Final Briefing for NASA CTD-Subtopic 1 NRA: Methods of ... · 29/10/2015 · BASE YEAR FINAL PRESENTATION NASA CTD-SUBTOPIC 1 NRA: METHODS OF INCREASING TERMINAL AIRSPACE FLEXIBILITY

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BASE YEAR FINAL PRESENTATION

NASA CTD-SUBTOPIC 1 NRA:

METHODS OF INCREASING

TERMINAL AIRSPACE FLEXIBILITY

AND CONTROL AUTHORITYSebastian Timar, Greg Carr, Architecture Technology Corporation

David Myers, Julien Scharl, Boeing

Phil Smith, Amy Spencer, Cognitive Systems Engineering & Design

Doc. #: 850-035977

Version: 1

Date: 21 October 2015

COMPANY UNCLASSIFIED - NOT EXPORT CONTROLLED

SAAB

Version: 1

Date: October 21, 2015

Doc. #: 850-035977

EXECUTIVE SUMMARY

Solicitation objective was to develop concepts and

algorithms for making tactical adjustments (e.g., path

stretch, speed adjustments) to strategically-planned arrival

and departure trajectories

During the course of the project, the objective changed to

developing a “What-if” Analysis capability for Departure

Metering Programs (DMP) in support of ATD-2

A fast-time simulation-based What-if Analysis capability

was developed and tested against three DMP use cases

Preliminary findings show that the DMP What-if Analysis capability

can help the Departure Reservoir Coordinator (DRC) select values

for key parameters, i.e.,

DMP Start and End Time

Target Departure Queue Length (TDQL)

Unscheduled Demand Buffer (UDB)

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PRESENTATION OUTLINE

Solicitation Objective

Evolution of Project Objectives

New Problem Focus—What-if Analysis

What-if Analysis Simulation Platform

What-if Analysis Use-Cases

What-if Analysis Evaluation Results

Conclusions and Discussion

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Overview

Literature Review

Real-world Problem Selection


New Problem Definition—What-if Analysis


What-if Analysis Evaluations



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SOLICITATION OBJECTIVE

Objectives Develop concepts and algorithms for making tactical adjustments to strategically-planned arrival and departure trajectories

Path modifications such as path-stretches, and/or

Temporal trajectory modifications such as speed adjustments

Perform human-factors analysis of the developed concept

ScopeSelect a set of three real-world problems for study

Focus on terminal airspace arrival-departure interactions

Emphasis on New York TRACON interaction-cases

Completed Tasks & DeliverablesLiterature Review Report documenting relevant previous studies

Real-world Problem Report and Briefing documenting 5 real-world problems of shared resources between arrivals and departures


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New Problem Focus—What-if Analysis





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EVOLUTION OF PROJECT

OBJECTIVESDesire to align project more closely with ATD-2 objectives

Focus on departure management

ATD-2 sites unknown, shift focus to DFW as surrogate

Series of interviews with Greg Juro/D10 TRACON

Identify DFW arrival/departure/surface interactions that complicate

scheduling of departures

DFW not a good candidate for developing tactical

departure traffic management tools

Not many arrival-departure interaction problems

Significant airspace available for last minute trajectory adjustments

Numerous strategic departure problems (e.g., meeting and resolving

multiple MITs on single aircraft, scheduling takeoffs to meet MITs,

etc.), but not many tactical control problems


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DEVELOP SURFACE-TERMINAL WHAT-IF

ANALYSIS CAPABILITY FOR CLT

Supports integration of NASA ATD-2 concept &

technologies with FAA Surface CDM Concept of

Operations

Allows NASA to credibly test different options before

finalizing concept of operations and exact configuration of

different components of ATD-2

E.g., what is the best choice for the target departure queue length

parameter for the departure metering component of ATD-2

In future, this capability can be converted into a tactical

what-if analysis tool for real-time departure planning

Part of ATD-2 real-time tactical what-if planning platform


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ATD-2

Departure Metering Program (DMP)

What-if Analysis





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ATD-2 OVERVIEWScheduling of departures within a metroplex terminal environment to increase predictability, efficiency and throughput

Compute coordinated times for pushback, spot rendezvous, takeoff, departure fix crossing

Ideal departure profile: delay at gate, unimpeded taxi, continuous climb to cruise altitude

Account for departure constraintsMerging at fixes and into overhead streams

Traffic Management Initiatives, weather impact on available fixes/routes

TMA Expected Departure Clearance

Arrival-departure flow interaction points on airport surface (e.g., shared runways, taxiways) and in terminal airspace


NASA Technologies FAA Technologies

Terminal Sequencing and Spacing (TSS) Time Based Flow Management (TBFM)

Precision Departure Release Capability

(PDRC)

Terminal Flight Data Manager (TFDM)

Spot and Runway Departure Advisor

(SARDA)

Traffic Flow Management System (TFMS)

Surface Decision Support System (SDSS)

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SURFACE COLLABORATIVE

DECISION MAKING (CDM)Improve Shared Situational Awareness to Collaboratively Optimize Airport Capacity

Efficient Management of Departure Queues and Aircraft Flow on the Airport Surface

Improve Situational Awareness to Manage Arrival Traffic Flows

Improve Analysis and Measurement of Surface Operations

Global Harmonization

Notifications


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DEPARTURE METERING

PROCEDURES (DMP) Target Movement Area entry Time (TMAT) for flights

Target Queue Length exceeds Upper Threshold

Metering times to maintain Target Queue Length

Departure Reservoir Coordinator (DRC)

Actively monitor traffic for future demand-capacity imbalances

(indicated by departure queue length)

Initiate departure metering based on the queue length predictions

Manage departure queue by setting the DMP parameter values

What-if Modeling Automation

Determine DMP parameters in real-time

Determine the impact of DMP parameter changes

Share the results with other Stakeholders


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DMP PARAMETERS

Parameter Description

• Planning Horizon • Time within which flights expected to depart could be

assigned metering times

• Departure Target

Queue Length

• Upper Threshold

• Lower Threshold

• Number of departures in the departure queue considered

optimal for the local airport

• Determine need for a DMP and reassignment of TMATs

• Determine need for compression or termination of a DMP

• Unscheduled Demand

Buffer

• Lower Threshold

• Upper Threshold

• Number of unscheduled flights identified as potential demand

• Unscheduled Flights Low notification

• Unscheduled Flights High notification

• Airport Metering • Single airport queue or multiple runway queue metering

• TMAT Compliance

Window

• Window around the TMAT within which flights are considered

compliant

• Others…


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Components

How the simulation works

Airport surface/airspace adaptation

Departure scheduling




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WHAT-IF ANALYSIS CAPABILITY

OVERVIEWFast-time simulation

Link-node model of the airport surface and terminal

airspace routes

Primary and satellite airports within a metroplex

Node queue control

Departure runways, departure fixes, and en route traffic stream

merge-points

Models current-day departure management

Sequencing for fix balancing, Approval Requests (APREQs), and

miles-in-trail restrictions to constrained merge-fixes

Alternatively models ATD-2 operations

Integrated surface-airspace traffic scheduling of Target Off Block

Times (TOBTs) for departures to shift delays to the gates


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WHAT-IF CAPABILITY COMPONENTS


Airport Surface and Terminal Airspace Departure Traffic

Simulation

ATD-2 Traffic Scheduling Algorithm Emulation

• Traffic Demand Set• Runway Capacities• Departure Fix Capacities• MIT Restrictions At Runway• MIT Restrictions At Departure Fixes• Other Traffic Management Initiatives• Runway Configuration• (primary and satellite airports)

Departure leaves gate at/near airline scheduled gate departure

time

Target Off Block Times (TOBTs) for all departures

1

2

Airport Surface and Terminal Airspace Departure Traffic

Simulation

Departure leaves gate at or near its TOBT

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HOW THE SIMULATION WORKS (1)

Link-node representation of airport

surface, terminal airspace and en

route airspace

Queuing simulation with key control

nodes located at

Terminal gate groups (by airline) at

major and satellite airports

Departure runways at major and

satellite airports

Departure fixes (metering fixes at

the boundary of the TRACON)

Center-center boundary metering

fixes (merge-fixes for the overhead

enroute traffic stream)

Gate Nodes

Departure Runway Nodes

Enroute Stream Merge Node

Departure Fix Nodes


Surface

Terminal

Enroute

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HOW THE SIMULATION WORKS (2)

Transit time & queue management models on airport

surface, terminal airspace and enroute airspace


EnrouteTerminalSurface

Departure Pushback Management

Taxi Out Time Calculation

Actual Pushback Times

Departure Takeoff Queue Management

Actual Runway Queue Entry Times

Runway to Fix Transit Time Calculation

Actual Takeoff Times

Departure Fix Queue Management

Actual Dep Fix Queue Entry Times

Actual Dep Fix Crossing Times

Dep. Fix to Enroute Merge-fix Transit Time Calculation

Actual Enroute Merge-Fix Queue Entry Time

Enroute Merge-fix Queue Management

Actual Enroute Merge Time

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ADAPTATION TO CHARLOTTE

METROPLEXParameter Source

Interacting

satellite

airports

• Concord Regional (JQF), Charlotte-Monroe Executive (EQY), Spartanburg

Downtown Memorial (SPA), Hickory Regional (HKY), Gasontia Municipal

(AKH), Rock Hill (UZA) and Statesville Regional (SVH)

• Based on FAA Optimization of Airspace and Procedures in the Metroplex

(OAPM) Study Reports

Runways • Lumped capacity model for CLT & satellite airports

Taxi times • Airline-specific ASQP model for CLT, fixed model for satellites

Departure

fixes

• ANDYS, BUCKL, DEBIE, GANTS, JACAL, LILLS, MERIL, SPA, SUG,

ZAVER

• Identified from CLT Standard Instrument Departure (SID) procedures and

departure fixes for flights in SOSS input file

• Assigned based on departure fix closest in bearing to destination airport

En route

merge points

• PSEUDO_15MIN_FROM_DF for flights via departure fix MERIL

Airborne

transit times

• Simple & Boeing physics-based models


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DEPARTURE TRAJECTORY MODEL737 NG Test Bench at Boeing Integrated Aircraft Simulation Laboratory (IASL) was utilized to perform a multitude of real-time departure simulations (MERIL7 – Charlotte)

737 Flight software and hardware working in closed-loop with high fidelity aircraft and environmental models

Obtained accurate aircraft state data versus time over 94 separate permutations of departure conditions from initial runway departure through achievement of cruise altitude at 35,000 ft.

time, altitude, calibrated airspeed, ground speed, rate-of-climb, fuel burn, …

data above delivered at each major waypoint (and archived at 1 sec intervals)

Able to see trends in the data for transit time and fuel usage variations to assist in the overall objectives of this NRA study

Hardware and software contained within this simulation framework enable some of the highest fidelity results on the performance of aircraft trajectory and state data time histories for test and evaluation of scenarios, but limited to real-time operations.

Fast-time medium fidelity aircraft simulations can be utilized for future studies of this nature that will produce acceptable levels of accuracy


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MERIL6/7 DEPARTURE PROCEDURE


MERIL

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8E,2, 28 MY 20115 m 25 JUN 2011

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DEPARTURE PROCEDURE /

GENERAL TRENDSTwo overlapping MERIL Routes were simulated

RW18L through HISOR, EATHR, TIBLE, MUNBE, LILIC, MERIL

RW18R through WEKIN, EATHR, TIBLE, MUNBE, LILIC, MERIL

Modified CDU “Legs” pages during simulation pre-flight procedures to affect routing changes

Simulation of these two routes with superimposed variations on aircraft initial conditions

Varied aircraft initial take-off weights (minimum, medium and maximum 737-700 aircraft weights)

Varied powered flight cost index values entered into CDU (0, 250 and 500)

Varied initial ground temperatures (affecting air densities and thus lift characteristics in early flight)

Wind variations (no wind, a forecast wind, a deviation of the forecast wind)

Higher cost indices (i.e., 500) cause aircraft FM logic to burn fuel faster and arrive at given respective waypoint destinations in shorter intervals of time

Superimposed weight variations show some transit time variability, with higher weight aircraft tending to arrive at destinations later, but with less of an impact on performance when compared to cost index variations

Modest (realistic) wind variations empirically show lower levels of transit time influence, given the conjecture that powered flight during the departure phase likely overwhelms these wind differences.


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EXAMPLE AIRCRAFT STATE DATA AT

WAYPOINTS FOR ONE CASE

Time

(sec)

Altitude

(ft)

CAS

(knots)

Ground

Speed

(knots)

Fuel

Burn

(lbs)

Ground

Distance

(nmi)

Flight

path

Angle

(deg)

Rate of

Climb

(ft/sec)

HISOR 115.0 4087.7 168.5 177.0 526. 3.9 8.0 42.1

EATHR 224.7 7994.5

(in level)

254.3 285.0 955.6 11.3 0.38 3.2

TIBLE 357.0 8004.5

(in level)

248.2 278.3 1140.7 21.5 -0.11 -0.9

MUNBE 548.8 7999.3

(in level)

249.7 279.9 1407.3 36.3 -0.12 -1.0

LILIC 764.8 11106.3 298.6 349.1 1910.9 53.6 1.5 15.3

MERIL 1079.1 23393.6 334.3 465.2 3028.4 90.6 2.06 28.3

State

Waypoint

Case: 133 klbs (medium Wt);Cost Index=500; rw18L; 10min Level Off


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EMULATION OF ATD-2 DEPARTURE

SCHEDULINGATD2 scheduler computes Target Off Block Times (TOBTs) for departure flights in order to

Absorb most delays at the gate

Enable departure flights to fit into available slots at the runway, with minimum taxi delays

Orchestrate the merging of departures from multiple airports to commonly shared departure fixes with minimum possible airborne delays

Coordinate takeoff times of departures to “hit” enroute merge stream gaps

Predict unimpeded times to the runway, departure-fix and enroute stream merge point

Determine earliest runway departure timesAdhere to ration-by-schedule principle

Space flights sufficiently at the runway

Delay runway departure time to “hit” enroute merge stream gaps

Apply Order of Consideration algorithm to determine sequence of departure-fix merging, back propagating delay to the surface

Emulate TMA’s Dynamic Planner algorithm


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DMP Start & End Times

DMP Target Departure Queue Length

DMP Unscheduled Demand Buffer



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WHAT-IF ANALYSIS USE CASES

Defined three Use Cases (UCs) based on hypothesized DRC activities:

UC1: DMP Start and End TimesDRC assesses candidate DMP start and end times, selects values

Time period for ATD2 scheduling of departure flight TOBTs/TMATs, accounting for all other traffic

UC2: Target Departure Queue Length (TDQL) (and Upper/Lower Bounds)

Given DMP start and end times, DRC assesses candidate departure queue lengths, selects value

TDQL of X: number of minutes of departure delay shifted from gate holding to taxiing during DMP

Departure queue slot = runway time-slot, ~1 minute

Hasten TBOT or TMAT

UC3: Unscheduled Demand BufferGiven DMP start and end times and TDQL, DRC assesses candidate capacity allocations for unscheduled demand

Reduce airport departure quarterly capacity during DMP to accommodate unscheduled traffic


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BASELINE PERFORMANCE

Two departure demand peaks, 17:00 – 20:00

Active departures exceeds 15 in 1-minute period

Runway queue exceeds 15 in 1-minute period

Options: 1 longer DMP, 2 short DMPs or other…

Consider operational complexity, other constraints besides target departure

queue length alone in specification


Departue Queue Length Baseline

--'Active Departures ' --Queued Departures

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Avg. Gate Delay Avg.Taxi Delay

Transit Phase

Avg. Airborne Delay

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UC1: START & END TIME SELECTION

Maintain number of active departures to acceptable level,

e.g., 15

Maintain gate delay to a level acceptable with occupancy

considerations for airlines

Minimize taxi delay to extent possible

Maintain airport departure throughput


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USE CASE 1: START & END TIMES

• Departure scheduling shifts taxi & airborne delay to gate

• DMP start & end times impact distribution of delay among gate, taxi,

airborne flight phases


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• DMP: 16:00 - 20:00

• DMP: 17:00 -20:00

• DMP: 17:00 - 19:00

• DMP: 17:00 - 18:00

Avg. Airborne Delay

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USE CASE 2: TARGET DEPARTURE

QUEUE LENGTHAvoid starving the runway of flights while there are active

departures

Maintain number of active departures to an acceptable

level


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Version: 1


Doc. #: 850-035977

USE CASE 2: TDQL SELECTION

• TDQL shifts gate delay to taxi & airborne phases

• Selected 3 to retain gate holding benefits while meeting acceptable

number of active departures


0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Avg. Gate Delay Avg.Taxi Delay Avg. Airborne Delay

Ave

rage

De

lay,

Min

ute

s

Transit Phase

Average Delay for Different Target Departure Queue Lengths

TDQL_0

TDQL_3

TDQL_5

TDQL_8

Page 33

•

•

• •

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Doc. #: 850-035977

USE CASE 3: UNSCHEDULED

DEMAND BUFFERAt lower levels, UDB has minimal impact on departure

queues and taxi delays

May be more appropriate to specify this parameter a priori

based on typical unscheduled demand levels and apply to

DMP rather than design on the fly


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US

E C

AS

E 3

: UN

SC

HE

DU

LE

D

DE

MA

ND

BU

FF

ER

Page 3

5C

OM

PA

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valu

ate

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nschedule

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em

and B

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rs o

f 1, 3

, 5, 8

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re c

apacity

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cte

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to a

fford

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epartu

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as p

ossib

le w

ithout

incre

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15:01

15:11

15:21

15:31

15:41

15:51

16:01

Number of Departures f-.> f-.> N N W W ./:>

0 ~ 0 ~ 0 ~ 0 ~ 0

16:11 I 16:21 )> c 16:31 Q. C tD 16:41 ~- C "g 16:51 ~ C:, ""' 17:01 ~ II 2' 17:11 ~ ~ tD 17:21 ._.,._.....__ V, ~ 0

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18: 51 V,

19:01

19:11

19:21

19:31

19:41

19:51

20:01

20:11

20:21

Version: 1


Doc. #: 850-035977

USE CASE 3: UNSCHEDULED

DEMAND BUFFER

• UDB has minimal impact on transit delay at low buffer levels

• Select value which maintains gate delay


2.0

"' ~ ::I .5 2 1.5 > "' ai C ~ 1.0 "' .. QI ::, <t

0.5

0.0

Average Delay for Different Target Departure Queue Lengths


Transit Phase

Avg. Ai rborne Delay

• UDB 0

• UDB 1

• UDB 3

• UDB 5

• UDB 8

Version: 1


Doc. #: 850-035977

IMPACT OF UNCERTAINTY

Initial evaluation of the impact of transit time uncertainty on

effectiveness of DMP

Incorporate transit time uncertainty models into CLT surface traffic

simulation, conduct 100 simulation runs

Evaluate resulting performance of airport surface traffic under

specified DMP parameters

Data sources

Taxi transit time

Airline-specific ASQP taxi-time data for CLT up to 10th percentile

Terminal airspace transit time

Adapt & apply data from Boeing simulations of MERIL7 SID

En route airspace transit

10-minute mean transit time, standard deviation based on

Boeing terminal airspace transit data

Assume each is Normally distributed as per mean and standard

deviation for each


0 0

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Doc. #: 850-035977

NUMBER OF DEPARTURES


• Modest range of number of aircraft on the airport surface with differences of

~3-5 aircraft during peak demand periods

Variability in Number of Active Departures 2s~-~--~-~-~-~-~-...,.c--~-~-~-~-~--'--~-~-~~-~-~~----~------_~_-~~

20

Ill I!! ,E 15 ns CL

8 0 ... GI

~ 10 ::, z

5

~ Minimum ----- Maximum

15:30 15:45 16:00 16:15 16:30 16:45 17:00 17:15 17:30 17:45 18:00 18:15 18:30 18:45 19:00 19:15 19:30 19:45 20:00

Time, Hours

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Doc. #: 850-035977

DEPARTURE QUEUE LENGTH


• Modest range of the number of aircraft in the departure queue with

differences of ~2-5 aircraft during peak demand periods

Variability in Departure Queue Length 15~-~-~-~-~-~-~-~-~-~-~-~~-~-~-~-~-_,,._-~-~~

Ill 10 l!! :, t: co 0.

~ 0 ... QI JJ E :,

z 5

_,._ Minimum _,._ Maximum

15:3015:4516:0016:1516:3016:4517:0017:1517:3017:4518:0018:1518:3018:4519:0019:1519:3019:4520:00

Time, Hours

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AVERAGE DELAY BY FLIGHT PHASE


• Modest range of taxi delays experienced with differences of ~1.0 minutes in

mean taxi delay of aircraft

Variability in Average Transit Delay 3.5 ~----~---------~-~---~---~-~--------,::-~~======::;-a

- Minimum • Maximum

3

0.5

0 Gate Taxi Terminal Enroute

Transit Phase

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Doc. #: 850-035977









0

0

0

0

0

0

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Doc. #: 850-035977

CONCLUSIONS & DISCUSSION

Evaluation of the What-if Analysis capability indicates the

potential to improve the DMP parameter selection process

Use Case Evaluation

Number of flights in the ramp + movement area is a key control

parameter

Above N is a good indicator of when to start a DMP

Below N is a good indicator of when to end a DMP

May not be possible to precisely control the departure queue length,

but TDQL is effective in tuning departure throughput

The unscheduled demand buffer may not have any positive effect

without an estimate of when unscheduled flights might appear

Transit time uncertainties introduce some variability in the surface

traffic levels and flight delays realized with a DMP


C 0

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BACKUP


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Doc. #: 850-035977

LITERATURE REVIEW

Focus on precision methods of arrival and departure

management in the terminal area

Summary of literature in areas including

scheduling concepts

schedule conformance

off-nominal situations

evaluations of tools and gaps identified

technological requirements for tools

management of arrival-departure interactions

airport surface traffic management

metroplex operations


0 0

0

0

0

0

0

0

0

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Doc. #: 850-035977

REAL-WORLD PROBLEM SELECTION

Select five high-priority arrival-departure interactions from

metroplex or single-airport sites

Literature review, subject matter expert consultation, data

analysis to identify & evaluate

Compared & selected sites via numerous factors

Presence of significant departure delays

Presence of significant arrival delays

Dependent runway usage

Problem site in the FAA FACT-2 Report

Complexity of arrival-departure TRACON airspace

Others


0 0

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0

0

0

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Doc. #: 850-035977

REAL-WORLD PROBLEM SITESSite Reason for Selecting

New York

metroplex

High departure and arrival delays at all component airports; highly complex terminal airspace; multiple

runway interaction geometry-types present at different metroplex airports; interest from NASA; SMEs

identified multiple existing problems that can be solved by tactical scheduling decision support tools

Charlotte

International

Airport

High departure delays; significant potential for saving departure delays by better traffic management;

intersecting arrival-departure runways; multiple points where taxiing aircraft cross active arrival and

departure runways; restricted ramp area causing arrival-departure interactions; presence of

interactions between departure flows and overhead en route streams; interest from NASA; SMEs

identified airspace interaction problems that can be solved by strategic/tactical temporal scheduling

Southern

California

metroplex

Presence of significant departure delay, mixed-use runway at LAX, limited space for building queues to

hold aircraft while they wait to cross active runways identified as a major problem; SMEs identified

number of high-priority terminal airspace interactions that may be resolved by strategic or temporal

trajectory control methods

Atlanta

Hartsfield

International

Airport

High departure delays; significant potential for saving departure delays by better departure

management; two closely spaced parallel runway pairs, frequently used for simultaneous arrival and

departure operations

Northern

California

metroplex

Three airports within close proximity display multiple interdependencies, intersecting runway pairs at

SFO create a unique scheduling problem, limited space for building queues to hold aircraft while they

wait to cross active runways identified as a problem


Version: 1


Doc. #: 850-035977

REAL-WORLD PROBLEMS

PROPOSED

Problem Description

1) JFK 22R departures interacting with

JFK 22L/22R arrivals

JFK 22R departures tunnel under the JFK 22L/22R

arrivals at 5000 feet for 20-25 miles

2) JFK Arrivals on VOR 13L, interact

with LGA 13 ILS arrivals and LGA 13

departures

Indirect routing of LGA 13 departures to avoid JFK

13L arrivals via VOR approach using Coney

airspace; significant source of delay

3) EWR Arr-22L, Dep-22R; TEB Dep-

19: TEB departures interact with EWR

arrivals

TEB 19 departures via noise abatement procedure

require 10 MIT gaps in EWR 22L arrivals

4) CLT runway operations—integrated

arrival-departure-surface interaction

18C arrivals & departures, 18L & 18C departures

with 23 arrivals, 18R arrivals crossing 18C

departures & arrivals, call for release of departures

5) LAX runway system interactions Arrivals to outboard runways crossing inboard

departure runways, mixed-use of inboard runways


Version: 1


Doc. #: 850-035977

AIRPORT SURFACE/TERMINAL

AIRSPACE ADAPTATIONInteracting satellite airports

Identified from FAA Optimization of Airspace and Procedures in the Metroplex (OAPM) Study Reports

Departure fix & enroute merge point locationsBased on CLT Standard Instrument Departure (SID) procedures and departure fixes for flights in SOSS input file

Departure fix/runway assignmentBased on actual assignment data where available

Otherwise, assign flight to departure fix closest in bearing to destination airport, relative to origin airport

Runway assignment based on departure fix

Taxi TimesUnimpeded times based on ASQP taxi time data

Airborne transit timesPhysics based model: Simple Model, Boeing Model


0 0

0

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Doc. #: 850-035977

SIMULATION CONTROLS AND

EVALUATION METRICS

Calculations within simulated traffic management DSTs are controlled by the parameters such as Target Departure Queue Length, Static Time Horizon, etc.

What-if analysis capability allows fast evaluations over different values of individual parameters and combinations

Manual mode: Test performance at a few user-defined points in the parameter space

Auto mode: Sweep over a range of parameter values

Key metrics are computed by simulating traffic over a user-defined time-horizon for each combination of parameter settings

Metrics are displayed on a succinct display that is easy for a Departure Reservoir Coordinator (DRC) to comprehend quickly and make informed decisions


Version: 1


Doc. #: 850-035977

UC1: DMP START AND END TIMES

DRC determines start and end times of DMP

Detects demand-capacity imbalance for runways

Baseline simulations

Analyzes Departure Queue Graph, Departure Fix Load Graph, Enroute Merge

Point Load Graph

Determines candidate start/end times to evaluate

Selection criteria

Conducts what-if analysis for discrete start/end time combinations

ATD-2 scheduling and simulations

Selects discrete start/end times based on airport traffic performance criteria

Start/end times to 15-minute precision, similar to JFK DMAN


0 C

C

C

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Doc. #: 850-035977

UC2: TARGET DEPARTURE QUEUE

LENGTH (TDQL) AND UPPER/LOWER

BOUNDS

DRC determines the TDQL and its upper/lower bounds,

airport-wide or per-runway

DMP start and end times established

Determines candidate TDQL and bounds to test

Conducts what-if analysis for discrete TDQL and upper/lower bound

values

ATD-2 scheduling and simulations

Selects TDQL and upper/lower bound values based on airport traffic

performance criteria

ATD-2 performance evaluation

Selects policy to manage event of excessive mismatch between

actual and target departure queue length



0

0

0

Version: 1


Doc. #: 850-035977

UC3: UNSCHEDULED DEMAND

BUFFERDRC determines Unscheduled Demand Buffer (UDB) of

DMP

DMP start and end times, TDQL and upper/lower bounds established

Determines individual or range of UDB values to test

Conducts what-if analysis for discrete UDB values

Selects UDB values based on airport traffic performance criteria



0

0

0

0

Version: 1


Doc. #: 850-035977

DEPARTURE METERING PROGRAM


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UC

1: D

MP

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35977

UC

2: T

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Version: 1


Doc. #: 850-035977

UC3: UDB SELECTION

0

5

10

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Departue Queue LengthUDB = 1% of Capacity

Active Departures Queued Departures

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Final Briefing for NASA CTD-Subtopic 1 NRA: Methods of ... · 29/10/2015 · BASE YEAR FINAL PRESENTATION NASA CTD-SUBTOPIC 1 NRA: METHODS OF INCREASING TERMINAL AIRSPACE FLEXIBILITY