The role of track stiffness and its spatial variability on long-term track quality deterioration

Abstract

With rapid advances in sensor and condition monitoring technologies, railways infrastructure managers are turning their attention towards the promises that digital information and big data will help them understand and manage their assets more efficiently. In addition to existing track geometry records, it is evident that track stiffness is a key physical quantity to help assess track quality and its long-term deterioration. The present paper analyses the role of the track stiffness and its spatial variability through a set of computational experiments, varying other vehicle and track physical quantities such as vehicle unsprung mass, speed and track vertical irregularities. The support stiffness conditions are obtained using a sample procedure from an Autoregressive Integrated Moving Average (ARIMA) model to generate representative larger set of data from previously on-site measured data. A set of computational experiments is carefully designed, varying different physical variables, and a vehicle-track interaction model is used to estimate track geometry deterioration rates. A series of log-linear regression models are then used to analyse the impact of the tested physical variables on the track deterioration. The main findings suggest that the spatial variability of track stiffness contributes significantly to the track deterioration rates, and thus it should be used in the future to better target design and maintenance of railway track. Finally, a comparative study of some settlement models available in literature shows that they are very dependent on the test conditions under which they have been derived.

The role of stiffness variation in switches and crossings: Comparison of vehicle–track interaction models with field measurements

“…baseline scenario and the difference in terms of displacement signal SD over the entire panel is up to 70%. These differences may contribute to important under-or over-prediction of long-term behavioural characteristics of the track when used with numerical simulation tools [14].…”

“…Measurements of stiffness from rolling devices give the composite trackbed stiffness (dynamic values in the case of RSMV, static values in the case of devices developed in China [12] and USA [13]), calculated from the measured displacement under a known axle load [11]. Owing to local variations such as missing or aged rail and/or baseplate pads, it may not be as straightforward to separate the influence of the trackbed from that of the fixing system and superstructure on a per bearer basis as on plain line [14].…”

Development of an On-Board Measurement System for Railway Vehicle Wheel Flange Wear

“…For example if the track flexibility has a role in the wheel wear process, the track longitudinal stiffness variations in a curved track will also be a factor via possible increased impact loads [19] and increased maximum rail deflections [20]. In addition, tract stiffness variations lead to varied track settlements [21], and hence, irregularities. Other factors such as surface roughness, and environmental conditions that could lead to track irregularities must also be accounted in the prediction models.…”

A model for the stochastic prediction of track support stiffness

“…Grossoni et al, [31] developed a stochastic model to predict track stiffness using an autoregressive integrated moving average (ARIMA ) method calibrated against falling weight deflectometer (FWD) estimates of trackbed stiffness from two sites comprising 155 and 80 sleepers. The ARIMA method allowed for dependence between sleepers and weighted a number of preceding sleepers for their influence on the stiffness of the current sleeper.…”