Assessing the performance of the sonAIR aircraft noise model in predicting noise levels at Schiphol Airport

Master Thesis (2023)
Author(s)

R.N.J. Boelhouwer (TU Delft - Aerospace Engineering)

Contributor(s)

M. Snellen – Mentor (TU Delft - Control & Operations)

D.G. Simons – Graduation committee member (TU Delft - Aircraft Noise and Climate Effects)

R.C. Van der Grift – Coach (TU Delft - Aircraft Noise and Climate Effects)

Faculty
Aerospace Engineering
Copyright
© 2023 Robbert Boelhouwer
More Info
expand_more
Publication Year
2023
Language
English
Copyright
© 2023 Robbert Boelhouwer
Graduation Date
09-05-2023
Awarding Institution
Delft University of Technology
Programme
['Aerospace Engineering']
Faculty
Aerospace Engineering
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Aircraft noise is a significant problem for communities surrounding airports. Accurate prediction models are needed to estimate noise levels from aircraft operations. In this research, the accuracy of the sonAIR aircraft noise model is evaluated in predicting noise levels around Schiphol airport by comparison to measurement data from NOMOS and the current best-practice modelling approach Doc29. Results show a significant but consistent underestimation of noise levels by sonAIR, mainly due to a generalisation of emission models. The standard deviation of differences between model results and measurements is lower for sonAIR than for Doc29 by up to 1 dB. Differences between measurement and model results were found in the relation between N1 and noise levels, maximum noise levels and frequency spectra. These results demonstrate that sonAIR provides more reliable predictions of noise levels on the single flight event level than Doc29. Additionally, this study shows agreement with results from a previous validation study in Zürich, thereby confirming the applicability of sonAIR to another airport. This research contributes to better aircraft noise predictions, which will have implications ultimately leading to a better quality of life for communities affected by aircraft noise.

Files

Thesis_RNJBoelhouwer.pdf
(pdf | 16.2 Mb)
License info not available