noise power distance re-evaluation
TRANSCRIPT
FAA CENTER OF EXCELLENCE FOR ALTERNATIVE JET FUELS & ENVIRONMENT
Lead investigator: Dimitri Mavris (PI), Chris Perullo (Co-I)Presenter: Greg Busch
Project manager: Hua (Bill) He (FAA)
Noise Power Distance Re-evaluationProject 43
April 3 & 4, 2018Boston, MA
Opinions, findings, conclusions and recommendations expressed in this material are those of the author(s)and do not necessarily reflect the views of ASCENT sponsor organizations.
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How Does It All Fit Together?
• Multiple projects leveraging information to inform AEDT predictions
• Projects shown are focused on noise, not meant to exclude other ASCENT funded work supporting AEDT
ASCENT 35Estimate Reduced Thrust Takeoff
Refine Takeoff Weight Assumptions
ASCENT 43Determine Impact of NPD+C
ASCENT 45Model More Representative
Departure Procedures
ASCENT 23More accurate departure and arrival
Noise estimates from adv. procedures
*MIT
AE
DTNow
VOLPEAEDT Flap Setting
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Project 43 Goals
• Goals– Understand the sensitivity of including aircraft configuration
changes and speed in NPDs on resulting noise contours– Provide physics-based recommendation on format of NPD +
Configuration (NPD+C) curves for use in AEDT
• Project Impact– Quantify improvement to noise contour prediction from including
aircraft configuration information
• Objectives– Study representative fleet mixes and aircraft sizes– Validation against available measurement data, where available– Maintain compatibility with existing NPD (integrated model)
approach
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ASCENT Project 43 Overview (Year 1)• Objectives
– Understand the sensitivity of including aircraft configuration changes and reference speed in NPDs on resulting noise contours for 50 – 400 PAX
– Provide physics-based recommendations on format of NPD + Configuration (NPD+C) curves for use in AEDT
– Maintain compatibility as much as possible with existing NPD approach
• NPD Modeling Overview
ANOPP
AEDT NPD+C
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Summary of Key Findings (Year 1)
Grouping Study ParametersBaseline 0 Baseline NPD
Main EffectsI.A Include only speedI.B Include only flaps/slatsI.C Include only gear
Cross TermsII.A Speed + GearII.B Speed + FlapsII.C Gear + FlapsII.D Speed + Gear + Flaps
SEL Contour Area Variation for
Approach and Departure
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Summary of Key Findings (Year 1)
Grouping Study ParametersBaseline 0 Baseline NPD
Main EffectsI.A Include only speedI.B Include only flaps/slatsI.C Include only gear
Cross TermsII.A Speed + GearII.B Speed + FlapsII.C Gear + FlapsII.D Speed + Gear + Flaps
Studies Correspond to Table at right
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Summary of Key Findings (Year 1)
Bar shows variation in contour
area across size classes
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Summary of Key Findings (Year 1)
• The presence of the speed dimension in the NPD+C curves has the most significant impact in the overall noise contour obtained from running the modified AEDT environment
• Departure procedures are less affected by the modifications– Jet source noise is dominant– Velocity corrections at higher reference speeds are negative
• Impact is mostly an area decrease difference due to:– Changes in source noise with velocity– The velocity corrections having a great impact in the final total SEL value for the given grid point
Grouping Study ParametersBaseline 0 Baseline NPD
Main EffectsI.A Include only speedI.B Include only flaps/slatsI.C Include only gear
Cross TermsII.A Speed + GearII.B Speed + FlapsII.C Gear + FlapsII.D Speed + Gear + Flaps
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Year 2 Project Goals
• Goal– Provide a method for expanding and implementing NPD+Cs into
AEDT
• Project Impact– Previous year study was performed using existing detailed analysis
models (ANOPP2)– Not practical to create detailed ANOPP2 models for every AEDT
database vehicle– Develop a method to facilitate implementation correction functions
to database NPD+Cs
• Objectives – Quantify sensitivity of corrections to aircraft configuration as well as
aircraft and engine design inputs– Understand the sensitivity of configuration and design inputs in
order to develop correction factors– Study sensitivities to various noise sources– Develop correction functions for NPD+Cs– Validate correction functions with ANOPP2 or data (if available)
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Phase IIIPhase II.BPhase II.APhase I
Flow Chart: Overview
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Phase IIIPhase II.BPhase II.APhase I
[Complete]
Flow Chart: Overview
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Sensitivity Approach
Power (Thrust)
No
ise
1) Identify Major Noise Sources & Relative Contribution
JetFlap
Fan
No
ise
Co
ntr
ibution
Flap
FanJet
&2) For Each Source -> Identify Physical Drivers
No
ise
Co
ntr
ibution
Flap
FanJet
*All data on this slide is provided as an example for illustrative purposes only
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Top Contributors to Total Noise –Approach: 150pax
LEGENDSlatFlapWingGearFanCoreJet
Distance First Contributor to Noise: 150pax
25,000 Flap Flap Flap
16,000 Flap Flap Flap
10,000 Flap Flap Flap
6,300 Flap Flap Fan
4,000 Flap Fan Fan
2,000 Flap Fan Fan
1,000 Flap Fan Fan
630 Flap Fan Fan
400 Flap Fan Fan
200 Flap Fan Fan
10% 20% 30%% Thrust
Distance Second Contributor to Noise: 150pax
25,000 Slat Slat Slat
16,000 Slat Slat Core
10,000 Slat Slat Fan
6,300 Slat Fan Flap
4,000 Slat Flap Flap
2,000 Slat Flap Flap
1,000 Fan Flap Flap
630 Fan Flap Flap
400 Fan Flap Flap
200 Fan Flap Flap
10% 20% 30%% Thrust
Distance Third Contributor to Noise: 150pax
25,000 Wing Wing Core
16,000 Wing Wing Slat
10,000 Wing Fan Core
6,300 Wing Slat Core
4,000 Wing Slat Core
2,000 Fan Slat Core
1,000 Slat Slat Core
630 Slat Slat Core
400 Slat Slat Core
200 Slat Slat Slat
10% 20% 30%% Thrust
• Plots show which noise sources contribute most (top three) to the overall SEL at each attitude/thrust combination in a traditional NPD
• Approach is primarily dominated by flap, fan, & slat noise with wing and core noise being secondary players
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Top Contributors to Total Noise –Departure: 150pax
• Plots show which noise sources contribute most (top three) to the overall SEL at each attitude/thrust combination in a traditional NPD
• Departure is primarily dominated by Fan, Jet, Flap & Core Noise
Distance First Contributor to Noise: 150pax
25,000 Flap Jet Jet Jet Jet Jet Jet
16,000 Flap Jet Jet Jet Jet Jet Jet
10,000 Flap Jet Jet Jet Jet Jet Jet
6,300 Fan Jet Jet Jet Jet Jet Jet
4,000 Fan Fan Jet Jet Jet Jet Jet
2,000 Fan Fan Fan Jet Jet Jet Jet
1,000 Fan Fan Fan Fan Jet Jet Jet
630 Fan Fan Fan Fan Fan Jet Jet
400 Fan Fan Fan Fan Fan Jet Jet
200 Fan Fan Fan Fan Fan Jet Jet
40% 50% 60% 70% 80% 90% 100%% Thrust
Distance Second Contributor to Noise: 150pax
25,000 Jet Flap Flap Core Core Core Core
16,000 Jet Flap Core Core Core Core Core
10,000 Fan Core Core Core Core Core Core
6,300 Flap Fan Fan Fan Core Core Core
4,000 Flap Jet Fan Fan Fan Fan Fan
2,000 Flap Jet Jet Fan Fan Fan Fan
1,000 Flap Jet Jet Jet Fan Fan Fan
630 Flap Jet Jet Jet Jet Fan Fan
400 Flap Jet Jet Jet Jet Fan Fan
200 Flap Jet Jet Jet Jet Fan Fan
40% 50% 60% 70% 80% 90% 100%% Thrust
Distance Third Contributor to Noise: 150pax
25,000 Core Core Core Flap Flap Flap Fan
16,000 Core Core Flap Flap Flap Fan Fan
10,000 Core Flap Fan Fan Fan Fan Fan
6,300 Core Core Core Core Fan Fan Fan
4,000 Core Core Core Core Core Core Core
2,000 Core Core Core Core Core Core Core
1,000 Core Core Core Core Core Core Core
630 Core Core Core Core Core Core Core
400 Core Core Core Core Core Core Core
200 Core Core Core Core Core Core Core
40% 50% 60% 70% 80% 90% 100%% Thrust
LEGENDSlatFlapWingGearFanCoreJet
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Approach Fundamental Noise Drivers
Single Aisle
Deflection Angle Primary
Noise Driver for Approach
Performed top driver analysis for
each power-distance point in NPD
to determine top three drivers
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Approach Fundamental Noise Drivers
Single Aisle• Combining the information
gained finding the major noise sources at each location with the results of physical drivers for each source
• Allows for analysis of where certain physical parameters will significantly impact the overall SEL levels of the vehicle NPD tables
• Will aid GT in determining which parameters are crucial for the correction functions and which are not for each point in the NPD
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Next Steps
• Complete sensitivity to identify– What sources need to be corrected– Where the sources need to be corrected– What is the correction function?
• Identify additional data required in AEDT database– Can data be estimated from existing information?– Is new data required?
• Develop correction functions and compare to ANOPP generated NPD+C
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Acknowledgements
• FAA & Volpe for valuable feedback
• Juliet Page and Eric Boeker for invaluable insight into prior work
Participants
• GT Research Staff:• Greg Busch, Holger Pfaender, Michelle Kirby
• GT Students:• Sara Huelsman