The distortion of homogeneous isotropic turbulence interacting with a porous cylinder is calculated by means of the rapid distortion theory (RDT). The porous treatment, characterised by a constant static permeability, is modelled as an impedance boundary condition accounting for the Darcy's flow within the body. The RDT algorithm is first validated through comparisons with published velocity measurements in the stagnation region of an impermeable cylinder placed downstream of a turbulence grid. Subsequently, the impact of porosity on the velocity field is investigated through the analysis of the one-dimensional spectra at different locations near the body and the velocity variance along the stagnation streamline. The porous surface affects the incoming turbulence distortion near the cylinder by reducing the blocking effect of the body and by altering the vorticity deformation caused by the mean flow. The former leads to an attenuation of the one-dimensional velocity spectrum in the low-frequency range, whereas the latter results in an amplification of the high-frequency components. This trend is found to be strongly dependent on the turbulence scale and influences the evolution of the velocity fluctuations in the stagnation region. The porous RDT is finally adapted to model the turbulence distortion in the vicinity of the leading edge of a NACA-0024 profile fitted with melamine foam. The good agreement between the calculations and the experimental results demonstrates that the present methodology can improve the understanding of the physical mechanisms involved in the aerofoil-turbulence interaction noise reduction through porosity and be instrumental in designing such passive noise-mitigation treatments.

With the rapid proliferation of unmanned aerial vehicles, understanding the aeroacoustics of drones in operating conditions is essential to mitigate perceived annoyance. Performing these measurements in a large indoor test hall is particularly attractive, as it allows the execution of complex drone maneuvers under controlled atmospheric conditions, with high-precision trajectory tracking provided by motion capture systems. Yet, not being acoustically treated, these facilities present challenging reverberant conditions for acoustic measurements. This research work focuses on investigating a maneuvering quadcopter drone inside an indoor test hall and proposes a methodology based on phased-array techniques to decontaminate the recorded noise from the reverberation effects using a tailored Green's function. The results indicate that the tonal contributions of the noise spectrum are significantly influenced by drone operation and orientation, with distinct changes in the blade pass frequencies linked to the varying speeds of the front and back rotors during different flight phases. By filtering out spurious broadband noise due to sound reflections, the proposed dereverberation methodology facilitates the tracking of these tonal components, which can be more clearly visualized in the noise spectrum. The study eventually highlights the importance of analyzing the drone trajectory when interpreting the corresponding noise radiation.

Amiet's model for turbulence-ingestion noise prediction for rotors is adapted to incorporate pointwise velocity measurements as input. This is accomplished by using an inverse strip theory approach and transforming the three-dimensional turbulence spectrum, which models inflow conditions, into a one-dimensional term. This latter modification enhances the low-fidelity prediction tool in two key ways. First, it enables its application in cases where turbulence modeling is unavailable, or detailed inflow characterization is impractical. In this way, for example, hot-wire anemometry measurements of the incoming turbulence can be used to compute the acoustic prediction. Second, since the conversion of the turbulence term entails introducing two new functions describing spanwise and axial turbulence correlations; this approach establishes a framework for Amiet's theory in which the contributions to turbulence alteration and noise scattering are separated and represented individually. This “modular” structure enables independent analysis and modeling of these contributions, facilitating the application of Amiet's model to complex flow configurations and rotor geometries. The proposed methodology is successfully validated through experimental measurements of a simplified axial-flight turbulence-interaction setup, where a two-bladed propeller interacts with grid-generated turbulence at three different advance ratios.