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Wheel-Rail Dynamic Model and Stochastic Analysis of the Friction in the Contact Patch

机译:车轮轨动态模型与摩擦摩擦随机分析

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摘要

The coefficient of friction (CoF) is one of the most important parameters for characterizing the contact between the wheel and the rail. The assumption of a constant CoF is still used in most theoretical studies, although experimental work indicates that the CoF depends on material and dynamic parameters. In the real world, accurate estimation of the CoF is not simple due to various uncertainties. In this paper we present a new 3-D nonlinear dry CoF model at the wheel-rail contact. In addition, a stochastic analysis using the polynomial chaos theory is performed with the CoF model. The maximum amplitude of rail roughness and the lateral displacement of the wheel are considered as uncertain parameters in this study. One of the novelties in this study is that our CoF model captures the maximum CoF value (an initial peak) when the wheel starts to move. The stochastic analysis results show that the CoF probability density function (PDF) of a combination of two uncertain parameters has wider PDF ranges than the PDF obtained for only one uncertain parameter. The current work demonstrates that the CoF is strongly affected by the stochastic variation of dynamic parameters. In reality, the CoF is critical to rail tractive performance and efficiency. Thus, the PDF distribution of the CoF must be accounted for in the design of the wheel-rail system.
机译:摩擦系数(COF)是用于表征车轮和轨道之间的接触的最重要参数之一。恒定COF的假设仍然在大多数理论研究中使用,尽管实验工作表明COF取决于材料和动态参数。在现实世界中,由于各种不确定性,COF的准确估计并不简单。在本文中,我们在轮轨接触处提出了一种新的3-D非线性干COF模型。另外,使用COF模型进行使用多项式混沌理论的随机分析。轨道粗糙度和车轮的横向位移的最大幅度被认为是该研究的不确定参数。本研究中的一个新奇是我们的COF模型在车轮开始移动时捕获最大COF值(初始峰值)。随机分析结果表明,两个不确定参数的组合的COF概率密度函数(PDF)具有比仅获得一个不确定参数所获得的PDF更宽的PDF范围。目前的工作表明,COF受到动态参数随机变化的强烈影响。实际上,COF对铁路牵引性能和效率至关重要。因此,COF的PDF分布必须在轮轨系统的设计中进行。

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