Predicting Spatial Distributions of Lighthill's Aeroacoustic Source Terms Using Steady-State RANS Simulations in Turbocharger Compressors

Lighthill’s aeroacoustic analogy connects acoustic source terms with vortical and turbulent structures. For resolving vortical and turbulent structures in computational fluid dynamics (CFD) simulations, mesh refinements in certain regions of the computational domain are crucial. Regarding complex geometric structures, the location of turbulence and, therefore, aeroacoustic source terms cannot be predicted in advance. Iterative approaches, performing multiple transient simulations for establishing sufficient mesh refinements, are computationally demanding. Consequently, we investigate the source location prediction capabilities of coarse Reynolds averaged Navier-Stokes (RANS) simulations in combination with moving reference frames (MRF) to predict the spatial distribution of aeroacoustic source terms for performing mesh refinements. For validating the computed source terms, a detached Eddy simulation (DES) with advanced mesh refinements and a rigid body rotation (RBR) was used. By performing two different grid studies, it could be shown that RANS simulations are capable of predicting quantitative information of the actual aeroacoustic source terms location for any mesh. Furthermore, RANS simulations were capable of resolving global quantities, such as the isentropic efficiency, the pressure ratio, and the mass flow adequately. Connecting those to findings, it is shown that computing source terms are more sensitive regarding mesh coarsening than computing global quantities. Consequently, global measurements cannot be used as an indicator of whether the computed locations of the source terms are still sufficient. However, computing a coarse RANS simulation for obtaining source term locations is about 996 times faster than computing a DES simulation. Furthermore, the main advantage in this study is that for most operating points of a DES simulation, a RANS is necessary to obtain initial conditions.