Systematic statistical characterisation of stress-life datasets using 3-Parameter distributions

Joshua Hoole*, Pia Sartor, Julian Booker, Jonathan Cooper, Xenofon V. Gogouvitis, R. Kyle Schmidt

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

1 Citation (Scopus)
38 Downloads (Pure)


The variability present in S-N datasets is typically characterised using probability distributions to enable the construction of Probability-S-N curves for design. 3-Parameter Log-Normal and Weibull distributions have been proposed as alternative distributions to the commonly assumed 2-Parameter Log-Normal distribution. This paper performs statistical characterisation of a 4340 steel S-N dataset from the Engineering Sciences Data Unit using a systematic methodology. The 3-Parameter Weibull distribution provided improved characterisation of the S-N dataset. Using a case study, it was also demonstrated that use of a 3-Parameter Weibull distribution can increase component safe-life values by 20% when compared to the 2-Parameter Log-Normal distribution.

Original languageEnglish
Article number105216
Number of pages15
JournalInternational Journal of Fatigue
Early online date31 Jul 2019
Publication statusPublished - 1 Dec 2019


  • Fatigue Design
  • Probabilistic Analysis
  • S-N Curves
  • Statistics


Dive into the research topics of 'Systematic statistical characterisation of stress-life datasets using 3-Parameter distributions'. Together they form a unique fingerprint.

Cite this