IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-0-85729-218-6_3.html
   My bibliography  Save this book chapter

Principles Underpinning Reliability based Prediction of Fatigue and Fracture Behaviours

In: Fatigue and Fracture Reliability Engineering

Author

Listed:
  • J. J. Xiong

    (Beihang University)

  • R. A. Shenoi

    (School of Engineering Sciences, University of Southampton)

Abstract

A series of original and practical approaches including new techniques in determining fatigue and fracture performances, phenomenological expressions for generalized constant life curves, parameter estimation formulas, the two-dimensional probability distributions of generalized strength in ultra-long life regions are proposed. New techniques on randomization approach of deterministic equations and single-point likelihood method (SPLM) are presented to address the paucity of data in determining fatigue and fracture performances based on reliability concepts. Three new randomized models of time/state-dependent processes are presented for estimating the P-a-t, P-da/dN-ΔK and P-S-N curves, by using a randomization approach of deterministic equations and single-point ikelihood method (SPLM), dealing with small sample numbers of data. The confidence level formulations for these curves are also given. Two new phenomenological expressions for generalized constant life curves are developed based on traditional fatigue constant life curve, and new parameter estimation formulas of generalized constant life curves are deduced from a linear correlation coefficient optimization approach. From the generalized constant life curves proposed, the original two-dimensional joint probability distributions of generalized strength are derived.

Suggested Citation

  • J. J. Xiong & R. A. Shenoi, 2011. "Principles Underpinning Reliability based Prediction of Fatigue and Fracture Behaviours," Springer Series in Reliability Engineering, in: Fatigue and Fracture Reliability Engineering, chapter 0, pages 63-103, Springer.
    • Handle: RePEc:spr:ssrchp:978-0-85729-218-6_3
    DOI: 10.1007/978-0-85729-218-6_3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ssrchp:978-0-85729-218-6_3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.