Estimating variation in community noise due to variation in aircraft operations

Abstract

Notwithstanding considerable effort by many researchers world-wide, the estimation of community noise due to changes in aircraft fleets and operations remains subject to considerable uncertainty. This paper describes a new taxonomical architecture for aircraft noise prediction models that can be adapted to differing levels of input data and required outputs. Sound levels on the ground are estimated at base level using existing tools (such as INM or ANCON). The aim then is to determine variations on this base level depending upon differences in known input data whilst by-passing the full complexity of engineering models for which the necessary inputs can often only be assumed or are not even available for particular cases. The architecture is well-adapted for estimating incremental change associated with single input variables, such as approach glide slope angle, or flight track concentration associated with performance based radio navigation. The research is being carried out as part of a wider effort to better understand environmental and economic interdependencies, for which taxonomical models can be highly beneficial. To illustrate the approach, the model is compared against empirical data collected from trials of steeper approach glide slope angles

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