MS9.4 - Dynamics of Railway infrastructures

The current regulations address the limit-state of running safety of non-ballasted railway bridges by applying the same concept as for ballasted bridges. In this context, an uncalibrated safety factor of two is applied to an arbitrarily chosen bridge deck vertical acceleration threshold (i.e., 10 m/s^2) to prevent train derailments. The former can be used in simplified modelling strategies, namely moving load approaches; however, the latter can be accounted for by the unloading ratio. This ratio basically calculates the ratio of the difference between static and dynamic vertical loads to the static one. It expresses the loss of wheel-rail contact through the cost of constructing complex computational models that take into account train-track-bridge interactions. Despite this hypothesis in the design regulations, previous studies have not found a strong correlation between these two situations. In addition, to the authors' knowledge, the bridge deck vertical acceleration threshold was chosen based on the assumption that the induced dynamic loads would overcome gravity at higher accelerations, resulting in a loss of contact between wheels and rail, which has also been refuted by previous studies. Considering these inconsistencies, a better understanding of the simplified design criteria is essential before conducting further studies such as calibration of partial safety factors. Therefore, this study considers a large number of representative design scenarios with bridge characteristics, number and length of spans, and train characteristics for a wide range of operating speeds. Wheel-rail contact loss is then statistically compared with other criteria that can be derived from moving load models, such as bridge deck vertical accelerations/deflections, and support reactions. It should be noted that the design situations considered are obtained from the upper and lower quantiles of the probability distribution functions corresponding to each of the contributing variables.

The presence of unbalanced loads on freight trains can potentially cause higher levels of deterioration or even the failure of railway track components, as well as situations of risk of derailment. This paper aims to develop an unsupervised methodology for the early detection of unbalanced load scenarios, both in lateral and longitudinal directions. The study relies on a 3D numerical simulation of the train-track dynamic response to the presence of unbalanced vertical loads. Different measurements layouts were tested, in terms of type (strain gauges and accelerometers) and position of the sensors. The proposed methodology involves: i) the feature extraction based on an Autoregressive Exogenous model (ARX); ii) the feature modelling based on a Principal Component Analysis (PCA) to remove the influence of operational effects; iii) feature fusion, and iv) feature classification based on a cluster analysis to distinguish a regular loading situation from a faulty one.