MEMS Seminar: Juan Alonso, PhD, Stanford University
Thursday, October 30, 2025 2:30 PM to 3:30 PM
About this Event
6548 Forest Park Pkwy, St. Louis, MO 63112, USA
https://mems.washu.edu/index.htmlValidation of Aircraft Noise Modeling by Large-Scale Data Collection and AEDT Prediction
Accurately assessing noise from aircraft operations is critical to allow for the planning of fuel-optimal routes and to support noise abatement and mitigation procedures. In the U.S., the Federal Aviation Administration's Aviation Environmental Design Tool (AEDT) is used to predict the impacts of aircraft noise and emissions. Previous studies suggest that AEDT’s noise predictions may lack the desired accuracy, especially in areas away from the airport. This presentation describes the results of a large-scale study we have conducted using over 200,000 flight trajectories paired with measured sound levels for arrivals into runways 28L/28R at San Francisco International Airport, over a period of 12 months. For each flight, two AEDT studies were run, one using the approved mode for regulatory purposes and the other using an advanced non-regulatory mode with exact aircraft trajectories. AEDT's per aircraft noise predictions were compared with curated measured sound levels at two locations. On average, AEDT underestimates LAmax by −3.09 dB and SEL by −2.04 dB. Discrepancies appear to result from limitations in the physical modeling of flight trajectories and noise generation, combined with input data uncertainties (aircraft weight, airspeed, thrust, and lift configuration) and atmospheric conditions. Given the abundance of data, we have experimented with the use of data-driven methods to construct more accurate noise models of certain classes of aircraft that we observe very frequently. Some results for this enhanced modeling strategy are also discussed.

