Towards proper sampling and statistical modelling of defects

Ali Cetin (Corresponding Author), Andrew Roiko, M. Lind

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)

Abstract

Predicting the size of the largest defect expected to occur in components based on samples obtained from polished inspection areas is a common exercise, which is even addressed in standards. However, the standard practice may occasionally yield poor results. This paper presents a comprehensive method that aims to improve some of the shortcomings of the standard practice. The method is utilized on actual defect data, which showed that the proposed method is able to predict significant experimental observations that the standard practice missed.
Original languageEnglish
Pages (from-to)1056-1065
JournalFatigue & Fracture of Engineering Materials & Structures
Volume38
Issue number9
DOIs
Publication statusPublished - 2015
MoE publication typeA1 Journal article-refereed

Fingerprint

Sampling
Defects
Inspection

Keywords

  • comprehensive method
  • standard practices
  • statistical modelling
  • statistics of extremes
  • steel cleanness

Cite this

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Towards proper sampling and statistical modelling of defects. / Cetin, Ali (Corresponding Author); Roiko, Andrew; Lind, M.

In: Fatigue & Fracture of Engineering Materials & Structures, Vol. 38, No. 9, 2015, p. 1056-1065.

Research output: Contribution to journalArticleScientificpeer-review

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AU - Cetin, Ali

AU - Roiko, Andrew

AU - Lind, M.

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KW - standard practices

KW - statistical modelling

KW - statistics of extremes

KW - steel cleanness

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