Quiet aircraft passenger cabins contribute significantly to the well-being and health of billions of air travellers. During design, a reliable prediction of the sound pressure level is seen as crucial decision-making basis. The wave-resolving numerical simulation of sound pressure levels in the cabin is investigated within this thesis, which results in a comprehensive modelling of a typical aircraft fuselage, the efficient numerical solution and the assessment of the sound induced by a novel engine concept and the turbulent boundary layer. A major challenge is the complexity of aircraft models including structural, acoustic and poro-elastic domains. For each relevant fuselage part, experiments are conducted and different vibroacoustic models are compared in order to choose a suitable modelling approach, repectively. The airframe, the insulation, the interior panels and the cabin are studied separately and merged into a full aircraft fuselage model. One important finding is on the glass wool insulation layer between the airframe and the interior panel, for which the need for the Biot model is shown. The modelling of structure-borne sound transmission within the glass fibres is necessary to take structural resonances within the double wall gap in the low frequency range into account. Another finding concerns the cabin domain containing seats and passengers – a global homogenised damping approach yields suitable results compared to a more detailed consideration of local surface impedances. As the resulting finite element model incorporates millions of degrees of freedom, efficient solving approaches are studied with regard to potentially introduced errors. The combination of frequency-adaptive meshes and the admissible weak mechanical coupling assumption for the cabin above 410 Hz decreases the computational time required by 87% for a 4.3m fuselage section, while the reference is a constant mesh with a strong mechanical coupling between all domains. In addition, the application of the iterative solver GMRES in ...
Wave-resolving aircraft cabin noise prediction
01.01.2022
Hochschulschrift
Elektronische Ressource
Englisch
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