Estimating the fatigue stress concentration factor of machined surfaces

Arola, D.; Williams, Cyril L.

doi:10.1016/s0142-1123(02)00012-9

Cited by 322 publications

(158 citation statements)

References 8 publications

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“…The asperities that constitute surface roughness can also be treated as microscopic notches by introducing a stress concentration factor K t . This factor can be calculated either from averaged geometrical parameters of the surface [11], and or by finite element analysis (FEA) [12].…”

Section: Introductionmentioning

confidence: 99%

The use of areal surface topography characterisation in relation to fatigue performance

et al. 2018

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Abstract. Although the effect of surface topography on fatigue life is widely accepted, the underlying role of surface roughness from first principles is still poorly understood. Currently approaches which consider the influence of surface roughness on fatigue life prediction can be broadly classified into surface corrector factors (C s ) and stress concentration factors (K t ). Those approaches describe the surface according to the manufacturing process (machined, grounded…), or using 2D height descriptor parameters (R a , R z ...). However, these approaches are not able to correctly describe the effect of roughness on the fatigue performance where it is anticipated a richer set of surface descriptors would show correlation. The present work aims to highlight the inherent limitations of the most commonly employed 2D surface measurement and characterization techniques, and provides an insight into the application of 3D areal surface characterization processes including the use of the latest areal surface topography parameters quantifying amplitude, spatial, and hybrid topographical information which is considered to be important for fatigue performance correlation.

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Section: Introductionmentioning

confidence: 99%

The use of areal surface topography characterisation in relation to fatigue performance

et al. 2018

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“…The fatigue stress concentration factor K f was used for describing the effect of the surface roughness on the fatigue limit. It was the function of the stress concentration factor K t which can be estimated by the finite element method [5,6] or the empirical formula including the average geometric parameters of surface roughness [7,8]. A method has been also reported to estimate the fatigue life by:…”

Section: Introductionmentioning

confidence: 99%

Fatigue Life Estimation of Medium-Carbon Steel with Different Surface Roughness

Dai

Duan

et al. 2017

Applied Sciences

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Medium-carbon steel is commonly used for the rail, wire ropes, tire cord, cold heading, forging steels, cold finished steel bars, machinable steel and so on. Its fatigue behavior analysis and fatigue life estimation play an important role in the machinery industry. In this paper, the estimation of fatigue life of medium-carbon steel with different surface roughness using established S-N and P-S-N curves is presented. To estimate the fatigue life, the effect of the average surface roughness on the fatigue life of medium-carbon steel has been investigated using 75 fatigue tests in three groups with average surface roughness (R a ): 0.4 µm, 0.8 µm, and 1.6 µm, respectively. S-N curves and P-S-N curves have been established based on the fatigue tests. The fatigue life of medium-carbon steel is then estimated based on Tanaka-Mura crack initiation life model, the crack propagation life model using Paris law, and material constants of the S-N curves. Six more fatigue tests have been conducted to validate the presented fatigue life estimation formulation. The experimental results have shown that the presented model could estimate well the mean fatigue life of medium-carbon steel with different surface roughness.

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“…In order to study the character of H p (y) curves of cracking, the magnetic signals of specimen after cracking from line d 1 4 go through the cracking. It is indicated that the magnetic signals of cracking and stress concentration both sharply change and their gradient «k« intensely increase, but there are abnormal magnetic peaks only in the magnetic signals of cracking.…”

Section: Results and Analysismentioning

confidence: 99%

Distinguishing Stress Concentration or Cracking in Ferromagnetic Material Using Abnormal Magnetic Signals

Changliang

Dong

et al. 2013

Mater. Trans.

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In the geomagnetic field, spontaneous magnetic signals in ferromagnetic materials can be induced by stress, which can be potentially applied to estimate the damage degree. In this research, a method of distinguishing stress concentration or cracking in ferromagnetic material was proposed. The normal component of magnetic field, H p (y), was measured on the surfaces of ferromagnetic specimens with notch. The results indicated that the shapes of H p (y) curves of stress concentration and cracking were different, there was abnormal magnetic peak in the H p (y) curve of cracking. Meanwhile, the effect of lift-off on abnormal magnetic peak was studied, and the optimal lift-off value was also presented.

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Estimating the fatigue stress concentration factor of machined surfaces

Cited by 322 publications

References 8 publications

The use of areal surface topography characterisation in relation to fatigue performance

The use of areal surface topography characterisation in relation to fatigue performance

Fatigue Life Estimation of Medium-Carbon Steel with Different Surface Roughness

Distinguishing Stress Concentration or Cracking in Ferromagnetic Material Using Abnormal Magnetic Signals

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