S.F. Bokhari, O. von Estorff

Early design phase of an aircraft requires reducing a flow noise in an air-distribution system. This necessitates predicting an aeroacoustic behaviour of its components, which can either be done by employing extensive numerical simulations or by using experimental data. This paper deals with the latter and a systematic and an efficient method of utilizing the experimental data for an estimation of empirical models is presented. A single-hole orifice has been taken as a representative example, for a component of an air-distribution system, to demonstrate that same approach can be used to model other components. The presented approach uses Neuro- Fuzzy based Local Models, which have been estimated at different geometries and flow conditions, and a network of these Local Neuro-Fuzzy Models, known as a Local Model Network, has been used to cover the complete set of conditions. Dimensional analysis of the problem, presented here, reveals that the aeroacoustic spectrum depends on a dimensionless number that is defined by the sound power, its frequency, the geometry of a component and the density of the fluid. Two empirical models have been developed by using this approach. The inputs to the models are the geometric parameters of the orifice and the flow conditions. Both models have different accuracies and complexities, where the first model can predict the newly found dimensionless number up to Helmholtz number of 5.83 while the second model consists of only one local model and the prediction horizon reduced to 3.64.

Deutscher Luft- und Raumfahrtkongress 2012, Berlin

Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V., Bonn, 2015

Conference Paper

englisch

21,0 x 29,7 cm, 18 Seiten

urn:nbn:de:101:1-201507223860

empirical modelling, experimental aeroacoustics

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22.07.2015