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Drone Noise

PI Reda Mankbadi

A hybrid Large-Eddy Simulation approach is developed to predict the tonal and broadband noise of Drones, UAV, and eVTOL 


Hi-Fidelity Simulations of a small UAS flow & Noise

The ERAU team developed a Hybrid LES-URANS of the flow and acoustic field of a small UAV propeller, which accurately predicts tonal noise as well as the BBN of the propeller and its wake. This provides a framework for studying various rotor complex interactions.

To examine BBN, we conducted a spectral POD analysis, which suggested that at low frequencies, the blade self-noise and the wake noise are comparable sources of the broadband noise. But at higher frequencies, the blade self-noise dominates

By examining the contribution to the FWH integration we concluded that the pressure contribution is the dominant one. The momentum contribution becomes of the same order as that of pressure only in the rotor plane. The mass flux contribution is much smaller in this situation.

Fig: Q-criterion Iso contours with Dilatation field in background.

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Fig: Snapshot of shear momentum flux of FWH equations.


Research Dates

09/01/2018 to 09/01/2023

Researchers

  • Reda R. Mankbadi

    Reda R. Mankbadi

    Department
    Aerospace Engineering Department
    Degrees
    Ph.D., Brown University

Categories: Faculty-Staff