An Empirical Model for Landing Gear Noise Prediction

*† ‡ This paper presents an experimental investigation on aircraft landing gear noise. The study consists of systematic testing and data analysis, using the full-scale Boeing 737 landing gear. The database covers a range of mean flow Mach numbers typical of landing conditions for commercial aircraft and various landing gear configurations, ranging from a fully dressed, complete gear to cleaner configurations involving only parts of the complete gear. This enables us to reveal contributions from various groups of the gear assembly and to derive functional dependencies of the radiated noise on the flow Mach number at various far field directivity angles and on various gear geometry parameters. It is shown that the noise spectrum can be decomposed into three frequency components, namely, the low, mid and high frequency components, respectively representing contributions from the wheels, the main struts and the small details such as hoses, wires, cutouts and steps. It is found that these different frequency components have different dependencies on flow parameters and gear geometry. For example, while the low and mid frequency noise scale on the sixth power law with flow Mach number, the high frequency noise follows the eighth power Mach number scaling and has a spectral shape proportional to the inverse square of frequency, indicating the turbulent wake, instead of the unsteady forces on the gear, as the sources of the noise. This is confirmed by phased microphone array measurements, identifying a source distribution in the wake region at high frequencies. Based on the spectral decomposition in the three frequency domains, normalized spectra are derived for all three components in terms of the Strouhal numbers. A model for the Overall Sound Pressure Level (OASPL) is also developed as a function of flow and geometry parameters. For the high frequency noise generated by small features in the landing gear, a detailed description of their numbers, sizes, shapes, locations and orientations is apparently not practical so that a complexity factor is introduced to account for the aggregate effects of all the small details. This complexity factor can be empirically related to aircraft design parameters such as the maximum takeoff or landing weight. Some examples are given to show the accuracy of the empirical model and comparisons with data show very satisfactory results.