Assessment of an Open-Source Aircraft Noise Prediction Model Using Approach Phase Measurements
Journal article, 2024

An open-source simulation model for aircraft noise prediction is presented and validated using backpropagated noise measurements for a state-of-the-art engine and aircraft. The validation is focused on approach procedures and was performed using ground-based noise measurements that were taken at 17 recording stations for a total of 18 consecutive flights carried out during the morning of 8 April 2021. The flights were performed using two A321neo aircraft with LEAP-1A engines. It is demonstrated that the presented noise model provides a satisfactory estimation of the source noise for varying approach configurations and flight conditions. Configurations using a greater number of high-lift devices are particularly well predicted in the mid- and high-frequency regions, whereas the lower configuration settings show greater spectral deviations, which are partly attributed to measurement uncertainties caused by the increased aircraft–microphone distance. The model can predict the overall mean total sound intensity level within a 2 dB accuracy for all configurations, while the average predicted level at each microphone differs by less than 3 dB from the measurement average, for all cases except one. Variation in aircraft speed showed to have a strong impact on the predicted total noise, which matches the well-recognized sixth-power Mach number far-field sound intensity scaling law for airframe noise models, while the measurements indicated a less significant dependency. This is mainly due to installation effects and noise reduction measures that are not included in the models. Nevertheless, the variations in the spectra of the predicted and measured noise showed similar patterns.

Final Approach

Acoustic Measurement

Aircraft Noise

Acoustic Properties

Landing

Empirical Methods

Overall Sound Pressure Level

Aircraft Configurations

Author

Evangelia Maria Thoma

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Tomas Grönstedt

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Evelyn Otero Sola

Royal Institute of Technology (KTH)

Xin Zhao

Chalmers, Mechanics and Maritime Sciences (M2), Fluid Dynamics

Journal of Aircraft

0021-8669 (ISSN) 15333868 (eISSN)

Vol. 61 3 745-760

(CorrelatIon- and physics based preDiction of noisE scenaRios) CIDER

Swedish Transport Administration (TRV2019/95826), 2019-09-02 -- 2023-10-01.

Subject Categories

Aerospace Engineering

Fluid Mechanics and Acoustics

DOI

10.2514/1.C037332

Related datasets

Open-source noise prediction model [dataset]

URI: https://github.com/emthm/CHOICE

More information

Latest update

7/5/2024 1