Sound Propagation Modelling for Manned and Unmanned Aircraft Noise Assessment and Mitigation: A Review

Abstract

This paper addresses one of the recognized barriers to the unrestricted adoption of Unmanned Aircraft (UA) in mainstream urban use—noise—and reviews existing approaches for estimating and mitigating this problem. The aircraft noise problem is discussed upfront in general terms by introducing the sound emission, propagation, and psychoacoustic effects. The propagation of sound in the atmosphere, which is the focus of this paper, is then analysed in detail to isolate the environmental and operational factors that predominantly influence the perceived noise on the ground, especially looking at large-scale low-altitude UA operations, such as in the envisioned Urban Air Mobility (UAM) concepts. The physics of sound propagation are presented, considering all attenuation effects and the anomalies due to Doppler and atmospheric effects, such as wind, thermal inversion, and turbulence. The analysis allows to highlight the limitations of current mainstream aircraft noise modelling and certification approaches and, in particular, their inadequacy in addressing the noise of UA and, more generally, UAM vehicles. This finding is important considering that, although reducing noise at the source has remained a priority for manufacturers to enable the scaling up of UAM and drone delivery operations in the near future, the impact of poorly considered propagation and psychoacoustic effects on the actual perceived noise on the ground is equally important for the same objective. For instance, optimizing the flight paths as a function of local weather conditions can significantly contribute to minimizing the impact of noise on communities, thus paving the way for the introduction of full-scale UAM operations. A more reliable and accurate modelling of noise ground signatures for both manned and unmanned low-flying aircraft will aid in identifying the real-time data stream requirements from distributed sensors on the ground. New developments in surrogate sound propagation models, more pervasive real-time sensor data, and suitable computing resources are expected to both yield more reliable and effective estimates of noise reaching the ground listeners and support a dynamic planning of flight paths.

Requirements for Drone Operations to Minimise Community Noise Impact

“…Neutral atmospheric conditions are considered in this paper; however, wind speed and direction can significantly influence both the sound emission [ 27 ] and propagation to the receiver. Appropriately accounting for these factors is crucial for setting operational requirements representative for the area under study.…”

“…Therefore, the sound pressure level at any distance , which is obtained by Equation (4), is usually to avoid the effects of the near field [ 26 ]. The effects on the atmospheric modifying factor on sound level attenuation due to the atmospheric sound absorption are included in the term , where is the attenuation coefficient for air absorption in Equation (5) [ 27 , 28 ]: …”

“…Furthermore, if the estimation of the is based on the maximum sound pressure level, i.e., the sound exposure level can be obtained with an effective time by Equation (6) [ 27 , 29 ]: …”

Study of barriers for the use of drones in the last mile logistics

“…Drones cause noise pollution as well, CO2 emissions and visual pollution [24][25][26][27]. Drones are powered by engines, which emit gases into the atmosphere, including CO2 and other harmful gases.…”

Computational investigation of various wedges electromagnetic wave absorbers on anechoic chambers

“…Sound waves can propagate directly from the source to the receiver in free field conditions [7]. When a sound wave hits the end of a medium or comes over an impediment in its route, it performs a behavior known as boundary behavior.…”