Development of a Tire/Pavement Contact-Stress Model Based on Artificial NeuralNetworks

摘要

This report presents the first world-wide tire/pavement contact-stress modelworldwide based on the artificial neural networks (ANN) developed by the authors at Pennsylvania Transportation Institute at the Pennsylvania State University. These models represent the first mathematical representation of real, measured, contact stress at wide ranges of vertical loads and inflation pressures for two types of tires. The neural network models have been trained using precise measured three-dimensional contact-stresses distribution patterns obtained from low-speed rolling tire tests conducted by the University of California at Berkeley, and data have been supplied by FHWA. In this study, two types of tires, namely Goodyear 11R22.5 radial-ply and Goodyear 10.00X20 bias-ply truck tires, were modeled at different inflation pressures ranging from 520 to 920 kPa and vertical loads ranging from 26 to 56 kN.