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DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 369 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 361 | - |
dc.citation.title | STRUCTURAL ENGINEERING AND MECHANICS | - |
dc.citation.volume | 69 | - |
dc.contributor.author | Prabhu, Sreehari Ramachandra | - |
dc.contributor.author | Lee, Young-Joo | - |
dc.contributor.author | Park, Yeun Chul | - |
dc.date.accessioned | 2023-12-21T19:37:36Z | - |
dc.date.available | 2023-12-21T19:37:36Z | - |
dc.date.created | 2019-03-11 | - |
dc.date.issued | 2019-02 | - |
dc.description.abstract | The determination of Paris' law parameters based on crack growth experiments is an important procedure of fatigue life assessment. However, it is a challenging task because it involves various sources of uncertainty. This paper proposes a novel probabilistic method, termed the S-N Paris law (SNPL) method, to quantify the uncertainties underlying the Paris' law parameters, by finding the best estimates of their statistical parameters from the S-N curve data using a Bayesian approach. Through a series of steps, the SNPL method determines the statistical parameters (e.g., mean and standard deviation) of the Paris' law parameters that will maximize the likelihood of observing the given S-N data. Because the SNPL method is based on a Bayesian approach, the prior statistical parameters can be updated when additional S-N test data are available. Thus, information on the Paris' law parameters can be obtained with greater reliability. The proposed method is tested by applying it to S-N curves of 40H steel and 20G steel, and the corresponding analysis results are in good agreement with the experimental observations. | - |
dc.identifier.bibliographicCitation | STRUCTURAL ENGINEERING AND MECHANICS, v.69, no.4, pp.361 - 369 | - |
dc.identifier.doi | 10.12989/sem.2019.69.4.361 | - |
dc.identifier.issn | 1225-4568 | - |
dc.identifier.scopusid | 2-s2.0-85062457026 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/26170 | - |
dc.identifier.url | http://www.techno-press.com/?page=container&journal=sem&volume=69&num=4# | - |
dc.identifier.wosid | 000459303300001 | - |
dc.language | 영어 | - |
dc.publisher | TECHNO-PRESS | - |
dc.title | A new Bayesian approach to derive Paris' law parameters from S-N curve data | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Engineering, Civil; Engineering, Mechanical | - |
dc.relation.journalResearchArea | Engineering | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.subject.keywordAuthor | Bayesian approach | - |
dc.subject.keywordAuthor | fatigue crack growth | - |
dc.subject.keywordAuthor | Paris&apos | - |
dc.subject.keywordAuthor | law | - |
dc.subject.keywordAuthor | statistical parameter | - |
dc.subject.keywordAuthor | S-N curve | - |
dc.subject.keywordPlus | FATIGUE-RELIABILITY | - |
dc.subject.keywordPlus | LIFE | - |
dc.subject.keywordPlus | INITIATION | - |
dc.subject.keywordPlus | INSPECTION | - |
dc.subject.keywordPlus | STRENGTH | - |
dc.subject.keywordPlus | JOINTS | - |
dc.subject.keywordPlus | STATE | - |
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