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Crown shape optimization for enhancing tire wear performance by ANN

机译:通过ANN优化胎冠形状以增强轮胎磨损性能

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摘要

Tire wear performance is influenced majorly by the distribution of contact pressure with ground, and which is in turn dominated by the shape of tire tread called crown contour. So, the optimum crown shape design is essential for improving the tire wear performance, however it encounters a difficulty of long CPU time when the sensitivity analysis invokes the direct FEM analysis. As a remedy for resolving this numerical problem, we present a crown shape optimization by employing an artificial neural network (ANN). As well, we introduce the non-uniform weighting factors in the objective function definition, in order to effectively obtain an optimum crown contour which provides the contact pressure distribution close an ideal one. Through the illustrative numerical experiments, we assess the CPU-time efficiency and the reliability of the numerical optimization method presented.
机译:轮胎的磨损性能主要受与地面的接触压力分布的影响,而轮胎的胎面形状又称为胎冠轮廓,这主要决定了轮胎的磨损性能。因此,最佳的胎冠形状设计对于改善轮胎的磨损性能至关重要,但是当灵敏度分析调用直接FEM分析时,会遇到较长的CPU时间的困难。作为解决此数值问题的一种补救措施,我们提出了一种采用人工神经网络(ANN)的牙冠形状优化方法。同样,我们在目标函数定义中引入了非均匀加权因子,以便有效地获得最佳的冠状轮廓,从而提供接近理想的接触压力分布。通过说明性的数值实验,我们评估了所提出的数值优化方法的CPU时间效率和可靠性。

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