Prediction of the fatigue limit defining mechanism of nodular cast iron based on statistical microstructural features |
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Author: | Vaara, Joona1; Väntänen, Miikka2; Laine, Jarkko1; |
Organizations: |
1Wärtsilä, Järvikatu 2-4, 65100 Vaasa, Finland 2Global Boiler Works Oy, Lumijoentie 8, 90400 Oulu, Finland 3Applied and Computational Mathematics, University of Oulu, Pentti Kaiteran katu 1, 90014, Finland
4Materials and Mechanical Engineering, University of Oulu, Pentti Kaiteran katu 1, 90014, Finland
5Faculty of Built Environment, Tampere University, Korkeakoulunkatu 7, 33720, Finland |
Format: | article |
Version: | published version |
Access: | open |
Online Access: | PDF Full Text (PDF, 2.3 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2023050440936 |
Language: | English |
Published: |
Elsevier,
2022
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Publish Date: | 2023-05-04 |
Description: |
AbstractThe microstructure and nodule count of large-size nodular cast iron components vary spatially. These variables are qualitatively known to affect the fatigue limit, yet no model exists to quantify the effects. Some of the physical aspects, such as the clustering of graphite nodules and the role of ferrite microhardness in ferritic–pearlitic nodular cast iron fatigue, have been unclear in the literature. This paper aims to clarify and quantify these aspects. In the absence of casting defects, the largest ferrite with a crack initiating graphite is shown to be the physical, and statistical, explanation for the mixed grade fatigue limit. see all
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Series: |
Engineering fracture mechanics |
ISSN: | 0013-7944 |
ISSN-E: | 1873-7315 |
ISSN-L: | 0013-7944 |
Volume: | 277 |
Article number: | 109004 |
DOI: | 10.1016/j.engfracmech.2022.109004 |
OADOI: | https://oadoi.org/10.1016/j.engfracmech.2022.109004 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
216 Materials engineering |
Subjects: | |
Funding: |
This study was conducted as part of the ISA Wärtsilä (Dnro 7734/31/2018) -research project. Co-funded by the European Union Grant Agreement No. 101058179 ENGINE project. The authors are grateful for the financial support provided by Business Finland Oy and Wärtsilä Finland Oy. |
Copyright information: |
© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
https://creativecommons.org/licenses/by/4.0/ |