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proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
ProESTOP Runway Occupancy Time Estimator
1. INFLUENCE OF RUNWAY OCCUPANCY TIME ON RUNWAY CAPACITY 2. EXISTING METHODS & TOOLS 3. proESTOP ALGORITHM 4. APPLICATIONS 5. CONTACT US
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
1. INFLUENCE OF RUNWAY OCCUPANCY TIME ON RUNWAY CAPACITY
proESTOP - Runway Occupancy Time Estimator
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
1. INFLUENCE OF ROT ON AIRPORT CAPACITY
proESTOP - Runway Occupancy Time Estimator
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Separation between operations (ICAO DOC444 §7.8.2 and §7.9.1)
& Local regulations
Runway operations affect overall Airport Capacity
Exit taxiway usage Taxi flows
Minimum Separations
Runway Occupancy Times (ROTs)
Taxi time & Number and Location of potential conflicts
X
DELAY
CAPACITY
GO-AROUNDS
CONFLICTS
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
• To help ANSPs and airport managers / planners identify capacity limits
• To identify improvements to maximize performance while maintaining safety levels
RUNWAY CAPACITY ASSESSMENT PLANNING AND DEVELOPMENT OF AIRPORTS
proESTOP - Runway Occupancy Time Estimator
5 proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
1. INFLUENCE OF ROT ON AIRPORT CAPACITY
Actual need to estimate occupancy times
2. EXISTING METHODS & TOOLS
proESTOP - Runway Occupancy Time Estimator
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
2. EXISTING METHODS & TOOLS
proESTOP - Runway Occupancy Time Estimator
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proESTOP / Ineco
None of the tools and/or methodologies then in use entirely satisfied planning needs.
Complexity/Effort
Accuracy
ANALYTICAL MODELS
ACTUAL DATA SURVEY
SIMULATION MODELS
PROESTOP: a cost-effective mathematical tool
Highest effort (Time & Resources) Minimum sample size to ensure statistical significance
Not always applicable to what-if scenarios
Intermediate models Lower reliability than survey Input information not always available
Simple models. Ready application Deviations not considered Assumptions not realistic
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
3. proESTOP ALGORITHM
proESTOP - Runway Occupancy Time Estimator
8 proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
proESTOP - Runway Occupancy Time Estimator
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The tool faithfully reproduces the runway operation in a given scenario.
A great number of factors must be taken into account in when assessing runway operation:
Type and weight of aircraft Approach speed Flight techniques
Elevation of aerodrome Wind
Temperature Runway condition (dry or wet)
Other factors (stand position, aerodrome knowledge, etc...)
Touchdown Runway THR
REVERSE SPOILERS
PLANEO GLIDE VUELO STRAIGHT FLIGHT
BREAK TRANSITION
NOMINAL BRAKING BRAKE ADJUSTMENT
VACATING TRANSITION
TURN
FLIGHT STAGE BRAKING STAGE VACATING STAGE
1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8
IDLE REVERSE MANUAL BRAKE ROLL
80KIAS 80KIAS V V STEER STEER <70Kts <70Kts V V EXIT EXIT V V TAXI TAXI V V THR THR V V TD TD
VACATING STARTING POINT
60KIAS 60KIAS 20’ 20’’
PALANCA
LDA
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
3 – proESTOP ALGORITHM
3 – proESTOP ALGORITHM
proESTOP - Runway Occupancy Time Estimator
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amax?
Iteration Next Available Exit
Exit Assignment XEXIT; Φ
ROT calculations (Numerical Integration)
∫ ∫==Xexit
EXITTHREXIT KVVV
dXVdxT
0
1
0),,(
ξ
ξξξξ
ξξ
ddV
XV
dtd
ddV
dtdVa
C
)()()(⋅=⋅==
Exit usage probability by ACFT group
)X(C
)X(C
ii
ii
e1eY
Σ
Σ
+=
amax >Max Deceleration (RWY conditions)
End
Speed Profile Assignment
VTHR; VEXIT(Φ); K(Φ)
ACFT MODEL METEO
Stochastic simulations based on realistic operational parameters distributions
Margin of error on average values: 3-5%
Simulation time: 2 min
Simulations based on Monte Carlo method:
Realistic operational parameters based on Ineco’s experience as airport engineering firm and Air Navigation Service Provider
The model generates pseudo-random numbers by simulation techniques to mimic the statistical distribution of the input variables.
Then, it obtains the correspondent output variables by computing the algorithm.
After a sufficient number of replications, the sampling results will reproduce the distribution of the statistic outputs.
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
proESTOP - Runway Occupancy Time Estimator
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PROESTOP: a cost-effective mathematical tool
RUNWAY PERFORMANCE
Customisable statistics on ROT ESTIMATIONS
Intermediate Occupancy Times
OPTIMISATION
Chronological Optimisation Plan (Time Horizons)
EXIT TAXIWAYS USAGE
Proposals for the LOCATION OF EXIT TAXIWAYS
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
3 – proESTOP ALGORITHM
4. APPLICATIONS
proESTOP - Runway Occupancy Time Estimator
12 proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
4 – SAMPLE CASE. proESTOP ESTIMATION
proESTOP - Runway Occupancy Time Estimator
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Estimation of ROT is required. Given no actual data available.
proESTOP estimates properly fits actual distributions
Conflicts were reduced from 28 to 1
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
4 – APPLICATIONS
proESTOP - Runway Occupancy Time Estimator
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Supporting tool to runway performance evaluation and planning processes
Different kind of studies based on runway occupancy times estimations:
International airports: Madrid – Barajas, Barcelona, Palma de Mallorca, Malaga, Puerto Vallarta, Kuwait, Luton, Fujairah, …
Airports planning and development
More than 50 studies comprising the evaluation of nearly 350 different proposals
Different airport complexity:
Runway capacity assessment
Small – medium airports: Ibiza, Lanzarote, Valencia, …
Impact of works in movement area
Evaluation of alternatives in Master Plans
Evaluation of expansion projects: location of new exit taxiways
Green Field studies: Murcia, …
Make the most of Ineco’s experience as airport engineering firm and Air Navigation Service Provider
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
5. CONTACT US
proESTOP - Runway Occupancy Time Estimator
15 proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15
5 – CONTACT US
proESTOP - Runway Occupancy Time Estimator
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+34 91 452 12 95
[email protected] http://www.ineco.com
INECO Avda. Partenón 4 – 4 28042 Madrid (Spain)
C. BARBAS, J. VÁZQUEZ, P. LÓPEZ (2007), “Development of an algorithm to model the landing operations, based on statistical analysis of actual data survey (PROESTOP)”, 7th ATM R&D Seminar, Barcelona 2007 http://atmseminar.eurocontrol.fr/past-seminars/7th-seminar-barcelona-spain-july-2007/papers/paper_027/view
Further information
WAC stand 845
proESTOP – Runway Occupancy Time Estimator_WAC 2015. Carlos Barbas. 11/03/15