One of the key-elements of train design is the wheelset lifetime, which is strongly dependent on the levels of wheel wear. In order to reduce costs and increase safety, wheel wear needs to be predicted with increasing precision. In the past few years specific tools have been introduced to combine the predicted dynamic data from multi-body models, with the analytical computation of the wheel-rail contact parameters, to achieve an improved wear prediction. The aim of the present work is to consider the different methodologies for wear prediction and to create a wear prediction tool which is based on available railway dynamics codes enhanced by improved rolling contact analysis, combined with recent research on wear.

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