Application of Monte-Carlo Simulation to Noise Abatement Approach Procedure Design Liling Ren, Nhut Tan Ho, and John-Paul B. Clarke Massachusetts Institute of Technology First DLR/Lufthansa/MIT Workshop Lufthansa Training Center Seeheim, Germany, 17-Aug-2004

Part of the work presented here is based on the joint effort of Acknowledgement Part of the work presented here is based on the joint effort of Boeing, FAA, MIT, NASA, UPS and Louisville Regional Airport Authority

Agenda Introduction Overview of Noise Abatement Approach Procedure Design Monte-Carlo Simulation Tool Separation Analysis Methodology Louisville (SDF) Case Study Wind Analysis Traffic Analysis Weight Analysis ATC altitude constraints analysis Initial Separation Analysis

Introduction Aircraft Noise Is: Noise Control Measures A critical problem at many airports Example: as of 2002, O'Hare has spent $197.5 million* on sound isolation for 79 schools significantly affected by aircraft noise A limiting factor for aircraft operations and airport expansion Noise Control Measures Quieter aircraft How about existing fleet? Airport restrictions and curfews Low noise operation procedures Fly preferable paths, and Departure procedures - essentially redistribute noise impact Steeper climb; slower acceleration; thrust cut back Arrival procedures - reduce noise generated, increase height Procedures provide additional noise benefit for any given aircraft * Source: O’Hare International Airport, 2002

Focus on Approach Procedures Why Approach Procedures Arrival noise contributes an increasing proportion, due to the 3° ILS glideslope constraint * Noise, and additional emission reduction and cost saving benefits Challenging issues in implementation Typical Noise Abatement Approach Procedures Vertically segmented descent (part of descent is steeper) Low Power Low Drag approach (LPLD) Early intercepting of final glide slope 3 degree decelerating approach (TDDA/Modified TDDA) Continuous descent approach (CDA) / RNAV based CDA Technology Opportunity GPS based Area Navigation (RNAV) Flight Management System (FMS) * Kershaw et al. 2000

Low Noise Procedure Framework Low noise descent leg starts from an intermediate metering point Controller free to apply vectoring before this point, and establishes initial separation and initial speed at this point Preferably no controller intervention during low noise descent leg The intermediate metering point determined by traffic conditions Lower traffic flow allow higher intermediate metering point, more fuel savings Height  Streaming/Sequencing Spacing Monitoring Intervention Descent from Cruise Initial Approach Low Nose Descent Leg Missed App. Low Noise Conventional FAF Wake Vertex Separation 4 - 6 nm Initial Separation Established (c) 17-Aug-2004

Low Noise Descent Leg Design RNAV Lateral Flight Path Keep the path shortest if possible, save fuel and time Avoid flying over noise sensitive areas Adjust path length to satisfy pre-existing ATC constraints Coupled with vertical profile design Vertical Profile Key factors for lower noise during approach Low power settings, preferably idle Higher flight path than conventional Eliminate level segments at low altitude Avoid constant low speed segment if possible Use speed /altitude constraint to adjust deceleration/flight path angle Lower deceleration gives steeper idle descent flight path Coupled with lateral flight path to meet ATC constraints Local wind conditions must be taking into account

Low Noise Descent Leg Design FMS RNAV CDA procedure Idle descent path from top of descent down to 1st vertical (altitude/speed) constraint computed by FMS Deceleration before speed transition and that before 1st constraint based on 500 ft/min descent rate 10,000 ft FMS computed flight path angle (assuming idle thrust) Speed transition Missed App. 240 KCAS (c) 17-Aug-2004 2nd vertical constraint Final configuration 1,000 ft ILS glideslope flight path angle 1st vertical constraint Computed Final app speed Speed Profile Altitude Profile

Simulation Software MIT Fast-Time Aircraft Simulator MATLAB Based 2001, Initial Version 2D longitudinal model, straight in approach With pilot action delay model, Monte-Carlo scheme Aircraft specific code 2002 Version 2D plus pitch for better accuracy, also improved efficiency Added wind effects 2003 Version System fully redesigned, became aircraft independent code Added lateral motion, added INM interface Current Version Added VNAV capability and new aircraft types With help from David H. Williams (NASA) and Kevin R. Elmer (Boeing)

Simulation Software Aircraft Dynamics Control Architecture Non-steady-state force equations Generic side force model Assume proper rotational control by aircraft control systems Avoided use of moment equations For simplicity and proper behavior under winds and turbulence Control Architecture FMS module builds flight path, provides autopilot control command and pilot cue Autopilot module performs thrust and aircraft attitude control Pilot module controls flap, speed brake and gear extension Pilot action delay model Mean delay time with random variation Parameters extracted from previous motion simulator experiment

Simulation Inputs Approach Procedure Definitions Lateral path defined by waypoints Lateral control modes: LNAV or non-LNAV (hdg-hold etc.) Vertical path defined by vertical constraints, starting altitude, runway threshold elevation and ILS glide slope Vertical control modes: VNAV or non-VNAV (Alt-Hold etc.) Aircraft Configuration Aircraft weight at starting altitude Final approach speed, fixed value or based on VREF Flap schedule, by speed (may be VREF based), altitude, or distance to runway Wind Profile External wind profile, as a function of altitude, or time, or location FMS wind forecast

Typical Simulation Results B757-200, RNAV Based CDA

Interface with Noise Models Built in interface to Integrated Noise Model (INM) Compatible trajectory data format with MIT Noise Prediction Tool The upper right graph is the MTDDA speed profile for B747-400 and the lower right graph is the MTDDA speed profile for B737-300. We see that final approach speed reached at about 2.5 nm to the threshold. The speed variation is also much smaller. The noise impact can be seen from the thrust profile. We see that the thrust required for initial speed hold is significantly lower than both that required for initial level flight and that required for maintain the final approach speed. Given that the altitude where initial speed hold is performed is high, the impact of initial speed hold on noise benefits is minimal. The possible noise benefit compromise due to early reaching of final approach speed no longer exists in MTDDA. INM 6.1 Noise Contour Based on Simulated Trajectory

Separation Analysis Methodology

SDF CDA Case Study Multiple-aircraft RNAV based CDA procedures for UPS west flow landing to runway 17R and 35L Determine variation in performance Performance variations due to: Wind Pilot actions Aircraft type (B757-200 versus B767-300) Aircraft weight Identify potential problems for further study ATC Constraint Compatibility Analysis Separation Analysis Analyze separation changes along the course of CDA descent Recommend miles-in-trial spacing at intermediate altitude

Wind Analysis Data Source Data Content National Oceanic and Atmospheric Administration (NOAA) Forecast Systems Laboratory (FSL) Aircraft Report Data Decoded and quality controlled ACARS/AMDAR automated weather reports from commercial aircraft Provided in web-based graphical displays, or as downloadable binary data in netCDF (network Common Data Form) Real time with 12 minutes delay, historical data available for 30 days Data may be used for research use, request access from FSL Data Content Latitude, longitude, altitude, observation time Wind direction, wind speed Temperature, downlinked relative humidity Heading, mach number, aircraft roll angle flag Originating airport & destination airport Very limited reports on gust and icing conditions etc.

Wind Analysis Using Binary Data Collecting Data Data Processing Higher resolution More efficient for batch and automatic processing Collecting Data Data has been collected at daily bases since February 10, 2004 Covers the airspace within 100 nm from SDF Covers reports starting 03 hours UTC for 5 hours each day 22:00 – 3:00 hours EST, covers most UPS night arrivals Will gain access to historical data from the past 2 years Data Processing Developed a c based software tool to extract weather information from raw binary data, and export it into MATLAB m file MATLAB code has been developed to filter, and process data Raw data are kept intact for further analysis

Wind Analysis Filtered Flight Tracks Reports from west of SDF that can form arrival/departure tracks Closely reflect what would be experienced in CDA to SDF Data points show spatial distribution of reports in a two-month period

Wind Analysis Filtered Flight Tracks Side view

Wind Analysis Filtered Flight Tracks Plan view

Wind Statistical Analysis Method Wind report of filtered flight tracks linearly interpolated at a set of altitudes with 1,000 ft interval All interpolated data points at a given altitude analyzed together and gave statistics at that altitude Mean wind speed and standard deviation computed based on the absolute wind speed value of each interpolated data point Mean wind direction is computed based on the wind direction of each interpolated data point using unit vector method (not weighted)

Interpolated Wind Data Point Distribution at 3,000 ft and 11,000 ft Data Point Distribution Shows the Variation of Wind Speed and Direction (Wind speed in meters per second. Feb 10 to May 18, 2004)

Mean, 2σ and Maximum Wind High altitude data not reliable due to lack of reports. Feb 10 to August 12, 2004

Special Winds Defined to Reflect Some Extreme Conditions Mean and 2σ from Southwest For runway 17R configurations Speed same as regular mean and 2σ Direction manually picked from data points from southwest with similar wind speed Mean and 2σ from Northwest For runway 35L configurations points from northwest with similar SW Mean NW

Daily Wind Variation Reflects wind changes within the same day Daily σ obtained from flights on the same day (5 hour period) Mean daily σ throughout the data collection period was selected 30 210 60 240 90 270 120 300 150 330 180 Data Points at 7000 ft Daily Variation Mean Wind Data Points Show Wind Variation over a Four Month Period

FMS Use of Wind Limited use of wind forecast by FMS during descent, in general, benefits of very detailed wind forecast for FMS would be limited Since FMS will mix the current wind measurement with wind forecast when computing vertical path, even if no wind forecast is entered, the vertical path will still be different for different winds When there is significant change in wind, or when wind at lower altitude is relatively strong and has a different direction, the execution of the planned vertical path may be affected

SDF UPS Night Arrival Traffic April 14-15, 2003, Landing to Runway 17R Data Source: Passur SDF airport monitoring website

SDF UPS Night Arrival Traffic April 14-15, 2003, Last Block from West to 17R

SDF UPS Night Arrival Traffic April 14-15, 2003, Time of Arrival at 17R Threshold The arrival rate of the last block from west was roughly 16 aircraft per hour Peak arrival rate was roughly 24 aircraft per hour

Aircraft Type and Weight B757-200 and B767-300 Representing last block UPS traffic from the west VNAV descent, autothrottle engaged Aircraft Landing Weight Aircraft landing weight depicts normal distribution Fixed landing weight: min, max and mean Random weight: normal distribution bounded by min and max Based on data provided by Jeff Firth, Bob Hilb, and James Walton from UPS B757-200, 1-Month Period 5 10 15 20 25 30 Landing Weight (Klb) Frequency B767-300, 1-Month Period 5 10 15 20 25 Landing Weight (Klb) Frequency

RNAV CDA, CHR25/CRD25 Option Chart From David H. Williams (NASA) and James Walton (UPS)

ATC Constraint Analysis ATC Altitude Constraint at CHERI Currently Indianapolis Air Route Traffic Control Center (Indy ARTCC) can only clear aircraft down to 11,000 ft at CHERI Need estimate the range of altitude variation at CHERI for aircraft perform CDA, so that procedure design or ATC agreement can be made accordingly Simulation Setup B757-200 and B767-300 Max and minimum aircraft weight Zero, mean, 2σ wind conditions No pilot delay variation, less significant factor for large wind variation Simulation Results (for BLGRS and CRD25 Option) Altitude at CHERI ranges from 10,509 ft to 15471 (2-Aug-2004 simulation setting)

Steady 2σ Wind Initial Separation SACKO selected as the intermediate metering point 2σ steady wind condition was analyzed Minimum separation requirement determines separation in time between aircraft at metering point Larger initial groundspeed require larger initial separation 2σ wind is a strong tail wind condition at SDF, thus would give larger groundspeed, 2σ wind represents the case of worst case initial separation Uses min and max landing weights No pilot action delay variation Less significant factor for 2σ wind, assume consistent pilot procedure will be used Aircraft descend from 31,000 ft at 330 KCAS

Steady 2σ Wind Initial Separation Initial Separation Analysis Matrix Aircraft Sequencing Leading AC Trailing AC Wake Vortex Separation B757-200 B757-200 4 nm B757-200 B767-300 4 nm B767-300 B757-200 5 nm B767-300 B767-300 4 nm Require wake vortex separations to be satisfied at runway threshold Aircraft Weight B767-300 min, max B757-200 min, max Runway Configuration Runway 1R Runway 35L A total of 32 combinations, the separation analysis methodology is applied to each of them

Steady 2σ Wind Initial Separation Sample Results: B767-300 followed by B757-200 Landing to runway 35L Wake vortex separation required at runway threshold 5 nm Required initial separation at SACKO for the four combinations Average capacity 24.56 aircraft per hour These cases requires largest initial separations Higher intermediate metering point, bad aircraft sequencing (2-Aug-2004 simulation setting) Trailing AC Leading AC B757-200 Min Max B767-300 22.64 nm 20.83 nm 21.00 nm 19.24 nm

Steady 2σ Wind Initial Separation Sample Results: B757-200 followed by B7657-300 Landing to runway 17R Wake vortex separation required at runway threshold 4 nm Required initial separation at SACKO for the four combinations Average capacity 39.28 aircraft per hour These cases requires smallest initial separations Lower intermediate metering point, good aircraft sequencing (2-Aug-2004 simulation setting) Trailing AC Leading AC B767-300 Min Max B757-200 12.23 11.58

Full Monte-Carlo Simulation SACKO selected as the intermediate metering point Mean wind condition as an example Representing most common wind conditions Daily random wind variation presenting worst wind variation between flights Random aircraft weight Normally distributed aircraft weight bounded by max and min Random pilot action delay variation Aircraft descend from 31,000 ft at 330 KCAS Initial descent speed at SACKO is targeted at 330 KCAS but actual simulation maybe different

SDF RNAV CDA Landing 17R Time and Speed Variation – B757-200 Landing 17R (10-AUG-2004 Simulation Setting)

SDF RNAV CDA Landing 17R Time and Speed Variation – B767-300 Landing 17R (10-AUG-2004 Simulation Setting)

SDF RNAV CDA Landing 17R Final Separation at Runway Threshold: 4/5 nm Separation at SACKO Point B757-200/B757-200: 140.2 sec time interval, or 25.7 aircraft per hour 18.25 nm initial separation B757-200/B767-300: 127.2 sec time interval, or 28.3 aircraft per hour 15.83 nm initial separation B767-300/B757-200: 158.8 sec time interval, or 22.7 aircraft per hour 20.67 nm initial separation B767-300/B767-300: 122.7 sec time interval, or 29.3 aircraft per hour 15.26 nm initial separation Average: 15.26 - 20.67 nm initial separation, gives 26.5 aircraft per hour

SDF RNAV CDA Landing 35L Time and Speed Variation – B757-200 Landing 35L (10-AUG-2004 Simulation Setting)

SDF RNAV CDA Landing 35L Time and Speed Variation – B767-300 Landing 35L (10-AUG-2004 Simulation Setting)

SDF RNAV CDA Landing 35L Final Separation at Runway Threshold: 4/5 nm Separation at SACKO Point B757-200/B757-200: 138.7 sec time interval, or 26.0 aircraft per hour 18.81 nm initial separation B757-200/B767-300: 121.21 sec time interval, or 29.7 aircraft per hour 15.88 nm initial separation B767-300/B757-200: 166.5 sec time interval, or 21.6 aircraft per hour 22.60 nm initial separation B767-300/B767-300: 126.1 sec time interval, or 28.5 aircraft per hour 16.53 nm initial separation Average: 15.88 - 22.60 nm initial separation, gives 26.9 aircraft per hour

Reduced Final Separation SDF RNAV CDA Landing 17R Final separation reduced to 2.5 nm Separation at SACKO Point B757-200/B757-200: 98.3 sec time interval, or 36.6 aircraft per hour 12.80 nm initial separation B757-200/B767-300: 87.3 sec time interval, or 41.2 aircraft per hour 10.86 nm initial separation B767-300/B757-200: 93.6 sec time interval, or 38.4 aircraft per hour 12.21 nm initial separation B767-300/B767-300: 82.7 sec time interval, or 43.5 aircraft per hour 10.30 nm initial separation Average: 10.30 – 12.80 nm initial separation, gives 39.9 aircraft per hour

Reduced Final Separation SDF RNAV CDA Landing 35L Final separation reduced to 2.5 nm Separation at SACKO Point B757-200/B757-200: 97.4 sec time interval, or 37.0 aircraft per hour 13.22 nm initial separation B757-200/B767-300: 80.0 sec time interval, or 45.0 aircraft per hour 10.48 nm initial separation B767-300/B757-200: 102.3 sec time interval, or 35.18 aircraft per hour 13.88 nm initial separation B767-300/B767-300: 84.9 sec time interval, or 42.4 aircraft per hour 11.12 nm initial separation Average: 11.12 – 13.88 nm initial separation, gives 39.9 aircraft per hour

Simulation Discussion Monte-Carlo Simulation Finding New Things Monte-Carlo simulation revealed that at low aircraft landing weights, it’s very difficult to decelerate if flaps are extended at recommended speeds based on VREF This could easily be ignored if Monte-Carlo simulation were not used, internalized particular experience may not speak out loud The simulation results thus suggested revising the altitude/speed constraints and/or pilot procedures developed for CDA Fast Simulation We showed results from few simulation condition settings, however, for noise abatement procedures design, large number of condition settings shall be studied The Monte-Carlo scheme presented is flexible for different condition settings, and it is fast-time, can be executed in batch mode

Simulation Discussion Separation Analysis In the case shown, the separation method gave results that would meet ‘100%’ cases, the required initial separations are large Directly applied, they would not yield optimal noise reduction results in many cases Airline schedule may be disrupted and may causes extra-delays If final approach separation can be relaxed, or if not all cases are to be met (such as 95%, not shown here), the required initial separation can be significantly reduced This means if occasionally the initial separation gets lower, the safety requirements can still be satisfied Or, when potential violation is predicted, air traffic controller can always intervene This is true for the SDF project, it would probably be applicable to many other projects

Simulation Discussion Pilot action is the most difficult part to simulate Speed brake application Throttle control when autothrottle is not engaged Need data from pilot-in-the-loop flight test/experiment to support modeling Trajectory variation due this can be reduced through pilot procedure design and proper training Other Issues?