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原文传递 Development of a Tire/Pavement Contact-Stress Model Based on Artificial Neural Networks

题名：	Development of a Tire/Pavement Contact-Stress Model Based on Artificial Neural Networks
作者：	Moustafa El-Gindy and Heidi Lewis
关键词：	Tires, tire contact patch, contact patch stress, artificial neural networks, tire/pavement stress, tire modeling.
摘要：	This report presents the first world-wide tire/pavement contact-stress model worldwide 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 developed ANN model has the capabilities to generate such complex stress distribution patterns under a tire at any given load and inflation pressure for a specific tire type used for the ANN training. The information given in this report is considered to be an important contribution to the ongoing efforts to improve tire/pavement contact-stress modeling and analysis. The neural network representation of a tire contact-stress distribution is named as "Neuro-Patch Model.® The neural network models have been trainee 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 11 R22.5 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.
报告类型：	科技报告