Evaluation of local strength via microstructural quantification in a pearlitic rail steel deformed by simultaneous compression and torsion

Dimitrios Nikas, Xiaodan Zhang*, Johan Ahlström

*Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

    239 Downloads (Pure)

    Abstract

    Pearlitic steels are commonly used for railway rails because they combine good strength and wear properties. During service, the passage of trains results in large accumulation of shear strains in the surface layer of the rail, sometimes leading to crack initiation. Knowledge of the material properties versus the shear strain in this layer is therefore important for fatigue life predictions. In this study, fully pearlitic R260 rail steel was deformed using a bi-axial torsion-compression machine to reach different shear strains. Microstructural parameters including interlamellar spacing, thickness of ferrite and cementite lamellae and dislocation density in the ferrite lamellae, as well as hardness were quantitatively characterized at different shear strain levels. Based on the microstructural observations and the quantification of the microstructural parameters, the local flow stresses were estimated based on boundary strengthening and dislocation strengthening models. A good agreement was found between the estimated flow stresses and the flow stresses determined from microhardness measurements.
    Original languageEnglish
    JournalMaterials Science and Engineering: A - Structural Materials: Properties, Microstructure and Processing
    Volume737
    Pages (from-to)341-347
    ISSN0921-5093
    DOIs
    Publication statusPublished - 2018

    Keywords

    • Pearlitic rail steel
    • TEM
    • Hardness
    • Strengthening mechanisms
    • Dislocation density

    Fingerprint

    Dive into the research topics of 'Evaluation of local strength via microstructural quantification in a pearlitic rail steel deformed by simultaneous compression and torsion'. Together they form a unique fingerprint.

    Cite this