A simple approach for evaluating the stress concentration factor of a corroded surface using the fast Fourier transform

Kim, Hyoung-Seok; Toledo, Kyra Kamille; Jeong, Young-Soo; Kim, In‐Tae

doi:10.1016/j.engfailanal.2020.104612

Cited by 5 publications

(1 citation statement)

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“…From a technical perspective, having a theoretical approach to consider the resolution definition of the surface roughness in fatigue limit predictions is very appealing. Recently, the stress concentration for 2D and 3D machined surfaces have been comprehensively investigated, and analytical solutions via Fourier representation were derived as well 31–35 . However, the analytical derivation about the stress concentration for predicting the fatigue limit of machined round bars is still lacking.…”

Section: Introductionmentioning

confidence: 99%

Analytical prediction of the fatigue limit for axisymmetric round bars with rough surface morphology

Cheng

Zhu

Zhang

et al. 2021

Fatigue Fract Eng Mat Struct

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Analytical approaches to calculating stress distribution in machined round bars with slightly axisymmetric surface topography were derived. Surface morphologies of machined round bars were simplified as axisymmetric geometries and simulated in the form of Fourier representation. According to the point method of the theory of critical distance (TCD), an analytical expression for predicting the fatigue notch factor (FNF) of rough round specimens was proposed as well. The effectiveness of the proposed analytical expression was well verified by finite element method (FEM), with relative errors of less than 15%. Besides, the definition of the upper cut‐off frequency for estimating the fatigue limit of rough round bars was discussed comprehensively. Results showed that stress concentration factor (SCF) was sensitive to the upper cut‐off frequency and unable to be convergent, while FNF tended to be convergent and was mainly determined by low frequencies of surface topography. It explained why the height parameters of surface morphologies are the most significant characteristic parameters in determining fatigue behaviors.

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Section: Introductionmentioning

confidence: 99%