Size effect in fatigue based on the extreme value distribution of defects

    Research output: Contribution to journalArticleScientificpeer-review

    10 Citations (Scopus)

    Abstract

    Fatigue limits need to be extrapolated from test specimens to manufactured products. The relevant industry standards provide a method for this by utilizing the statistics of defects in the material. We show here that the standard method involves an inappropriate definition. Moreover, it relates to the characteristic size of the largest defects, which is not associated with any unique exceedance probability. We outline a more consistent method which, by a quantile of the largest defects, relates the sample size effect to the desired failure probability. This method is applicable also to samples smaller than the test specimen.
    Original languageEnglish
    Pages (from-to)68-71
    Number of pages4
    JournalMaterials Science & Engineering A: Structural Materials: Properties, Microstructure and Processing
    Volume594
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA1 Journal article-refereed

    Fingerprint

    Fatigue of materials
    Defects
    defects
    quantiles
    industries
    Statistics
    statistics
    products
    Industry

    Keywords

    • fatigue
    • gracture
    • material defect
    • microanalysis
    • size effect
    • steel

    Cite this

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    title = "Size effect in fatigue based on the extreme value distribution of defects",
    abstract = "Fatigue limits need to be extrapolated from test specimens to manufactured products. The relevant industry standards provide a method for this by utilizing the statistics of defects in the material. We show here that the standard method involves an inappropriate definition. Moreover, it relates to the characteristic size of the largest defects, which is not associated with any unique exceedance probability. We outline a more consistent method which, by a quantile of the largest defects, relates the sample size effect to the desired failure probability. This method is applicable also to samples smaller than the test specimen.",
    keywords = "fatigue, gracture, material defect, microanalysis, size effect, steel",
    author = "Lasse Makkonen and R. Rabb and Maria TIkanm{\"a}ki",
    year = "2014",
    doi = "10.1016/j.msea.2013.11.045",
    language = "English",
    volume = "594",
    pages = "68--71",
    journal = "Materials Science & Engineering A: Structural Materials: Properties, Microstructure and Processing",
    issn = "0921-5093",
    publisher = "Elsevier",

    }

    TY - JOUR

    T1 - Size effect in fatigue based on the extreme value distribution of defects

    AU - Makkonen, Lasse

    AU - Rabb, R.

    AU - TIkanmäki, Maria

    PY - 2014

    Y1 - 2014

    N2 - Fatigue limits need to be extrapolated from test specimens to manufactured products. The relevant industry standards provide a method for this by utilizing the statistics of defects in the material. We show here that the standard method involves an inappropriate definition. Moreover, it relates to the characteristic size of the largest defects, which is not associated with any unique exceedance probability. We outline a more consistent method which, by a quantile of the largest defects, relates the sample size effect to the desired failure probability. This method is applicable also to samples smaller than the test specimen.

    AB - Fatigue limits need to be extrapolated from test specimens to manufactured products. The relevant industry standards provide a method for this by utilizing the statistics of defects in the material. We show here that the standard method involves an inappropriate definition. Moreover, it relates to the characteristic size of the largest defects, which is not associated with any unique exceedance probability. We outline a more consistent method which, by a quantile of the largest defects, relates the sample size effect to the desired failure probability. This method is applicable also to samples smaller than the test specimen.

    KW - fatigue

    KW - gracture

    KW - material defect

    KW - microanalysis

    KW - size effect

    KW - steel

    U2 - 10.1016/j.msea.2013.11.045

    DO - 10.1016/j.msea.2013.11.045

    M3 - Article

    VL - 594

    SP - 68

    EP - 71

    JO - Materials Science & Engineering A: Structural Materials: Properties, Microstructure and Processing

    JF - Materials Science & Engineering A: Structural Materials: Properties, Microstructure and Processing

    SN - 0921-5093

    ER -