The life of railway wheels and rails has been decreasing in recent years. This is mainly caused by more traffic and running at higher vehicle speed. A higher speed usually generates higher forces, unless compensated by improved track and vehicle designs, in the wheel-rail contact, resulting in more wear and rolling contact fatigue (RCF) damage to the wheels and rails. As recently as 15 years ago, RCF was not recognised as a serious problem. Nowadays it is a serious problem in many countries and ''artificial wear'' is being used to control the growth of cracks by preventive re-profiling and grinding of, respectively, the wheels and rails. This can be used because a competition exists between wear and surface initiated RCF: At a high wear rate, RCF does not have the opportunity to develop further. Initiated cracks are in this case worn off and will not be able to propagate deep beneath the surface of the rail or wheel. When wheel-rail damage in terms of wear and RCF can be predicted, measures can be taken to decrease it. For example, the combination of wheel and rail profiles, or the combination of vehicle and track, can be optimised to control the damage. Not only can this lead to lower maintenance costs, but also to a safer system since high potential risks can be detected in advance. This thesis describes the development of a wheel-rail life prediction tool with regard to both wear and surface-initiated RCF. The main goal of this PhD work was to develop such a tool where vehicle-track dynamics simulations are implemented. This way, many different wheel-rail contact conditions which a wheel or a rail will encounter in reality can be taken into account. The wear prediction part of the tool had already been successfully developed by others to be used in combination with multibody simulations. The crack prediction part, however, was more difficult to be used in combination with multibody simulations since crack propagation models are time-consuming. Therefore, more concessions had to be made in the crack propagation part of the tool, since time-consuming detailed modelling of the crack, for example in Finite Elements models, was not an option. The use of simple and fast, but less accurate, crack propagation models is the first step in the development of a wheel-rail life prediction model. Another goal of this work was to verify the wheel-rail prediction tool against measurements of profile and crack development. For this purpose, the wheel profiles of trains running on the Stockholm commuter network have been measured together with the crack development on these wheels. Three train units were selected and their wheels have been measured over a period of more than a year. The maximum running distance for these wheels was 230,000 km. A chosen fatigue model was calibrated against crack and wear measurements of rails to determine two unknown parameters. The verification of the prediction tool against the wheel measurements, however, showed that one of the calibrated parameters was not valid to predict RCF on wheels. It could be concluded that wheels experience relatively less RCF damage than rails. Once the two parameters were calibrated against the wheel measurements, the prediction tool showed promising results for predicting both wear and RCF and their trade-off. The predicted position of the damage on the tread of the wheel also agreed well with the position found in the measurements. / <p>QC 20150526</p>
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-168023 |
| Date | January 2015 |
| Creators | Dirks, Babette |
| Publisher | KTH, Spårfordon, Stockholm |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Doctoral thesis, comprehensive summary, info:eu-repo/semantics/doctoralThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | TRITA-AVE, 1651-7660 ; 2015:16 |
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