A PhD position is offered within the Department of the Built Environment of the Eindhoven University of Technology. After four years of research, you can obtain a PhD degree.
The research aims to develop models and methods for improving the prediction of the fatigue crack growth rate of squat defects in railway rails. Squat defects are the most frequently occurring type of rolling contact fatigue cracks that is found in the railway network. Once detected, these defects are classified into different categories depending on their size, and actions are taken to guarantee the safe use of the infrastructure. In the case of severe defects, these actions concern the immediate train speed reduction and replacement of the defective rail, causing large costs for the society, traffic disruptions, and the impossibility of allocating maintenance resources.
An analytical model should be developed to predict the remaining fatigue life, based on fracture mechanics. The model parameters are calibrated through experiments in our laboratory. This aims to support decision-making related to inspection intervals and replacement decisions, instead of relying only on the simple set of fixed replacement rules. The technical and scientific challenges in the proposed project which must be addressed for in the model formulation are:
A successful result is to be able to forecast squat crack propagation taking these aspects into account. The application of the results will be estimating the required inspection intervals after squat detection based on quantitative information resulting from the prediction model.
In this way, it is possible to locally apply specific predictive maintenance to railway tracks in which squat defects are found. Estimating the fatigue crack growth rate, crack orientation, and crack size at the onset of unstable growth is fundamental for determining the inspection intervals, the frequency, and the type of maintenance, of which the extent influences the cost of ownership, the durability, and the availability of the asset, potentially reducing unnecessary traffic disruption.
The research will be carried out with the support of the research organization TNO and the company ProRail, the Dutch railway infrastructure owner.
We are looking for:
The ideal candidate will meet as many of the following requirements as possible:
Do you recognize yourself in this profile and would you like to know more? Please contact
assistant prof. Davide Leonetti, d.leonetti[at]tue.nl.
For information about terms of employment, click here or contact HRServices.BE[at]tue.nl.
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