NOISE PREDICTION METHODS

Noise prediction methods are necessary in aspects of aerodynamic and hydrodynamic engineering. Predictive models of noise from rotating machinery ingesting turbulence is of much interest and relatively recently studied. This thesis presents a numerical method processed in a series of three codes that was written and edited to receive input for geometrical features of rotating machinery, as well as, adjustments to turbulent operating conditions. One objective of this thesis was to create a platform of analysis for any rotor design to obtain five parameters necessary for noise prediction; 1) the hydrodynamic inflow angle to each blade section, 2) chord length as a function of radius, 3) the cylindrical radius of each blade section, 4) & 5) the leading edge as a function of span in both the rotor-plane and as a function of axial distance downstream. Another objective of this thesis was to use computational fluid dynamics (CFD), specifically by using a Reynold’s-Averaged Navier-Stokes (RANS) Shear Stress Transport (SST) 𝑘 − 𝜔 model simulation in ANSYS Fluent, to obtain the turbulent kinetic energy distribution, also necessary in the noise prediction method presented. The purpose of collecting the rotor geometry data and turbulent kinetic energy data was to input the values into the first of the series of codes and run the calculation so that the output spectra could be compared to experimental noise measurements conducted at the Stability Wind Tunnel at Virginia Tech. The comparison shows that the prediction method results in data that can be reliable if careful attention is payed to the input parameters and the length scale used for analysis. The significance of this research is the noise prediction method presented and used simplifies the model of turbulence by using a correlation function that can be determined by a one-dimensional function while also simplifying the iterations completed on rotor blade to calculate the unsteady forces.