1. Modeling NextGen Functions in Future ATM Concepts Evaluation Tool (FACET)
Banavar Sridhar
NASA Ames Research Center
Second Annual Workshop
Innovations in NAS-Wide Simulation
Washington, DC
January 27-28, 2010

2. Outline NASA ATM Research in Traffic Flow Management
FACET Baseline Capability
New Functionality
Simulation and Optimization
Integration of TFM and TMA Concepts
Collaborative Decision-Making
Environmental Models and Trajectory Optimization
Concluding remarks
In the rest of the presentation, I will talk about the prediction model, some result, how to add the weather information into the model, then conclusion

3. Integrated TFM Solution
TFM Simulation
20 min - 8 hrs
National Airspace System
User
schedules
and flight
plans
Observed
traffic
Weather Translation
TFM Optimization
Traffic
Predictions
Metrics
Collaborative Traffic Flow Management
TFM Decisions
Aircraft-level (FACET)
Aggregate-level
Airspace Adaptation Data
Meteorological Data
What’s right mix of air and ground automation?
How to make this all safe given uncertainties and failures?
Investigate modeling, simulation and optimization techniques to minimize total system delay (or other performance functions) subject to airspace and airport capacity constraints while accommodating three times traffic in the presence of uncertainty

4. Software Environment FACET
4/24/2017
FACET
Software environment for developing and testing Traffic Flow Management and Dynamic Airspace Concepts
AIAA Engineering Software of the Year (2009)
Available to universities world-wide and U.S. companies
Integration with Optimization Methods
Integrated with MATLAB tools
Integrated with Linear Programming (CPLEX) tools
Integration with other NASA ATM Software Systems
Center-TRACON Automation System (CTAS)
ACES (Airspace Concept Evaluation System)
4/24/2017

5. Interaction of Simulation and Optimization
Decision are made through a three step process, on an hourly basis a strategic departure control model is used …

6. Coordinated TFM and TMA Operations*
* S. Grabbe, B. Sridhar, A. Mukherjee and A. Morando, “Integrated Strategic and Local
Arrival Flight Scheduling,” Submitted to the AIAA Guidance, Navigation and Control
Conference, 2-5 August 2010, Toronto, Canada

7. Motivation
Traffic flow management currently accomplished through a loosely coordinated set of national and regional level controls
Predicted interactions and integrated impact of these controls are not well understood
Long (sometimes duplicate) pre- departure delays assigned to some flights
and inconsistently control traffic flows
- GDP assigns EDCT to satisfy the airport capacity constraint
TMA delays flight to fit it into the overhead stream
Controls tend to under, over, and inconsistently control traffic flows
3 of 17

8. Objectives
Develop an integrated test-bed to facilitate integrated traffic flow management and metering studies
Explore concepts and models for improving the inter-operability between traffic flow management and metering.
First objective allows us to identify system choke-points that lead to or contribute to NY delays
For the remainder of this section of the presentation I would like to (1) review the modeling methodology, (2) review the experimental setup, and (3) look at the results
8 of 17

9. GDP scenario at DFW

10. Simulation and analysis of aircraft trajectories with environmental constraints*
*N.Chen, B. Sridhar and H.Ng, “Strategies for Reducing Contrail Formations Using Predicted Contrail Frequency Index,” Submitted to the AIAA Guidance, Navigation and Control Conference, 2-5 August 2010, Toronto, Canada.
B.Sridhar, N. Chen and H. Ng,“Simulation and optimization methods for assessing the impact of aviation operations on the environment,” 27th Congress of the International Council of the Aeronautical Sciences (ICAS), September 2010, Nice, France.

11. Impact of Aviation on Climate Change*
Increased urgency to deal with factors affecting climate change
Climatic changes include
Direct emissions: CO2 , Water vapor and other greenhouse gasses (best understood)
Indirect effects from NOx affecting distributions of Ozone and Methane (Ozone and Methane effects have opposite signs)
Effects associated with contrails and cirrus cloud formation
Aviation responsible for 13% of transportation-related fossil fuel consumption and 2% of all anthropogenic CO2 emissions
Large uncertainty in the understanding of the impact of aviation on climate change
*“Workshop on the Impacts of Aviation on Climate Change,” June 7-9, 2006, Boston, MA.

12. Why another simulation?
Focus on impacts of subsonic aviation emissions at cruise altitudes in the upper troposphere and lower stratosphere (~14Km and above)
Emissions at cruise altitudes have a larger impact than emissions on the surface
Need a air traffic simulation and optimization tool-box with fuel, emission and contrails models

13. Environmental Considerations*

14. Environment Simulation Modules
Aircraft Dynamics
3-DOF equations
Wind models
RUC 40/20 KM grid
Contrails
Computed using RUC data
Fuel burn
Leverage FAA SAGE models
Emission
Trajectory optimization

15. Contrails
Occur if ambient temperature along the aircraft trajectory is colder and moister than a threshold defined by thermodynamic parameters
Contrails persist under certain conditions (Relative humidity with respect to ice >100%)
Effect different during night and day

16. Persistent Contrail Formation Model
RHW Contours
RHI Contours
Aircraft
Rhi>100%
Persistent Contrail
RHI>100% Contours 16 16

17. Contrail Frequency Index

18. Trade-offs Amongst Aviation Emissions Impacting Climate
Flight altitude effects on ozone, contrail formation and other effects
Differential impact of night and day operations
Routings to avoid certain regions with specialized chemistry (e.g. supersaturated air, cirrus, or polar)

19. Fuel optimal contrail avoidance aircraft trajectories
Fuel optimal trajectories generated using point mass aircraft dynamics and trajectory optimization based on Singular Perturbation Theory

20. Concluding Remarks
Presented recent changes to FACET software to enable evaluation of TFM concepts in support of NextGen
Emphasized current research on TFM-TMA interaction and environmental modules

21. Key TFM Research Activities
Weather Impacted Airspace/Airport Capacity Estimation
(AFD/Chan, AFD/Love, TI/Wolfe, TI/Wang, AFC/Sheth, UARC/Islam, MIT-LL, NRA/Krozel, NRA/Cook)
Metrics for Correlating the Performance of the NAS with Weather
(AF/Sridhar, UARC/Chen, TI/Wang, TI/Kulkarni, AFD/Walker)
TFM Simulation
20 min - 8 hrs
National Airspace System
User
schedules
and flight
plans
Observed
traffic
Weather Translation
TFM Optimization
Traffic
Predictions
Metrics
Collaborative Traffic Flow Management
TFM Decisions
Aircraft-level
Aggregate-level
Airspace Adaptation Data
Weather Data
Aggregate-level Demand Estimation and Flow Modeling (AFC/Bloem, NRA/Bayen, TI/Timucin)
Assigning Aircraft-level Delays to Satisfy Airport/Airspace Constraints
(AFC/Rios, AFC/Grabbe, UARC/Mukherjee, TI/Agogino, NRA/Ball, NRA/Clarke)
Integration of TFM Capabilities
(AFC/Grabbe, UARC/Mukherjee, UARC/Morono, UARC/Lock)
Weather Rerouting (AFC/Grabbe, UARC/Mukherjee, UARC/Ng
Influence of User Preferences on Flight Routing (AFC/Sheth, AFC/Bilimoria, TI/Wolfe, TI/Enomoto, UARC/Jarvis, NRA/Idris)

22. FACET Software Architecture Aircraft Performance Data
National
Weather
Service
Winds
Severe Weather
FAA
Traffic Data
Tracks
Flight Plans
Aircraft Performance Data
Climb
Descent
Cruise
Airspace
Airways
Airports
Adaptation Data
Historical
Database
Traffic & Route
Analyzer
User
Interface
Route Parser &
Trajectory Predictor
FACET CORE FEATURES
APPLICATIONS
Air and Space Traffic Integration
Airborne Self-Separation
Data Visualization
Direct Routing Analysis
Controller Workload
System-Level Optimization
Traffic Flow Management

23. Simulation and Optimization
Java Application
Read/Implement Flight Controls
FACET
NAS Simulation
4D Trajectories
Weather Forecasts
Generate/Introduce Simulation Uncertainties
Run optimization model in CPLEX/AMPL
Start Simulation
Application Program
Interface
Create CPLEX/AMPL Input File
Log airspace/airport occupancy/usage statistics
Repeat N time steps
Flight Controls
System Uncertainties
Generate weather impacted airspace/airport capacity
Flight Schedules
Weather Forecasts
Airspace Configuration

24. Aircraft Dynamics
Flat-Earth, inertial reference, point mass aircraft model
Find the optimal trajectory given the arrival and departure
airports, wind conditions subject to environmental conditions

25. Trajectory Optimization Options
No winds
Separate route and altitude profile optimization
Near optimal wind routes
Dynamic programming
Singular perturbation
Linear programming
Heuristics
Inclusion of contrail constraints (state constraints)