The aeroacoustic performance of porous materials for sound-control applications depends on the flow communication through the medium. Hence, flow-permeable noise-reduction technologies should be tailored to the flow they operate within. A large-scale simulation setup has been developed in this work to aid the design of porous materials for airframe-noise mitigation by modeling their aerodynamic and acoustic behavior. However, this aerodynamic modeling setup requires validation on a more fundamental flow case. To this purpose, large-eddy simulations of the turbulent boundary-layer flow over two porous materials and a reference solid wall are compared against wind-tunnel measurements. This analysis includes velocity-derived boundary-layer profiles and unsteady wall-pressure measurements on the upper and lower surfaces of the flow-permeable medium. The generated experimental data are additionally made publicly available as a benchmark for boundary-layer flows over a porous wall-insert. The results of the simulation show a satisfactory agreement with the experimental data in most cases, especially for the solid wall. The mean-velocity and turbulence-intensity profiles and the wall-pressure spectra of the boundary layer over the porous materials show a dependence on the streamwise position along the surface, leading to a decrease in wall-pressure energy below a Strouhal number based on the boundary-layer thickness and the outer-flow velocity of 3 and an increase above it. Future research will be aimed at developing a new model for porous media flow centered on the optimization of the flow communication paths within them. This will potentially allow the development of porous materials with favorable acoustic properties while minimizing their aerodynamic penalty.@en

The empirical calibration of remote microphone probes (RMP), used to acquire wall-pressure fluctuations, can introduce spurious resonance into the sensor transfer function due to the difference in the pressure field inside the calibrator geometry over multiple calibration steps. Such spurious resonance subsequently propagates into the unsteady-pressure data at which the calibration is applied, hindering the accuracy of the measurements. Current post-processing methods for tackling these issues are often manual and strongly dependent on the operator's expertise. In this study, we propose an original semi-empirical calibration method to remove spurious resonance in a less operator-reliant manner. The approach is based on fitting an existing analytical fluid-dynamical model for the propagation of pressure waves in the probe to the empirical calibration data using Bayesian inference. The proposed method is successfully applied to three datasets, from a simple probe recessed behind a pinhole to a more complex branching RMP. For all the configurations, spurious resonance is eliminated from the transfer function with a strongly reduced impact of the operator intervention while retaining the resonant features that are characteristic of the RMP. The affected frequency bands are then replaced using the underlying physical model. In this way, the detrimental impact of spurious resonance is removed from the measured wall-pressure spectra. Furthermore, the RMP parameters retrieved by the fit can also be used as inputs to corrective models, specifically to account for averaging effects due to the probe sensing area or for the impact of grazing flow or temperature variations on the transfer function.

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