the user to specify inputs on the three primary factors which affect runway capacity: (1) aircraft characteristics and fleet mix, (2) runway layout and availability, and (3) air traffic control operating procedures.  Fleet mix requirements include estimated number of operations by aircraft type. For computational efficiency, individual aircraft types are grouped into similar classes based on operating requirements and performance characteristics.  FLAPS utilizes up to eighteen aircraft classeswith distinct operating characteristics including approach speed, float and braking distances, and departure runway occupancy time. Runway layout input requirements include the orientation and length of each runway and the location and type (e.g. high speed) of runway exits and intersections.  Air traffic control inputs include a range of operational factors such as the runways in use at specified times and their modes (e.g. arrival only, mixed arrivals and departures, departure priority), runway assignment policy (e.g. by aircraft type, by direction of flight, etc.), and the required separations (arrival-arrival, departure-departure, departure-arrival) between successive aircraft operations under different weather conditions. Separation standards are a critical element of runway capacity calculations, and FLAPS is uniquely designed to accurately apply appropriate separations for single runways as well as multiple intersecting or non-intersecting runways. FLAPS also utilizes other air traffic control variables including the location of final approach fixes, land-and-hold-short operations, and the traffic distribution by arrival and departure fix.

The primary output of each FLAPS model run is the capacity of a runway configuration (the maximum number of aircraft arrivals and departures that can be achieved in one hour under given fleet mix, weather, and air traffic control conditions). FLAPS also produces detailed statistics on delays, runway use, and exit utilization by aircraft class.  FLAPS has been used to analyze over one hundred runway configurations as part of the Logan Airside Improvements EIS/EIR Project, and has also been used to determine runway capacities at Lambert St. Louis International Airport, Amsterdam's Schiphol Airport, and Sydney Kingsford-Smith Airport. 

   

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