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Article . 2020 . Peer-reviewed
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PubMed Central
Article . 2020
Data sources: PubMed Central
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Probabilistic Estimation of Fatigue Strength for Axial and Bending Loading in High-Cycle Fatigue

Authors: Tomasz Tomaszewski; Przemysław Strzelecki; Adam Mazurkiewicz; Janusz Musiał;

Probabilistic Estimation of Fatigue Strength for Axial and Bending Loading in High-Cycle Fatigue

Abstract

In this paper, the sensitivity to the type of loads (axial and bending loading) of selected construction materials (AW6063 T6 aluminum alloy, S355J2+C structural steel, and 1.4301 acid-resistant steel) in high-cycle fatigue was verified. The obtained S-N fatigue characteristics were described by a probabilistic model of the 3-parameters Weibull cumulative distribution function. The main area of research concerned the correct implementation of the weakest link theory model. The theory is based on a highly-stressed surface area and a highly-stressed volume in the region of the highest stresses. For this purpose, an analytical model and a numerical model based on the finite element method were used. The model that gives the lowest error implemented in specific test conditions was determined on the basis of high-cycle fatigue analysis. For the analyzed materials, it was a highly-stressed volume model based on the weakest link theory.

Keywords

Weibull distribution, rotary bending, high-cycle fatigue, Article, axial loading

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Top 10%
Top 10%
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