cns atm usaf civil planning.pdf

CNS/ATM Planning: Modeling USAF and Civilian Air Traffic Interactions in European AirspacePresentation for ICNS 3 May 2006 The MITRE Corporation Edward Wigfield, Kelly Connolly, Alexander Alshtein, James DeArmon, Richard Flournoy, William Hershey, John James, Paula Mahoney, Jennifer Mathieu, John Maurer, and Paul Ostwald

Slide 1

Approved for Public Release; Distribution Unlimited; Case No. 06-0068 06-

BackgroundOn 3 April 1996 a military version of the Boeing 737 crashed in Dubrovnik, CroatiaSec. of Commerce Ronald Brown one of 35 killed USAF investigation found faulty navigation equipment partly to blame

Global Access, Navigation, and Safety (GANS) program established in 1997Focal point for Air Force requirements

Air Force policy (2001)Conform to the appropriate civil communication, navigation, surveillance/air traffic management (CNS/ATM) performance standards to guarantee access to worldwide controlled airspace.

Slide 2


Some key pointsCNS/ATM capability is expensiveEquipment costs plus integration costs Range up to millions of dollars per aircraft

Mobility Air Force (MAF) supports Combat Air Forces (CAF)Different platforms, different philosophies, and different goals

US Air Force is a user of civilian-managed airspace

Slide 3


Key AssumptionsCivilian Air Traffic will continue to increaseIn line with Eurocontrol forecasts

Political considerations will drive stricter regulatory environmentBasing limitations Denial to airspace access; waiver process delays

Flexible Use of Airspace (FUA) and European Single Sky initiatives will further constrain militaryLimited availability of special use airspace (SUAs) ALTRVs (reserved air corridors) will be hard to obtain Missions will be required to fly within civil traffic Longer Military routes to mission operations areas

Slide 4


Analysis HypothesisPremise: Aircraft equipped with specific CNS capabilities gain from civil authoritiesMore optimal routing; more efficient use of civil airspace Reduced airspace denials More flexibility resulting from less setup time and planning

Premise:Uncertainties regarding use of civil airspace drive workarounds and contingency planningPilots plan for worst case Result is inefficient mission plans and in-transit routing

Hypothesis: Aircraft with better CNS capability gainReduced variability in arrival times Improved ops tempo Better resource utilization Improved dynamic task execution

Slide 5


Analysis Process1.

Falconview, standard Mission Planning tool, generated air routesAccomplished at detailed level; operationally realistic First cut at tanker/fuel utilization

2.

Military routes overlaid on civilian traffic in CAPERCongestion impact assessed at sector level by altitude Weather based on U.S. experience Refueling variance based on AMC inputs/experience

3.

CAPER output passed through Monte Carlo processRan five hundred missions per day; 100 trials per aircraft; Partitioned results into four periods per day Variance resulting from weather, congestion, and refueling Ops tempo metrics for individual aircraft and tanker utilization

4.

Individual aircraft ETAs and variance aggregated to assess strike package formationFailures to form strike packages can be varied to reflect experience

5.

Number of failures used to generate AOC impacts in MSim modelFailures to form strike packages treated as critical event within AOCApproved for Public Release; Distribution Unlimited; Case No. 06-0068 06-

Slide 6

Hypothetical MissionObjective:Air strike on a military airport in Southwest Asia

Notional Strike Package:B-52 (1) F-15D (4) F-15C (2) F-16C (4) E-3 E-8 RC-135 KC-10

Scenario 1:Fighters based in UK Current and future CNS/ATM capabilities

Scenario 2:Fighters based in Eastern Europe Current and future CNS/ATM capabilities Include a fighter drag case

CNS Capabilities Considered:8.33 kHz Voice Communications FM Immunity

Slide 7


Steps of Analysis and Tools used in CNS/ATM Impact StudyScenarios Based on CAF/MAF Processes, CNS Roadmap, and Eurocontrol Regulations

ATO

AOC Model

Resource Utilization (People)

Civilian Air Traffic

Time on Target (From ATO)

1. FalconView

2. CAPER

3. 1st Monte Carlo

4. 2nd Monte Carlo

5. MSIM

Average Time to Process a Critical Event

Capable and Non-Capable Military Routes Aircraft Flight Time for Each Route ETA Distributions for Each Route

Sortie Rate

Output from Tool Used as Input Input to Tool Tool Output

Missed Packages

Resource Utilization (Fuel, Tankers)

Slide 8


Fighter and Bomber Routes UK-Based ScenarioF15Cs, F15Ds

F16s and Equipped B52 Unequipped B52Slide 9


Fighter and Bomber Routes European-Based ScenarioF16s F15Cs

Equipped B52

F15Ds Unequipped B52Slide 10


Civilian Air Traffic Visualization

Slide 11


Structured Routes

Slide 12


Model Reroute

Slide 13


Execute Reroute

Slide 14


Bases in UK, F-15C, Time Period 4Not Capable: 435 minutes, 134 spread CNS Capable: 363 minutes, 107 spreadPercent of Count Cumulative Probability75 50 25 0 75 50 25 0

0.6 0.4 0.2 0.0

0.6 0.4 0.2 0.0

2010

35 4. 36 1 9. 38 1 4. 39 1 9. 41 1 4. 42 1 9. 44 1 4. 45 1 9. 47 1 4. 48 1 9. 1

Flight Duration (minutes)

Not Capable: 451 minutes, 145 spread CNS Capable: 377 minutes 133 spreadPercent of Count Cumulative Probability75 50 25 0 75 50 25 0

0.6 0.4 0.2 0.0

0.6 0.4 0.2 0.0

2015

35 3. 36 6 9. 38 6 5. 40 6 1. 41 6 7. 43 6 3. 44 6 9. 46 6 5. 48 6 1. 49 6 7. 6


The CNS capable case arrives faster, with better predictability.Slide 15


29 1. 30 2 6. 32 2 1. 33 2 6. 35 2 1. 36 2 6. 38 2 1. 39 2 6. 41 2 1. 42 2 6. 2


Cumulative Probability

0.8

Percent of Count

100

1.0

28 2. 29 7 7. 31 7 2. 32 7 7. 34 7 2. 35 7 7. 37 7 2. 38 7 7. 40 7 2. 41 7 7. 7


100

1.0 0.8

Cumulative Probability

0.8

Percent of Count

100

1.0

100

1.0 0.8

CNS Capable: 72 minutes faster and 27 minutes less variability

CNS Capable: 74 minutes faster and 12 minutes less variability

ME1

(4 Aircraft, Time Period 4, 2010) Note: sortie rate shows relative differences not absolute values Base in Hungary (F-15C)Not Capable Capable Not Capable Drag 435 +28 504 +28 minutes 470 +26

Package Formation

Sortie Rate 2.9

8.33 Area664 +36

3.1 3.3 2.2 2.4 2.8 4.3 4.4 4.5

7%

Base in Italy (F-16C)Not Capable Capable Not Capable Drag 510 +35 609 +35

8%

Base in Macedonia (F-15D)Not Capable Capable Not Capable Drag 337 +43 332 +38 316 +42

2%

Base in the UK (F-15C)Not Capable Capable 819 +51 954 +61

1.7 2.0

15%

2Slide 16

In Transit, Waiting at Marshaling Point, Completing Attack Phase, ReturnApproved for Public Release; Distribution Unlimited; Case No. 06-0068 06-

Effect of Packages Missed on Critical Event Response TimeNumber of People Added to Handle AOC WorkloadAverage Additional Response Time for Critical Events (hours) 4 3 2 1 0 0 10 20 30 40 Number of ATO Packages Missed

Slide 17


Package Fuel Requirements (Bases in UK)1,400,000 25

B521,200,000

Fighters20

For Both 2010 and 2015, ~300,000 lbs more fuel is used, equivalent to 5 more Tankers

1,000,000

800,000

15

600,000

10

400,000 5 200,000

KC-135E Loads *

Pounds of Fuel

2010 Not Capable 2010 Capable 2015 Not Capable 2015 Capable

0

* Estimate of gross number of KC135E assumes 1500 nm mission radius and takeoff at standard sea level atmosphere on 10,000 ft dry runway

Slide 18


Workarounds Produce Ripple EffectsSignificant cross-enterprise feedback between CAF, MAF, and civilian ATM CAF workarounds produce wide-ranging ripple effects:1.

Tanker Drag

For CAF perceived to work well BUT for MAF inefficient use of tankers Greater assurance of on-time arrival, BUT, sortie rates decrease, limiting flexibility. ETA variance unchanged, loitering continues at marshalling point wasting fuel. BUT flight time, fuel consumption, crew wear and tanker usage all go up. Sortie rates decrease, reduced flexibility. Can work well BUT bilateral negotiations required; potential economic impacts; no guarantees, future availability in doubtApproved for Public Release; Distribution Unlimited; Case No. 06-0068 06-

2.

Leave Earlier

3.

Plan to avoid regulated airspace

4.

Special Use Airspace (SUAs), Altitude Reservations (ALTREVs)

Slide 19

Phase 2 SummaryValidated hypotheses: CNS capabilities analyzed provide considerable operational improvement for scenarios studiedReduced ETA variability and associated waiting times Reduced tanker utilization and fuel expense Improved sortie rates Improved capability for dynamic tasking at AOC

Workarounds can maintain ability to get to a specific place at a specific time, at least over the short runImpacts are wide-ranging and increase over time Current workarounds may be unavailable in the future

Can support enterprise decision processesCNS/ATM roadmap (other capabilities, platforms, scenarios) Specific issues, e.g., ability to address funding reductions of E8 CNS/ATM program Flow of assets into AOR (by integration with AF ICE)Slide 20


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