Long freight trains & long-term rail surface damage – a systems perspective. Issue 6 (3rd June 2023)

• Record Type: Journal Article
• Authors: Krishna, Visakh V.; Wu, Qing; Hossein-Nia, Saeed; Spiryagin, Maksym; Stichel, Sebastian
• Is Part Of: Vehicle system dynamics. Volume 61:Issue 6(2023)
• Page Start: 1500
• Page End: 1523
• Publication Date: 2023-06-03
• Subjects: Rail surface damage -- multi-body simulation -- longitudinal train dynamics -- grinding -- rolling contact fatigue -- wear; Motor vehicles -- Dynamics -- Periodicals; Electronic journals; 629.231
• DOI: 10.1080/00423114.2022.2085584
• Languages: English
• ISSNs: 0042-3114

Abstract

Abstract : In this work, the authors present a detailed train-track interaction model of a long freight train operation to predict long-term rail surface damage. In addition to vehicles and track, intermediate maintenance actions in the form of cyclic grinding passes have also been modelled according to European standards to realistically represent the evolving wheel-rail interface. The influence of longitudinal train dynamics in the form of inter-vehicle interactions, traction, braking, gradients, etc is also included in this method to reflect their effect on damage evolution. The authors demonstrate that the novel 'Train-track interaction' formulation is more complete and therefore better suited to study long-term rail surface damage as opposed to existing 'vehicle-track' formulations since the former brings the system dynamics at play, significantly altering the wheel-rail interaction. A key highlight of this work is that the rail surface damage is expressed in the form of evolving rail profiles over a large tonnage passing and by depicting RCF-affected zones. This framework can be tuned into a digital twin to guide infrastructure managers regarding the condition of rail surface as a function of tonnage passage. This can in turn facilitate predictive maintenance of track depending on traffic and operation.