PREDICTION OF SURFACE CRACK PROPAGATION IN RAILS
The railway was established as a widely used means of transportation already by the early 1800’s. In the last decades, an increasing number of passengers and goods are being transported by the railway. Railway traffic presents several advantages compared to other means of transport such as very high capacity, punctuality, reduced CO 2 footprint and remarkable passage safety.
A key ingredient is the steel-to-steel contact between wheel and rail which reduces the frictional losses in rolling. However, the steel material of the components is subjected to severe mechanical loads. Defects such as cracks on the surface of rails and wheels greatly affect railway traffic in terms of reliability and cost. To mitigate such defects, preventive and corrective maintenance actions are often necessary. Traffic delays is an immediate
outcome especially of corrective maintenance operations, such as unscheduled replacement of a defective rail or wheel. To avoid such unplanned operations, preventive maintenance is opted for by railway infrastructure managers and operators. In such maintenance operations, existing defects on the surface of the rails and wheels are removed by grinding, milling or turning. These are operations in which the surface layer that contains the defects is removed before the cracks reach a depth below which they tend to become critical and propagate abruptly towards complete rupture of the rail. Thereby, knowledge of the direction and speed of propagation of early detected cracks is crucial information that essentially guides railway technicians on how much rail material should be removed from the rail surface and when.
Knowledge of the propagation behaviour of surface cracks in rails is limited and in current practice stems primarily from empirical knowledge. Once sufficiently severe cracks are detected in field, a small fraction of a millimetre from the surface of the rails is removed. This operation is repeated with varying intervals in different railway track sections where cracks are expected to form. These empirical methods allow for scheduling and are well suited for constant railway operational conditions. However, variation in e.g. climate conditions, the increasing number of passengers and increased amount of
transported goods over the years continuously alter railway operational conditions.
The work described in this thesis aims to contribute in exactly the information of the propagation behaviour of surface cracks in rails. To this end, theoretical and numerical simulation frameworks are developed that are based on (computational) mechanics and other engineering tools. These tools are used to develop models able to predict the propagation behaviour of cracks under arbitrary railway operational conditions. The validity of the theoretical models has been tested against crack propagation experiments from the literature and “real” data from field observations. Results indicate the great potential regarding prediction of crack propagation in rails via numerical simulations. Advances in crack growth predictive methods reported here are expected to contribute to a more sustainable railway and to optimization of the maintenance process of railway tracks. This is achieved through more targeted inspection intervals, reduced disturbance of traffic for maintenance work and more efficient use of resources.