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Joona Vaara, Miikka Väntänen, Panu Kämäräinen, Jukka Kemppainen, Tero Frondelius, Bayesian analysis of critical fatigue failure sources, International Journal of Fatigue, Volume 130, 2020, 105282, ISSN 0142-1123, https://doi.org/10.1016/j.ijfatigue.2019.105282

Bayesian analysis of critical fatigue failure sources

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Author: Vaara, Joona1; Väntänen, Miikka2; Kämäräinen, Panu1;
Organizations: 1Wärtsilä, Järvikatu 2-4, 65100 Vaasa, Finland
2Global Boiler Works Oy, Lumijoentie 8, 90400 Oulu, Finland
3Applied and Computational Mathematics, Pentti Kaiteran katu 1, 90014 University of Oulu, Finland
4Materials and Mechanical Engineering, Pentti Kaiteran katu 1, 90014 University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202003188364
Language: English
Published: Elsevier, 2020
Publish Date: 2021-09-19
Description:

Abstract

A novel approach for inferring the underlying non-metallic inclusion distribution from fatigue test fractography is presented. It is shown that the non-metallic inclusion size distribution obtained from fatigue testing differs from the extreme value distributions, which do not take fatigue into account. Fatigue, as a process, acts as a filter for the observed inclusions, and by taking advantage of this allows us to extract more refined information from the fractography using statistical inference. The emphasis in this paper is on analysis of axial fatigue testing of smooth specimens. The concepts presented here apply to all fatigue testing where the data from fracture surfaces is collected.

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Series: International journal of fatigue
ISSN: 0142-1123
ISSN-E: 1879-3452
ISSN-L: 0142-1123
Volume: 130
Article number: 105282
DOI: 10.1016/j.ijfatigue.2019.105282
OADOI: https://oadoi.org/10.1016/j.ijfatigue.2019.105282
Type of Publication: A1 Journal article – refereed
Field of Science: 111 Mathematics
112 Statistics and probability
214 Mechanical engineering
216 Materials engineering
Subjects:
Bayesian inference
Extreme values
Fatigue size effect
Fractography
Inclusion size distribution
Article
Funding: This study was conducted as part of the WIMMA (Dnro 1566/31/2015) -research project. The authors are grateful for the financial support provided by Business Finland Oy (former Tekes) and Wärtsilä Finland Oy.
Copyright information: © 2019 Elsevier Ltd. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.
  https://creativecommons.org/licenses/by-nc-nd/4.0/