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Rail RCF damage quantification and comparison for different damage models
KTH, School of Engineering Sciences (SCI), Engineering Mechanics.ORCID iD: 0000-0002-4477-971x
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics, Rail Vehicles.ORCID iD: 0000-0002-6346-6620
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics, Rail Vehicles.ORCID iD: 0000-0003-1583-4625
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics, Rail Vehicles.ORCID iD: 0000-0002-8237-5847
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2022 (English)In: Railway Engineering Science, ISSN 2662-4745, Vol. 30, no 1, p. 23-40Article in journal (Refereed) Published
Abstract [en]

There are several fatigue-based approaches that estimate the evolution of Rolling Contact Fatigue (RCF) on rails over time, built to be used in tandem with Multi-Body Simulations of vehicle dynamics. However, most of the models are not directly comparable with each other since they are based on different physical models even though they shall predict the same RCF damage at the end. This article studies different approaches to quantifying RCF and puts forward a measure for the degree of agreement between them. The methodological framework studies various steps in the RCF quantification procedure within the context of one another, identifies the ‘primary quantification step’ in each approach and compares results of the fatigue analyses. In addition to this, two quantities - ‘similarity’ and ‘correlation’ have been put forward to give an indication of mutual agreement between models. Four widely used surface-based and subsurface-based fatigue quantification approaches with varying complexities have been studied. Different operational cases corresponding to a metro vehicle operation in Austria have been considered for this study. Results showed that the best possible quantity to compare is the normalized damage increment per loading cycle coming from different approaches. Amongst the methods studied, approaches that included the load distribution step on the contact patch showed higher similarity and correlation in their results. While the different approaches might qualitatively agree on whether contact cases are ‘damaging’ due to RCF, they might not quantitatively correlate with the trends observed for damage increment values. 

Place, publisher, year, edition, pages
Springer Nature , 2022. Vol. 30, no 1, p. 23-40
National Category
Vehicle and Aerospace Engineering
Research subject
Järnvägsgruppen - Fordonsteknik; Vehicle and Maritime Engineering; Järnvägsgruppen - Infrastruktur
Identifiers
URN: urn:nbn:se:kth:diva-302640DOI: 10.1007/s40534-021-00253-yISI: 000701006500001Scopus ID: 2-s2.0-85115884568OAI: oai:DiVA.org:kth-302640DiVA, id: diva2:1598024
Funder
EU, Horizon 2020, 826206
Note

QC 20250326

Available from: 2021-09-28 Created: 2021-09-28 Last updated: 2025-03-26Bibliographically approved
In thesis
1. Long freight trains and long-term rail surface damage
Open this publication in new window or tab >>Long freight trains and long-term rail surface damage
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Track damage due to progressively increasing tonnage, especially due to longer and heavier freight trains, is one of the major problems faced in the European rail sector. In this context, to stay competitive, optimal track maintenance practices, track-friendly vehicles and safe operations of long freight trains assume prominence.

This PhD thesis studies long freight train operations and the long-term rail surface damage that they cause, to build a computer simulation-based framework for maintenance planning and assessment of running safety. 

The framework is formulated with four parts: long freight train operations, vehicle dynamics, rail surface damage and track maintenance. This is followed by a literature survey on each of the subtopics and how they are linked to each other.Safe operation of long freight trains in infrastructure bottlenecks such as S-curves is studied using three-dimensional multi-body simulations. Based on this, guidelines to build long freight trains and driving scenarios that can keep longitudinal in-train forces within acceptable limits have been provided. 

Multi-body simulation models of various freight bogies, including a novel design, are built and their dynamic running behaviour studied according to EN standards. The key focus is on track-loading and to this effect, methodologies for simulations-based assessment of `track-friendliness' of various bogie designs are studied. Various approaches to quantify rail surface damage using multi-body simulations in the form of wear and Rolling Contact Fatigue (RCF) are studied. Based on this, measures to ascertain similarities and differences in results from different approaches have been put forward. 

The impact of track maintenance, in the form of periodic rail reprofiling activities in different networks, on the evolution of rail surface damage is studied. It is found that optimal maintenance planning can be tailored depending on the type of traffic on the network.

Finally, various parts of the framework have been brought together to form a `train-track interaction' approach to facilitate optimal maintenance planning.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2022. p. 95
Series
TRITA-SCI-FOU ; 2022:01
Keywords
track friendliness; rail surface damage; multi-body simulation; longitudinal train dynamics; track maintenance; rolling contact fatigue, wear
National Category
Mechanical Engineering Vehicle and Aerospace Engineering Applied Mechanics
Research subject
Engineering Mechanics; Vehicle and Maritime Engineering; Järnvägsgruppen - Effektiva tågsystem för godstrafik
Identifiers
urn:nbn:se:kth:diva-307653 (URN)978-91-8040-130-2 (ISBN)
Public defence
2022-03-09, U1, Brinellvägen 26, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
EU, Horizon 2020
Available from: 2022-02-07 Created: 2022-02-02 Last updated: 2025-02-14Bibliographically approved

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Krishna, Visakh VHossein Nia, SaeedCasanueva, CarlosStichel, Sebastian

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