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 language | English |
|---|---|
| Pages (from-to) | 1056-1065 |
| Number of pages | 10 |
| Journal | Fatigue and Fracture of Engineering Materials and Structures |
| Volume | 38 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - 1 Sep 2015 |
| MoE publication type | A1 Journal article-refereed |
Keywords
- statistical model
- statistics of extremes
- steel
- steel cleanness