The investigation of technologies that can improve the sustainability of the air transport system requires not only the development of alternative fuel concepts and novel vehicle technologies but also the definition of appropriate assessment strategies. Regarding noise, the assessment should reflect the situation of communities living near airports, i.e., not only addressing sound levels but also accounting for the annoyance caused by aircraft noise. For this purpose, conventional A-weighted sound pressure level metrics provide initial but limited information as the level- and frequency-dependency of the human hearing is accounted for in a simplified manner. Ideally, subjective evaluations are required to adequately quantify the perceived short-term annoyance associated with aircraft noise. However, listening tests are time-consuming and not suitable to be applied during the conceptual aircraft design stage, where a large solution space needs to be explored. Aiming at bridging this gap, this work presents a methodology for the sound quality assessment of computational aircraft noise predictions, which is hereby conducted in terms of objective psychoacoustic metrics. The proposed methodology is applied to a novel medium-range vehicle with fan noise shielding architecture during take-off and landing procedures. The relevance of individual sound sources, i.e., airframe and engine noise contributions, and their dependencies on the aircraft architecture and flight procedures are assessed in terms of loudness, sharpness, and tonality. Moreover, the methodology is steered towards community noise assessment, where the impacts on short-term annoyance brought by the novel aircraft design are analysed. The assessment is based on the modified psychoacoustic annoyance, a metric that provides a quantitative description of human annoyance as a combination of different hearing sensations. The present work is understood as an essential step towards low-annoyance aircraft design.

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In this work, the impact of the COVID-19 outbreak on the environmental noise generated by the air traffic at the Hannover Airport, Germany, is assessed. For this purpose, a comparative study of the air traffic noise in the years 2019 and 2020 is conducted by means of publicly available measurement data and computational simulations. Based on environmental noise directives defined by the responsible German authorities, the comparative study is conducted in terms of A-weighted equivalent sound pressure level metrics computed for the six months of the forecast years with the largest number of flights. In comparison with the year of 2019, the measurement data indicates that the [Formula: see text], and [Formula: see text] were reduced in average by 2.4, 4.2, and 3.7 dBA, respectively, in the year 2020. Furthermore, the results based on the computational simulations show that the isocontour areas of the [Formula: see text] and [Formula: see text] noise protection zones defined by the German federal government were reduced by [Formula: see text] and [Formula: see text], respectively, in the year of 2020.

In the context of aircraft noise simulations, an accurate representation of the aircraft noise sources is crucial so that reliable predictions can be obtained. In this contribution, we present a comparative study between the predictions provided by the emission models based on the DLR in-house code PANAM and the sonAIR simulation software. Both are based on semi-empirical descriptions of the engine and airframe noise contributions, meaning that the emission levels are modeled separately for each noise source according to the operational conditions of the aircraft. This allows the comparison of the emission models not only in terms of the aircraft's overall noise levels, but also regarding its different noise sources. The comparative study considers models representing the noise emissions of an A319 aircraft, which are provided by both simulation tools but further simulated within the sonAIR software environment in order to yield noise immission levels on a large calculation area. In general, a good agreement is observed for the departure procedure due to the similar performance of the engine noise models. In contrast, larger differences are observed during the approach procedure and at larger distances from the runway, which might be explained by differences in the airframe noise models.