Estimation of Rotor Blade Loading Distribution from Slipstream Velocity Measurements

Abstract

Accurately determining experimental blade loading distributions is crucial for analyzing rotor performance but challenging due to the limitations of conventional measurement techniques. This paper presents a so-called wake-informed lifting line model that estimates blade loading distributions from phase-locked velocity measurements in the slipstream, eliminating the need for blade instrumentation. The model is evaluated against computational fluid dynamics (CFD) simulations under both attached and separated flow conditions. For the attached flow condition, the model achieves excellent agreement with CFD, with errors in the peak value of thrust distribution below 1%. In the separated flow condition, the model captures radial gradients and the shape of the thrust distribution but exhibits discrepancies in absolute values, with a 10% error in the peak value. These differences arise from the inherent limitations of the potential flow model, the increased significance of drag, and the heightened influence of the spinner’s presence in separated flows. Incorporating profile drag through external polar data improves the model prediction, reducing the error to 4%. The model cannot reliably predict power distributions without external polar data for both attached and separated flows due to the crucial role of drag in the torque direction. The application of the model to experimental flowfield data shows a performance similar to that of the validation case. Therefore, the wake-informed lifting line model offers a promising approach for obtaining experimental blade loading distributions, overcoming the limitations of traditional methods.