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The Airspace Concepts Evaluation System (ACES) is a distributed fast-time computer simulation used for design and trade-off studies of system level concepts for the National Airspace System (NAS). ACES employs multi-trajectory modeling in an agent-based software structure to describe the behavior and interactions of Traffic Flow Management, Air Traffic Control, Flight Deck, and Airline Operational Control functions and associated technologies. ACES modules include airport, terminal, en route and system-wide traffic management and controller agents, dispatcher agents, and flight agents; individual aircraft flight dynamics; and airport, airspace, meteorological, and related infrastructure components. ACES simulates gate-to-gate flight operations through the multi-sector, multiCenter, multi-airport NAS network. This paper focuses on the design and implementation of enhanced terminal area modeling capabilities in ACES Build 3. Previous builds of ACES have implemented a nodal model to describe runway system utilization at each airport with nominal terminal airspace transit times. The Build 3 capabilities provide improved modeling fidelity by accounting for individual runway operations and enabling the specification of additional detail in terminal airspace network operations. The Runway Modeling capability simulates individual aircraft operations on individual runways based on user-specified runway use configurations and runway interactions at an airport. The Simplified Terminal Airspace Network Modeling capability simulates irregular terminal airspace boundaries, variable terminal transit times and multiple airport operations in a terminal area. ACES Build 3 introduces capabilities to apply more complex terminal area modeling to selected airports while retaining the lesscomplex nodal model at other airports. ACES also supports variable complexity modeling by enabling users to define the time span over which Traffic Flow Management agents have accurate knowledge of upcoming airport operating conditions (versus inaccurate knowledge based on extrapolated forecasts) and to define the mode by which traffic flow restrictions are simulated (i.e., determined by runway system operating dynamics versus manually-defined static acceptance rates). These features support the modeling of decision support tools of variable levels of sophistication, enabling ACES users to assess the relative value of alternative advanced tool development efforts. |
