Digitala Vetenskapliga Arkivet

Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Surface integrity investigations for prediction of fatigue properties after machining of alloy 718
RISE Research Institutes of Sweden, Materials and Production, Manufacturing Processes. University West, Sweden.ORCID iD: 0000-0003-2991-2911
GKN Aerospace Engine System Sweden AB, Sweden.
Chalmers University of Technology, Sweden.
RISE Research Institutes of Sweden, Materials and Production, Manufacturing Processes.ORCID iD: 0000-0003-3656-1806
Show others and affiliations
2021 (English)In: International Journal of Fatigue, ISSN 0142-1123, E-ISSN 1879-3452, Vol. 144, article id 106059Article in journal (Refereed) Published
Abstract [en]

Fatigue performance is crucial for gas turbine components, and it is greatly affected by the manufacturing processes. Ability to predict the expected fatigue life of a component based on surface integrity has been the objective in this work, enabling new processing methods. Alloy 718 samples were prepared by different machining setups, evaluated in fatigue testing and surface integrity investigations. These results generated two predictive statistical multi-variate regression models. The fatigue correlated well with roughness, residual stresses and deformation. The two models showed great potential, which encourages further exploration to fine-tune the procedure for the particular case. © 2020 The Authors

Place, publisher, year, edition, pages
Elsevier Ltd , 2021. Vol. 144, article id 106059
Keywords [en]
Alloy 718, Fatigue prediction, Machining, Non-conventional machining, Surface integrity, Fatigue testing, Petroleum prospecting, Regression analysis, Component based, Fatigue performance, Fatigue properties, Manufacturing process, Processing method, Regression model, Fatigue of materials
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-51925DOI: 10.1016/j.ijfatigue.2020.106059Scopus ID: 2-s2.0-85097719719OAI: oai:DiVA.org:ri-51925DiVA, id: diva2:1520321
Note

Funding details: VINNOVA; Funding text 1: The results from this work was granted from the research project G5Demo-2 [2013-04666] and SWE DEMO MOTOR [2015-06047] financed by VINNOVA, Sweden’s innovation agency. Special thanks to GKN Aerospace Sweden AB. The authors also would like to thank the KK-foundation and the SiCoMaP research school.

Available from: 2021-01-20 Created: 2021-01-20 Last updated: 2023-05-22Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Holmberg, JonasBerglund, Johan
By organisation
Manufacturing Processes
In the same journal
International Journal of Fatigue
Natural Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 54 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf