A Semi-Empirical Model for Aircraft Landing Gear Noise Prediction

This paper presents an empirical model for landing gear noise prediction. The model is based on scaling laws of the theory of aerodynamic noise generation and correlations of these scaling laws with currently available test data. The method decomposes the landing gear noise into three spectral components respectively for the low, the mid and the high frequencies, which corresponds to cataloguing the parts in the landing gear assembly into three groups, namely, the wheels, the main struts and the small details. For all three spectral components, empirical models are derived for their spectral shapes, far field directivities and noise amplitudes. The spectral shapes are defined by normalized spectra, as functions of the Strouhal numbers based on the respective length scales of the three groups of parts in the landing gear. Individual directivity factors are also derived for the three spectral components, with the low frequency component having the smallest variations with emission angle and the high frequency component having the largest variations. Directivity due to installation effects is also modeled. The amplitudes of the three spectral components are correlated to parameters unique to each group of landing gear parts, with the low and mid frequency noise essentially characterized by the physical dimensions of the wheels and the main struts, respectively, and the high frequency noise, whose generation is associated with a large number of small details in practical landing gears, defined by a complexity factor. Quantities that affect this complexity factor are discussed and an empirical model is given for practical applications. The prediction model is validated by wing tunnel test data for an isolated Boeing 737 landing gear and by flight test data for the Boeing 777 airplane. In both cases, the predictions agree well with data, both in parametric trends and in absolute noise levels.