Noise Prediction Modeling I

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Presentation transcript:

Noise Prediction Modeling I John-Paul Clarke Nhut Tan Ho Liling Ren DLR-DLH-MIT Workshop on Noise Abatement Procedures August 17-19, 2004 Seeheim, Germany

Key Question How accurate do our noise model need to be? All aircraft versus only aircraft that drive noise? What is the right modeling approach? Single event versus extended duration noise levels? Detailed spectra-directivity versus noise-power-distance curves? Specific weather effects versus standard conditions? How could we use use these models in the design of noise abatement procedures?

How accurate? Developing models for all aircraft would require more money than we have Too many different aircraft types Prudent approach would be to: Analyze traffic and noise monitor data from all airports to determine aircraft that are main noise drivers Conduct flyover measurements to determine noise levels for these aircraft Data would of course also be used to support development of detailed component models Develop correlations with other aircraft types and use them to estimate noise levels of other aircraft

Modeling approach? Extended duration noise levels are used throughout the world for deciding on compensation for aircraft noise impact, but … Knowing the single-event spectral-based weather-affected noise level is critical for developing noise abatement procedures. Tailor operations to specific conditions (when weather conditions are included) and to specific population distribution Capture effects of variability in weather and operations on noise impact Can also be aggregated in post processing to give extended duration measures

Source Directivity-Spectra

How to use? Evaluate and compare noise impact of candidate procedure Straight-forward application of modeling Select best procedure for given conditions from list of pre-evaluated candidates procedures Initial study for NASA Ames suggests that this could be a useful tool for airport configuration management No current work being done in this area Optimize procedure parameters (e.g. targets) given variability in operating environment Very useful for developing pilot procedures

Effects of Weather Models generally ignore the effects of atmospheric gradients Airports assume ‘no weather’ for annual average noise levels The validity of this assumption was tested through a numerical study using the aircraft noise simulation model NMSIM [WYLE] Five years of meteorological data at 7 major US airports Model airport With the compliments of

Wyle Airport Noise Study Five years of weather at seven airport locations Upper air soundings – twice daily Surface weather - hourly Surface flux model Generate full profiles for each hour Model airport Composite of major air carrier airports Three runways, various directions Four nominal aircraft types Hourly operations based on annual operations at component airports Tracks straight in and out With the compliments of

No-Weather Leq (65 dB and higher) Leq contours for no gradients – the usual assumption. With the compliments of

U.S. Standard Atmosphere See how the shape differs – narrower alongside runways, where upward refraction causes shadow zones. With the compliments of

Sample Hour With the compliments of

Annual average Leq contours Areas in square miles With the compliments of

MIT Study MIT study (main campus and Lincoln Laboratory) of two airports agreed with Wyle study Significant impact due to weather Study went further to include effects of weather on aircraft performance

Logan Case Study Low Noise Departure Existing Departure North wind Scenarios/ dBA SEL 60-70 70-80 80-90 90-100 Above 100 Existing departure 405,885 235,083 43,825 5,764 192 Weather-specific dep. 293,745 94,574 18,882 5,320 143

Fast-time Simulators (1) Functionality Evaluation aircraft deceleration and maneuverability Simulation of noise abatement approach procedures (example: decelerate at idle thrust, 3º slope angle) Monte-carlo simulation studies for capacity and noise impact General features Actual aerodynamic models Aircraft : B737-300, B747-400, B757-200, B767-300 Control system functions: auto-pilot and navigation control logic Modes: level flight, level turn, climb/airspeed, 3º slope angle hold Models of pilot response, wind, disturbances Coded in Matlab

Fast-time Simulators (2) Point-mass modeling assumptions Aircraft behaves as a point mass (no rotation, inertia) No slide-slip {b = 0, v = 0}, coordinated turn Thrust is along the body axis Controls pilot has goes directly to applied forces Other body rates (q & r) are determined by curvature of trajectory i.e. cannot pitch without climbing

Fast-time Simulators (3) Point-mass simulation loop

Integrated Tool (1) Integration of simulators with Noise Model Automated to perform repeated computation A/C States Simulator input: A/C Initial conditions Pilot Response models Wind models Noise Model Fast-time Simulator

Integrated Tool (2) Tradeoff study: Noise Reduction and Target Achievement Pilot response models Approaches PF Cues PNF to extend flap PF cues PNF to extend flap in turbulence

Integrated Tool (3) Highest noise saving and highest target achievement for Non-turbulent pilot response model: Flaps schedule is designed for 1050 ft and HI equal 5000 ft Turbulent pilot response model: Flaps schedule is designed for 1200 ft and HI equal 7000 ft To design for worst case (i.e. turbulence): high value of HI provides best noise saving and target achievement probability Non-turbulent pilot response model Turbulent pilot response model