Improving Capabilities in Modeling Aircraft Noise Sources

Improving Capabilities in Modeling Aircraft Noise Sources

Vieira, A.E. (TU Delft Aircraft Noise and Climate Effects)

Simons, D.G. (promotor)
Snellen, M. (promotor)

Delft University of Technology

2021-06-16

Today's globalized world depends on civil air transportation, which has been continuously growing over the last decades. Nevertheless, the sustainability of this expansion is a challenge due to environmental problems. Along with greenhouse gas emissions, noise represents a severe hazard for human health, and consequently, noise regulations limit the airport capacity and impose night curfews.

Noise is therefore an important design driver for future aircraft, and accurate noise predictions are essential at an early design stage. The total noise emission of an aircraft poses a complex problem, as the distinct
components emit noise with different characteristics. High fidelity methods are computationally demanding and time-consuming at an early design phase and less complex solutions, such as semi-empirical methods, are often considered to be more suitable. This thesis focuses on aspects that can improve noise predictions for a new generation of silent aircraft.

The concept of noise shielding is present in many future aircraft designs, in which engine noise is partially shielded by the airframe, resulting in a noise reduction on the ground. The noise shielding predictions presented in this work use a theory based on the Kirchhoff integral and the Modified Theory of Physical Optics. This method was extended to consider other noise source radiations patterns than the monopole and to calculate the creeping rays originated by smooth edges.

Experiments in the wind tunnel were used to validate these methods and showed that the values of noise shielding are strongly dependent on the source directivity and the shape of the obstacle.

Flyover measurements of rear engined aircraft were compared with predictions of noise shielding. The good agreement obtained considering a sharp-edged wing in the predictions was further improved by considering the curvature of the leading edge.

A low-noise variation of the Boeing 747-400 is explored using noise shielding predictions, and the optimal engine positions were found to be different when considering the wing leading edge as sharp and with a curvature. This analysis shows how the design of an aircraft is affected by the approximations adopted in the noise shielding predictions, therefore also affecting its performance.

For conventional aircraft, the noise emission is commonly estimated using semi-empirical methods. These models are based on experimental data and require detailed input of the aircraft geometry and engine settings. This work uses experimental data to test the limitations of such empirical methods during take-off and landing.

The efforts to reduce aircraft noise are only meaningful when resulting in a decrease of annoyance. Traditional metrics such as the Effected Perceived Noise Level are used to assess the annoyance caused by aircraft flyovers but do not provide information about the sound characteristics, such as tonal content and fast and slow amplitude oscillations. Sound quality metrics provide a more complete characterization of a sound and can be combined in psychoacoustics annoyance metrics. Flyover measurements of different aircraft types during take-off and landing were used to investigate the correlation between the sound quality metrics and the aircraft geometry and propulsion system. Strong correlations were found between the sound quality metrics and a number of aircraft characteristics, indicating that psychoacoustic metrics can be used to drive the design process, similarly to existing methods that apply traditional metrics for the same purpose. The variability of the sound quality metrics and psychoacoustic annoyance within the same aircraft type was also investigated. This variability was attributed to the aircraft operating conditions.

Aircraft noise
Noise shielding
Noise semi-empirical methods
Sound quality metrics

https://doi.org/10.4233/uuid:806e1965-8320-4a40-b0fc-0b060ac62799

Institutional Repository

doctoral thesis

© 2021 A.E. Vieira