Synchrotron and neural network analysis of the influence of composition and heat treatment on the rolling contact fatigue of hypereutectoid pearlitic steels

W. Solano-Alvarez, M. J. Peet, E. J. Pickering, J. Jaiswal, A. Bevan, H. K.D.H. Bhadeshia

    Research output: Contribution to journalArticlepeer-review

    Abstract

    A series of experimental hypereutectoid pearlitic steels were tested under rolling contact sliding conditions using a lubricated twin-disc setup to study the influence of different chemical compositions and heat treatments on rolling contact fatigue life. Tested samples were then characterised using microscopy and synchrotron measurements as a function of depth from the contact surface. Results, analysed through neural networks, indicate that the most influential factor in lengthening the number of cycles to crack initiation of hypereutectoid steels is hardness, attained by increasing the cooling rate from the hot rolling temperature, but adequate alloying additions can enhance it further. The harder, fast-cooled samples displayed less plastic flow at the surface than the softer slow-cooled ones. With regard to chemical composition, silicon was found to strengthen the ferrite thus reducing strain incompatibilities with the cementite, preventing in this way the fragmentation and eventual dissolution of the lamellae. This is beneficial since larger depths of cementite dissolution were found in samples with lower cycles to crack initiation for a given cooling rate (hardness). Samples containing vanadium lasted longer and displayed less plastic deformation at the surface than those without, at a similar hardness.

    Original languageEnglish
    Pages (from-to)259-269
    Number of pages11
    JournalMaterials Science and Engineering A
    Volume707
    Early online date14 Sept 2017
    DOIs
    Publication statusPublished - 7 Nov 2017

    Keywords

    • Cementite dissolution
    • Hypereutectoid rail steels
    • Neural network
    • Pearlite
    • Rolling contact fatigue
    • Synchrotron

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