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NextGen Modeling in NASPAC

This toolset includes various modules and parsers for modeling and forecasting in the NASPAC environment, such as capacity scheduling, GDP generation, trajectory modules, and flight delay analysis.

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NextGen Modeling in NASPAC

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  1. NextGen Modeling in NASPAC

  2. Preprocessor (Demand) Future Schedule Generator Output Parser Core Queuing Model Industry/ Regulatory Response Itinerary Generation Fleet Evolution Trajectory Module Output Parser GDP Generator Sector Crossings Preprocessor (Capacity) Capacity Scheduler Modernized NASPAC Environment

  3. Δ Fuel Burn Modernized NASPAC Environment Wx Delay Fuel Burn Rate TAF Future Schedule Generator Flow Restriction Defns & Caps ETMS Constrained Traj.-Based Forecast (2D) Unconstrained Traj.-Based Forecast (2D) 4D Trajectories Core Queuing Model Flight Table Industry/ Regulatory Response Itinerary Generation Fleet Evolution Trajectory Module Output Parser GDP Generator Sector Crossings Airport Table Sector Table Sector Geometries Fleet Forecast Wind Field Unsatisfied Demand Flight Delays Time dependent Airport Capacities Pareto Curves Wx = weather TAF = Terminal Area Forecast MAP = Monitor Alert Parameter ETMS = Enhanced Traffic Management System Capacity Scheduler Wx Time dependent Sector Capacities MAP Values

  4. Airport Capacity Scheduler • Modeling airport capacity • Previously • Used ceiling and visibility to determine VMC, MMC, and IMC conditions and apply associated capacity curve • Now • Considers wind speed, wind direction, and time of day • Use special condition curves • Configuration specific • Wake Turbulence Mitigation for Departures (WTMD)

  5. Ground Delay Program (GDP)Generator • Previously • No GDP module • Now • GDP generator identifies GDPs and assigns expected departure clearance times • Given flight times and weather dependent airport capacities • Flights assigned arrival slot based on priority • Distance based tiers • International flights exempt • Airport specific GDP triggers • Max flight delay • Max queue length • Next • Airline response and cancellation module • Probabilistic GDP triggers • Probabilistic weather forecast

  6. Performance Based Navigation (PBN) • Model Q-Routes • Previously • No special treatment • Now • Allow equipped flights, between certain city pairs to fly special routes • Impose aircraft separation standards using restrictions

  7. ZOA Oceanic Separation • Previously • Flights flew unconstrained in oceanic airspace • Now • Oceanic separation standards imposed using static restrictions • Considers lead/following aircraft type/equipage to determine separation • Next • Incorporate altitude restrictions • Oceanic in-trail climb and descent

  8. SIDs and STARs • Standard Terminal Arrival Routes (STARs) • Previously • All flights had continuous descent arrivals • Estimated time/fuel inefficiencies by historical data analysis • Now • Assign each flight to a STAR • based on route and equipage • Define more detailed 4-D trajectory • with altitude restrictions • Standard Instrument Departures (SIDs) • Similar technique implemented

  9. Notional PBN Forecast Notional ADS-B Forecast Equipage Evolution • Previously • Baseline equipment data used throughout forecast • Soon • Evolve future fleet equipment to meet forecast • Equipment categories include • Datacomm • ADS-B In and Out • PBN: RNAV and RNP

  10. Next Steps • Incorporate Traffic Flow Management (TFM) • Airspace Flow Programs • Improve Terminal Approach Control (TRACON) • Update and automate arrival fix and departure fix flows • Incorporate fix balancing • Improve local and en-route weather effects • Model severe IMC conditions • Incorporate dynamic events • Dynamic rerouting, dynamic sectorization • Include Monte Carlo simulation capability • Re-factored source code • Validation, validation, validation

  11. Questions? SNAZPAC

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