Effects of inflow conditions on turbulence-ingestion noise prediction

Abstract

Turbulence-ingestion noise, caused by the interaction between incoming turbulence and rotors, is currently a key area of research in the rapidly expanding field of Urban Air Mobility. This is due to the highly turbulent flows characterizing urban environments, where acoustic optimization is especially critical, and to the complexity and diversity of the physical mechanisms involved in noise generation. This makes the analytical modeling for low-fidelity prediction – favored over computationally expensive numerical simulations in the optimization phase — particularly challenging. This study proposes two key modifications to Amiet’s model aimed at enhancing the assessment of inflow-conditions effects on noise generation and prediction. The first allows strip theory to be incorporated to account for radially-varying inflow while preserving the modeling of blade-blade correlation. The second enables the replacement of the original three-dimensional turbulence input, particularly challenging to measure both experimentally and numerically, with a one-dimensional one. This allows probe measurements to be directly used as input to assess the effects of inflow conditions. Additionally, it paves the way for the extension of turbulence-distortion models from rectilinear motion to rotating systems, potentially enhancing prediction accuracy. The approach is validated against experimental acoustic data obtained for a two-bladed propeller under various operating conditions.