An Image Based Computational Model to Predict Air Pumping Noise in Rolling Tires

In this work we propose an image based computational model to predict noise produced in rolling tires attributable to the air pumping phenomenon. The model uses different pitch geometries as input parameters, and subsequently predicts the noise generated by treads in temporal and frequency domains. The method lends itself available to explore roles of different pitch parameters; specifically pitch sequence, pitch length, pitch width, pitch angle, vehicle speed, contact patch length, and tread compression; on the overall amplitude and spectrum of air pumping noise generated in a rolling tire. The model uses data embedded in pitch images to calculate the volume velocity as a function of time. This temporal function is subsequently processed to compute sound pressure level in dB and dB(A) units. Predictions from such a model are compared with available data. Sensitivity studies have also been conducted to explore the role of various tread parameters on tread noise generated by a rolling tire.