Investigating the Potential of Using Quota Count as a Design Metric

Abstract

Identifying easy to use and communicate extensive design metrics for aircraft noise could be of substantial benefit to the aircraft design community. The current means of communication often revolves around margin to the certification stringencies. These stringencies are hard to communicate and not directly related to external impact. A good design metric correlates well with the individual aircraft's effect on these broader measures.This paper proposes the use of Quota Count, which was devised as a means of limiting night-time exposure to single equivalent events at London area airports. It is directly related to the actual energy emitted by the an aircraft and the resulting time average values observed on the ground. It is straightforward to communicate and comprehend. It is based upon the certification noise values, and therefore, straightforward for a design engineer to model. This paper answers the question does Quota Count relate well with cumulative measures especially day-night noise level estimates of the area exposed to a given cumulative level? Given that Quota Count, and a simple cumulative Quota Count model correlate highly with these measures, it is reasonable to suggest that Quota Count be used as a primary noise metric for new designs.

Noise-Sensitivity to Vehicle-Level Design Variables

“…While AEDT does not require these EPNL certification points to compute DNL contours, previous studies have attempted to predict DNL contours using these EPNL certification metrics. 15 EPNL certification metrics are also generated by ANOPP within the EDS environment, so it makes sense to track these metrics in parallel and check if they are driven by similar design variables as the NPDcurves and the SEL-contours.…”

Aircraft classification for efficient modelling of environmental noise impact of aviation

“…The computational time of airport noise models is most sensitive to the number of aircraft in the flight schedule (Bernardo et al, 2015). Therefore, another approach for reducing the combinatorial nature of the problem is the classification of the fleet into representative aircraft categories, and then selecting an indicative aircraft representative of each category (Hollingsworth and Sulitzer, 2011;Tetzloff and Crossley, 2014). With this approach, noise outputs can be more rapidly computed with either high-fidelity or simplified airport noise models using only a reduced number of aircraft types, i.e.…”