The permanent railway track deformation caused by regular train traffic is important for infrastructure managers and railway contractors, as it determines the railway track quality. Although several successful approaches have been made to address the topic of the permanent railway track deformation, these have only been applied at specific locations, and have not yet been successfully applied at a network level. This paper presents a methodology that can be applied at the network level, by making use of a stochastic subsoil model to characterise the subsoil uncertainty and variability along the railway line, and by combining it with a dynamic train-track model and a cumulative cyclic deformation model. This methodology is illustrated by analysing a railway track section of 9 km in the Netherlands. The effects of the train service, such as train speed and axle loads, on the permanent deformation of the track are quantified. The proposed methodology has been partially validated against results of the dynamic stiffness obtained during the passage of a measurement train. The results illustrate the added value of this methodology for infrastructure managers and railway contractors as it allows for the quantification, at network level, of the consequences of train service changes for the future state of the railway network.

定期列车交通引起的永久性铁路轨道变形对基础设施管理者和铁路承包商来说非常重要，因为它决定了铁路轨道质量。尽管已经提出了几种成功的方法来解决永久铁路轨道变形的问题，但这些方法仅适用于特定位置，尚未在网络级别成功应用。本文提出了一种可在网络层面应用的方法，通过使用随机底土模型来表征铁路沿线的底土不确定性和可变性，并将其与动态列车轨道模型和累积循环变形相结合。模型。通过分析荷兰 9 公里的铁路轨道段来说明这种方法。火车服务的影响，如列车速度和轴荷，对轨道的永久变形进行量化。所提出的方法已针对在测量列车通过期间获得的动态刚度的结果进行了部分验证。结果说明了这种方法对基础设施管理者和铁路承包商的附加价值，因为它允许在网络级别量化列车服务变化对铁路网络未来状态的影响。