MS9.1 - Dynamics of Railway infrastructures

The railway track is subject to the spatial stresses imposed by the vehicle and to the stresses generated by the typical temperature ranges of the seasons, increased by the running away actions of the waters that undermine the roadbed below the rail. The imposed stresses are static and dynamic. The higher the speed of transit of the trainsets and the worse the dynamics of the vehicle, the higher the intensity of dynamic loads. The vehicle’s dynamic aggressiveness is measured primarily by the axle weight. Secondly, by the high rigidities of the primary suspension and the more or less high unsprung masses of the engines, bridges, brake discs, and bushings. The thermal stresses are measured by the temperature differences between those imposed by the seasons and those of laying the railway track. Static stresses, dynamic stresses on the rolling stock, and the stresses imposed by the seasons affect the roadbed. The work of undermining is favored by the action of water that increases the free length of inflection of the rails and varies the stiffness of the railway. These stresses cause stresses on the rail that can affect fatigue and wear and therefore line maintenance. Both parameters, due to fatigue and wear and tear, are related to average operating speeds and therefore to traffic intensity. As the speeds and intensities of traffic affect stress and fatigue cycles, the abrasive action of the wheels on the rail, and the misalignment of the complex rail sleepers concerning the underlying ballast, a comprehensive investigation of these phenomena affecting the work of the railway line is useful, to define the parameters that limit the life of the railway track. The railway track is represented by a beam resting of infinite length on an elastic ground such that at each point its reaction is proportional to the failure that the beam undergoes inflection. This hypothesis is verified experimentally because at each passage of an axis the sleepers sink into the roadbed and then rise as soon as the line is discharged. On the elasticity of the soil, there are experimental tests such as the remote transmission of sound waves and seismic waves. In the case of the railway track which is a beam resting on several points, the above considerations are valid with sufficient approximation, since the distance between the sleepers is small about the length of the rail inflection. The loads that cause high sagging close to the action and then decrease as the burdened point of the axis moves away. The wheelbase can be an influencing element. Where the wavelength interacts with a geometric dimension of the rolling stock, the concept of overlapping effects shall be used to determine the total stresses acting on the rail. The rail in addition to the vertical plane is stressed laterally in the curve for these considerations introducing the overall lateral stiffness of the railway track obtained experimentally. In the straight and in the curve, the railway track and the ground are stressed to torsion.

High-speed railway networks in Europe include thousands of bridges, which constitute potential points of failure. Presently, the assessment of running safety is reflected in the Eurocode in the form of deck acceleration limits. However, this indirect metric does not relate unambiguously to an evaluation of reliability. In order to contribute to this discussion, it is necessary to perform probabilistic analysis on different scenarios of high-speed trains crossing bridges. Since whether dealing with track instability or derailment the target probabilities of failure are very low (in the order of 10^-5 to 10^-4), typical Monte Carlo trials demand a great deal of computation cost. This work presents a practical application of Subset Simulation to mitigate this issue. Uncertainty in geometrical, mechanical, and dynamic parameters of the bridges are represented by several random variables and different sources of lateral instability are considered, such as wind and rail irregularities. The optimization process includes the sensitivity analysis of different intermediate probability density functions and sample sizes. With this application it is possible to reduce the computation cost by 3 orders of magnitude, therefore facilitating future discussions of running safety.

Nowadays, the society is highly dependent on railways, since it is the most effective mode of transportation that has the lowest greenhouse gas emissions in the transports sector. Because of that, there has been an increase in rail transport, with great dependence on transport infrastructure such as railway bridges. For that reason, and to reduce inspection and maintenance costs, some techniques using damage detection, that is part of the Structural Health Monitoring (SHM), are being developed and implemented in railway bridges, in order to these infrastructures can be used safely, thus extending their lifespan. This work is focused on the application of machine learning methodologies for damage identification in a filler-beam railway bridge, based on numerical simulations. The numerical simulations required the development of an advanced Finite Element (FE) numerical model of the train and the bridge, including the track. The dynamic analyses were performed using a train-bridge dynamic interaction method, including the track irregularities, and considering the baseline scenario of the bridge and the damage scenarios. The features extraction from the dynamic analyses will be performed based on Autoregressive models (AR) and Principal Component Analysis (PCA) applied to the acceleration records from the passing trains. Classification methodologies will be applied to select the most sensitive features for damage detection. The proposed methodology will be useful to detect early damage levels in the structure, without interfering with the normal service condition of the trains and bridge.

ABSTRACT Nowadays, transport policy is decisively influenced by environmental concerns, with railways expected to play a key role in achieving climate neutrality by 2050, according to the Green Deal proposed by the European Commission. The increase in railway traffic will require the expansion of the network, which must be done in part by kepping in service existing bridges as long as possible. Among the major threats to the structural integrity of these infrastrutures, fatigue is particularly relevant and may lead to local or global collapse. The codes in force propose global methods based on S-N curves for nominal stresses to assess fatigue damage. Nevertheless, this calculation philosophy leads to relevant and conservative approximations between the geometrical and material characteristics of a given existing detail and those that define a certain relatable normative S-N curve. The implementation of local fatigue approaches based on submodelling leveraged by modal superposition principles is critical to overcome these limitations, allowing the analysis of the local response of the real load transfer mechanism. This type of calculations can be assumed as an advanced stage applied to critical details identified using the mentioned normative global methods, following a multiphase strategy from global to local scale. In this context, an integrated methodology for fatigue life prediction of existing metallic railway bridges is suggested and applied to a real case study demonstrate the added value. Acknowledgments This work was financially supported by: Base Funding - UIDB/04708/2020 of the CONSTRUCT - Institute of R&D In Structures and Construction - funded by national funds through the FCT/MCTES (PIDDAC) and carried out within project IN2TRACK3 [101012456-H2020-S2RJU-CFM-2020]. Keywords: railway bridges; fatigue assessment; local fatigue approaches; submodelling relations; modal superposition.