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The probability of HCF - Surface and sub-surface models
KTH, School of Engineering Sciences (SCI), Solid Mechanics (Dept.).ORCID iD: 0000-0002-2917-5045
KTH, School of Engineering Sciences (SCI), Solid Mechanics (Dept.).
2016 (English)In: International Journal of Fatigue, ISSN 0142-1123, E-ISSN 1879-3452, Vol. 92, 147-158 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, new probabilistic HCF evaluation models based on the surface and the sub-surface region is presented. The sub-surface model stem from the hypothesis that the highest fatigue risk depends on the loading in a region slightly below the free surface area. There, the materials microstructural barriers must be overcome by fatigue crack propagation. The size of the region with high load below the surface affects the fatigue risk. The predictive capability of the new proposed HCF model is studied along with comparisons to other state of the art HCF probabilistic models. Fatigue data originating from different geometries and materials conducted at different loading modes, rotating bending and uniaxial loading is used for the analysis. The investigation performed in this work indicate that the new proposed models increase the prediction accuracy and hence predictive capability.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 92, 147-158 p.
Keyword [en]
Experiments, Probabilistic model, Highly loaded regions, High cycle fatigue
National Category
Applied Mechanics
Identifiers
URN: urn:nbn:se:kth:diva-193972DOI: 10.1016/j.ijfatigue.2016.06.021ISI: 000383930200015ScopusID: 2-s2.0-84978414670OAI: oai:DiVA.org:kth-193972DiVA: diva2:1037757
Funder
Swedish Energy Agency
Note

QC 20161018

Available from: 2016-10-18 Created: 2016-10-14 Last updated: 2016-10-18Bibliographically approved

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