This paper investigates the prediction accuracy and time efficiency of two distinct low-fidelity methods for predicting the tonal and broadband noise of a drone rotor in axial and non-axial inflow conditions. These are both derived from an aerodynamic rotor model based on the blade element momentum theory, respectively coupled with a time- and a frequency-domain solution of the Ffowcs Williams-Hawkings integral equation applied to a radial distribution of acoustically compact and non-compact sources. Experimental data and scale resolving
lattice-Boltzmann/very-large eddy simulation results for a two-bladed small unmanned aerial system in transitional boundary layer conditions are used to validate the low-fidelity approaches. Comparison between low-fidelity, high-fidelity and experimental results reveal that the underlying sound generation mechanisms are accurately modeled by the low fidelity methods, which therefore constitute a valid tool for the preliminary design of quiet drone rotors and for the estimation of the community noise impact of drone operations.

This paper investigates the prediction accuracy and time efficiency of two distinct low-order methods, Opty∂B and LOPNOR , for predicting tonal and broadband noise of a drone rotor in axial and non-axial flow conditions. These are both derived from an aero- dynamic rotor model based on the blade element momentum theory, respectively coupled with a time- (Opty∂B) and frequency-domain (LOPNOR) solution of the Ffowcs Williams- Hawkings (FW-H) integral equation applied to a radial distribution of acoustically compact and non-compact sources. Experimental data and scale-resolving lattice-Boltzmann/very- large eddy simulation (LB/VLES) results for a two-bladed small unmanned aerial system (sUAS) in transitional boundary layer conditions are used to validate the low-order ap- proaches. Comparison between low-order, high-fidelity and experimental results reveal that the underlying sound generation mechanisms are accurately modelled by the low-fidelity methods, which therefore constitute a valid tool for preliminary design of quiet drone rotors or to estimate the noise impact of drone operations.