NAS-Wide Flow
Modeling and Analysis
Boeing PW NST - Applied Math
Matthew Berge, Technical Fellow
December 10, 2008
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Copyright © 2007 Boeing. All rights reserved.
Topics
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Overview
• The flow problem
• Boeing NFM and related toolset
• Major activities and collaborations
• Modeling status
•
•
•
•
•
•
Boeing NFM
Convective weather
Collaborative flow management / schedule recovery
Future airline schedule generation
Representative weather days
Airport capacity model
• Example studies
• NFM Flow Team
• Matthew Berge, Mike Carter, Darryn Frafford, Laura Kang
• Bruno Repetto, David Wah, Aslaug Haraldsdottir, Charlie Soncrant
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 2
Introduction to the Flow Problem
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• The flow problem is a macro ATM decision problem pertaining to the day
of operations management of a large-scale traffic picture (e.g., the entire
U.S. National Airspace – NAS) in terms of organizing the traffic with
respect to potential limitations in airport / airspace capacities
• Cancellations, delay, and delay propagation are key metrics and pertain
to the thousands of airplanes and tens of thousands of flights in the NAS
• The U.S problem has been focused on airport capacity issues and has
been solved, pretty successfully, by ground-delay programs and
collaborative decision management (CDM) with the airlines
• In contrast, the European problem is focused on airspace capacity
problems and is, inherently, more difficult due to the more complex
origin-destination involvement
• U.S. convective weather problems have become increasing more
important and resemble the difficult European airspace problem; the new
airspace flow program represents a partial solution
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 3
Boeing R&D with respect to the Flow Problem
(Multiple activities initiated in y2001)
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Boeing R&D in flow management has focused on methods that deal
jointly with airport and airspace capacity issues and is, thus, applicable
to the U.S. problem (for convective weather) and the European problem
• Analysis environment: The Boeing National Flow Model (NFM) with
airport/airspace capacities, convective weather representation, tailrouted schedules (for delay propagation), and re-planning
• Decision Support: GDP plus airline schedule recovery model for
collaborative flow management (delays, cancellations, dynamic flight
plan generation, and pre- and post-departure re-routing)
• Disruption Generation: Convective weather modeling, for actual and
forecast weather; scenario modeling for finding representative bad
weather days
• Traffic Modeling: Future airline schedules (since y2001) and methods
for generating unscheduled traffic components (in-work)
Copyright © 2006
2007 Boeing. All rights reserved.
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Major Activities and Collaborations
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Developed NFM and related models (operational for many years) and
utilized in support of a variety of internal and external activities including
• Numerous NAS-Wide delay and benefits analyses including several for the
BCA Airspace Operational Design (AOD) program
• NASA VAMS, AvStar, GCNSS Phases I and II
• On-going internal R&D: distributed schedule recovery and future schedules
• Developed, presented, and published numerous papers and presentations for
a variety of venues including the joint FAA/Eurocontrol R&D seminars, DASC,
ATIO, other OR conferences / workshops; multiple best-of-session papers
• NFM enhancements are primarily driven by specific study needs
• Collaborations
• Metron Aviation team and the CED flow contract
• NOAA Forecast Verification Group (Mahoney, Madine, and others)
• Possible future NASA Ames collaboration
• Possible collaboration and application to safety initiatives
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 5
Introduction to the Boeing National Flow Model (NFM)
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Key inputs include
• Single Day in the NAS
• Tail-routed schedule
• Airport/sector geometries
• Route overlays
• Capacitized elements
• Airport arrival rates
• Airport departure rates
• Sector occupancy limits
• Processing
• A/C performance models
• Network of queues
• Replanning
• GDP and RBS++
• Collaborative flow mgt by
distributed schedule
recovery (with cancellations,
ground delays, re-routing)
• Key outputs
• Delays and delay costs
• Many others…
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 6
National Flow Model (NFM) Status
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Typical scenario models single day of air travel in U.S.
> 35,000 scheduled flights
> 40,000 flight routes
> 6,000 airports
> 1,000 airspace sectors
• Used on numerous studies
 System-wide benefits analysis
 Operational concepts
• Strengths and Differentiators:
 Collaborative flow management & airline schedule recovery
 Pre- and Post-departure re-routing (application to data-link)
 Convective weather – actual, forecasts, relationship to capacity
 Integrated approach for airports and en-route
 Quantifies NAS delays, delay propagation effects, and costs
 Companion capability for generating realistic future schedules
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 7
Convective Weather Modeling Status
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• The NFM uses weather in two forms:
• Actual convective weather
– This is the weather encountered by aircraft in flight
– Radar images expressed on a grid
• Forecasted convective weather (“point” forecasts)
– This is the weather information used by the planner
– Polygonal or gridded, including:
–
–
–
–
CCFP (polygonal)
RCPF & RUC (gridded)
“Perfect” (actual weather used as forecast)
CWFR (Boeing’s polygonal forecast generator)
• Convective weather causes reductions in both actual and forecast
system capacities
• NFM uses a function to translate weather coverage into capacity
Copyright © 2006
2007 Boeing. All rights reserved.
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Schedule Recovery (AOC) Model Status
(Advanced Planner for Collaborative Flow Management)
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Distributed schedule recovery (AOC)
•
•
•
•
Potential NextGen concept for collaborative flow management
Strategies include ground delay, re-routing, and cancellations
Dynamic flight planning capability for post-departure re-routing
Optimization-based approach can utilize alternative objectives and can
permit use of airline-specific business rules
• Computationally feasible even in large-scale NAS-wide simulation
• Initial prototype for stochastic planning
• Result is optimized airline schedules which are jointly feasible with
respect to total forecast airport and airspace capacities
• Central authority (SCC)
• SCC allocates airport and airspace capacity to each airline
• Currently use an extension of "ration by schedule" to sector capacity
allocations to achieve equitable allocations thru iterative collaborative
process with the AOC
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 9
Future Airline Schedule Modeling Status
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Capability for generating future (US) airline schedules developed in
y2001 and utilized many times in ATM analyses
ORD capacity utilization
2000-2020
• Utilizes Boeing CMO forecasts
• Schedule optimization algorithms
100%
2000 BL
2010 BL
2020 BL
80%
ops (% capacity)
• Analysis of schedules needed
for template; templates capture
hub-and-spoke structures
120%
60%
40%
• Airport capacity constraints
20%
• Used extensively
0%
• Model enhancements include
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
hour
• Schedule re-timer: for efficiently tail-routable schedules
• Schedule adjuster: performance-based block times and schedule pad
• Additional capability for tail-routing schedules for NFM input
• Updated for y2007 CMO
• Initial methodology for creation of alternative CMO forecasts
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 10
23
24
Selecting Representative Weather Days
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Challenges
• Weather scenario with correlated weather (airport visibility)
• Based on annualized NFM statistics
• Minimize number of NFM runs
• Methods
• Integer Quadratic Programming
(Min-Square Estimation) to pick
given number of dates and
associate weights that
represent annual weather stats
100%
80%
45
48
59
62
60%
95
82
9
11
8
7
Annual
FAA
100
16
40%
83
22
16
22
• Results
• Successfully picked
dates/weights in a few minutes
• within 0.25% of “optimal”
solution
20%
39
30
25
16
5
1
0%
feb 14
jun 9
sep 23
nov 26
dec 15
0
dec 32
0.142064
0.422648
0.09658
0.013146
0.067062
0.2585
date (weight)
• Next step: convective weather
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 11
VMC
MVMC
IMC
Airport Capacity Constraints Model
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Model overview
• Evaluates hourly airport runway capacity (arrivals and departures) for the 35 OEP
airports for different weather conditions and operating configurations
• Developed in 2004 and updated when new airport-specific fleet mix, runway
configurations, and hourly capacities are available from FAA or industry sources
• Calibrated to current ops by evaluating reduction in theoretical hourly airport capacity
due to current constraints caused by airfield configuration or operational procedures
• Evaluates benefits of advanced concepts by modifying model inputs to represent
improved performance due to new technology or operational procedures
• Advantages
• Provides quick evaluation of a range of technology alternatives across the NAS
• Supports sensitivity assessments across the NAS and can be used to prioritize solutions
• Ties benefits to specific performance requirements for new technologies and defines
research needs
• Model use
• Used by Boeing, often in concert with the NFM, to assess the airport capacity benefits of
advanced concepts
• Part of the JPDO Systems Modeling & Analysis Division tool suite to assess the airport
capacity benefits of NextGen
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 12
Example Studies (Page 1 of 2)
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Types of studies
•
Explore, in a static setting, the interaction of future traffic and capacity
•
Explore, in a dynamic way, the impact of day-of-operation disruptions, their
impact on available capacity, and compare the relative benefits of improved
forecasting and/or improved decision making (and greater automation)
• Example Study: Benefits of RNP and 3-D Paths
•
“Required Navigation Performance and 3D Paths in High Traffic Operations”
for the 25th DASC (y2006, Portland) by Haraldsdottir et. al.
• Example Study: Benefits of Improved Re-routing for Departures
•
“Airline Schedule Recovery in Flow Management: An Application for
Departure Re-routing” for the 25th DASC (y2006, Portland) by Berge et. al.
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 13
Example Studies (Page 2 of 2)
Engineering, Operations & Technology | Phantom Works
E&IT | Networked Systems Technology
• Example Studies: Benefits of Collaborative Flow Management for Convective
Weather Disruptions
•
“Benefits of Collaborative Flow Management During Convective Weather
Disruptions”, for the 7th USA/Europe ATM R&D Seminar (y2007, Barcelona)
by Berge et. al.
•
“Collaborative Flow Management: Analysis of Benefits During Convective
Weather Disruptions”, for the ATIO (y2008, Anchorage) by Berge et. al.
•
“Final Report for y2008 Distributed Airline Schedule Recovery, Collaborative
Flow Management: Automation and Forecast Comparisons for Convective
Weather Disruptions” by Berge et. al.
• Methodologies: Collaborative Flow Management and Future Schedules
•
“Airline Schedule Recovery in Collaborative Flow Management with Airport
and Airspace Capacity Constraints”, 5th USA/Europe ATM R&D Seminar
(y2003, Budapest) by Berge et. al.
•
“Future Airline Schedules for Air Traffic Management Concept Analysis”, 26th
DASC (y2007, Dallas) by Berge et. al.
Copyright © 2006
2007 Boeing. All rights reserved.
EOT_PW_Sub_no-icon.ppt | 12/10/2007 | 14
Questions, Answers, and
Discussion…
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Copyright © 2007 Boeing. All rights reserved.
Copyright © 2007 Boeing. All rights reserved.
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