Cabin noise prediction using wave‐resolving aircraft models

Abstract

AbstractWithin the Coordinated Research Center (CRC) 880, future civil aircraft with short take‐off and landing capabilities are investigated. A main motivation are efficient point‐to‐point connections within Europe. Environmental friendliness is a key factor in the development of such aircraft systems in order to ensure the acceptance of new technologies. Therefore, the sound immission at the ground and in the passenger cabin is a major focus in the project. In this paper, wave‐resolving models of complex aircraft fuselage structures and solution strategies of these large systems in frequency domain are presented.On the basis of preliminary aircraft design data available in the project, a mechanical model of all fluid and structural parts is developed. The model comprises the back partition starting from the wing‐box and assumes a linear behavior in deflection, strain and material. The thickness distribution on the outer surface, the stiffeners, the floor, the bulk heads and the inner panels are considered concerning the structural domain. The insulation is modeled by an equivalent fluid approach. The cabin fluid, the structural domain, and the insulation are fully coupled. All domains are discretized automatically applying coincident nodes at the coupling interfaces. Frequency‐dependent pressure fluctuations distributed on the outer surface as a result of Computational Aeroacoustic (CAA) simulations of jet noise are applied to the model. A realistic consideration of such characteristic noise footprints is only possible due to the wave‐resolving approach. The direct result of the aircraft model is the cabin's pressure field in frequency domain.The finite element discretization leads to a system of equations with 1‐3 mio degrees of freedom to be solved in frequency domain. As one solver run is easily realized, many solutions in the frame of uncertainty analyses or sensitivity studies require a highly efficient solution process. Different strategies applying direct solvers, iterative solvers or its combination are discussed within this contribution as well.