Representative-in-class vehicles for fleet-level aviation noise analysis

Global air traffic demand is projected to nearly double by 2035 (7.2 billion passengers) compared to the 3.8 billion passengers in 2016. At such a growth rate, the aviation sector might cause an important detriment of the welfare of those living around airports via a substantial increase in noise. For addressing such a concern, the aviation industry is required to assess a significant number of aviation scenarios, involving different technology platforms and operational procedures, in order to define the strategies that ensure the higher reduction in aircraft noise impact. A common approach to reduce the combinatorial nature of fleet-level studies and enable more flexibility for exploring multiple aviation scenarios, is to simplify the fleet into a number of representative-in-class vehicles that capture the noise performance of the various classes within the fleet. In this paper, a statistical classification process is implemented for reducing the UK commercial fleet into a number of representative-in-class vehicles based on aircraft noise characteristics. The optimal number of representative-in-class aircraft is analysed for three airports in the UK (London Gatwick, Heathrow and Stansted), with significant differences in aircraft movements and fleet composition, on the basis of the accuracy vs. computational time when calculating noise contour areas. Finally, it is discussed the use of these representative-in-class vehicles as baseline models for projecting the reduction in aviation noise impact with future technology implementation

Estimation procedure of the descriptor LAeq,T from the stabilization time of the sound pressure level value

Temporal structure of sound pressure level is a key aspect at the time of characterizing urban sound environments. In urban agglomerations, environmental noise levels fluctuate over a large range as a result of the great complexity of these settings, with considerable temporal and spatial heterogeneity. Furthermore, the domain in urban environments of noise sources, such as road traffic, commercial or leisure activities, construction works, etc., together with the occurrence of sudden sound-level maxima events (bells, sirens, vehicles at high traffic speed, honking horns...), which are quite frequent in urban agglomerations, generate the appearance of very high values of the impulsiveness of sound pressure level. This aspect causes a great influence on the time necessary for environmental noise levels to become stabilized, which is a key aspect for the accurate measurement, interpretation and guarantee of a statistically representative sample of a given urban sound environment. Therefore, the goal pursued in this work is to put forth a procedure for the calculation of a value of LAeq,T, representative of a certain urban location in a short-term time period, from the utilization of the value of the stabilization time of the sound pressure level

A Psychoacoustic Approach to Building Knowledge about Human Response to Noise of Unmanned Aerial Vehicles

We are on the cusp of a revolution in the aviation sector, driven by the significant progress in electric power and battery technologies, and autonomous systems. Several industry leaders and governmental agencies are currently investigating the use of Unmanned Aerial Vehicles (UAVs), or “drones” as commonly known, for an ever-growing number of applications—from blue light services to parcel delivery and urban mobility. Undoubtedly, the operation of UAVs will lead to noise exposure, which has the potential to become a significant public health issue. This paper first describes the main acoustic and operational characteristics of UAVs, as an unconventional noise source compared to conventional civil aircraft. Gaps in the literature and the regulations on the noise metrics and acceptable noise levels are identified and discussed. The state-of-the-art evidence on human response to aircraft and other environmental noise sources is reviewed and its application for UAVs discussed. A methodological framework is proposed for building psychoacoustic knowledge, to inform systems and operations development to limit the noise impact on communities