Statistical analysis of high cycle fatigue life and inclusion size distribution in shot peened 300M steel

Bag, Amrita; Delbergue, Dorian; Bocher, Philippe; Lévesque, Martin; Brochu, Myriam

doi:10.1016/j.ijfatigue.2018.08.009

Cited by 37 publications

(15 citation statements)

References 30 publications

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“…The S-N dataset used within this study is for 4340 steel, which is a high strength steel and typical of the materials used within aircraft landing gear components [6,30]. The Engineering Sciences Data Unit (ESDU) provide a rich S-N dataset for 4340 steel [3].…”

Section: Engineering Sciences Data Unit 4340 Steel S-n Datasetmentioning

confidence: 99%

“…The first investigation considered the value required to achieve a given at each stress level for the fitted 2P Log-Normal and 3P Weibull distributions ( ). is computed using the inverse of the CDF of the fitted distribution [6]. Figure 7 shows the 2P Log-Normal distribution and 3P Weibull distribution fitted to the dataset at Stress Level 6 and the presence of the threshold parameter for the 3P Weibull distribution can be clearly seen.…”

Section: Impact Of 3-parameter Weibull Distributions On P-s-n Curvesmentioning

confidence: 99%

“…Firstly, it has been identified that there are other 3P distributions within the literature, such as the Generalised Extreme Value (GEV) distribution, which encompasses the Gumbel, Fréchet and Weibull distributions [6]. The GEV distribution has been recently applied to a 300M steel S-N dataset (a modification of 4340 steel) [6] and therefore future work should investigate the application of the GEV distribution to the 4340 S-N dataset.…”

Section: Future Workmentioning

confidence: 99%

“…To achieve reliable fatigue design for safety-critical components, the variability within is often mitigated through the construction of Probability-S-N curves (P-S-N), which represent an S-N curve with a constant Probability of Survival ( ) [6]. A recent example demonstrating the construction of P-S-N curves is presented by Zhu et al [7].…”

Section: Introductionmentioning

confidence: 99%

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Systematic statistical characterisation of stress-life datasets using 3-Parameter distributions

Hoole

Sartor

Booker

et al. 2019

International Journal of Fatigue

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The variability present in S-N datasets is typically characterised using probability distributions to enable the construction of Probability-S-N curves for design. 3-Parameter Log-Normal and Weibull distributions have been proposed as alternative distributions to the commonly assumed 2-Parameter Log-Normal distribution. This paper performs statistical characterisation of a 4340 steel S-N dataset from the Engineering Sciences Data Unit using a systematic methodology. The 3-Parameter Weibull distribution provided improved characterisation of the S-N dataset. Using a case study, it was also demonstrated that use of a 3-Parameter Weibull distribution can increase component safe-life values by 20% when compared to the 2-Parameter Log-Normal distribution.

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Section: Engineering Sciences Data Unit 4340 Steel S-n Datasetmentioning

confidence: 99%

Section: Impact Of 3-parameter Weibull Distributions On P-s-n Curvesmentioning

confidence: 99%

Section: Future Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Systematic statistical characterisation of stress-life datasets using 3-Parameter distributions

Hoole

Sartor

Booker

et al. 2019

International Journal of Fatigue

View full text Add to dashboard Cite

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“…7,8) However, the use of rapid austenitization is difficult for large components due to the longtime heat transfer from surface to interior. To improve fatigue life, Amrita et al 9,10) employed a method of shot peening that increased the residual compressive stress, but this method becomes ineffective when the applied stress exceeds 0.64 times of yield stress. At present, there still has been no relatively satisfactory way established to simultaneously improve the toughness and fatigue life of large ultrahigh strength steel components.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Improvement of Toughness and Fatigue Life in a Typical Ultrahigh Strength Steel by a New Deep Cryogenic Treatment Process

et al. 2021

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Effect of Surface Mechanical Attrition Treatment on Surface Topography and Dry Sliding Wear Performance of AA7075‐T6

Yarar,

Erturk,

Karabay

2024

Adv Eng Mater

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Surface roughness significantly impacts the service life of materials, particularly in relation to fatigue and wear behavior. This study investigates the effects of surface mechanical attrition treatment (SMAT) on the wear performance and surface topography of AA7075‐T6 aluminum alloy. Experimental investigations are conducted using a specially designed vibration table to apply SMAT at low speeds, varying shot amount, and shot diameter. Surface roughness is measured using a 3D optical profilometer, and wear performance is evaluated through friction coefficient, wear rate, and microstructural analysis via scanning electron microscope. The results highlight several key findings. First, SMAT demonstrates the capability to yield smoother surfaces compared to equivalent processes, enhancing performance and applicability in engineering contexts. Second, SMATed samples exhibit increased surface roughness compared to untreated samples, underscoring the influence of SMAT on surface topography and its potential implications for wear resistance and frictional behavior. The comparative analysis shows that SMAT treatment increases surface roughness from 0.14 μm to a maximum of 0.24 μm. Finally, a notable reduction in friction coefficient, up to 22%, is observed in SMATed AA7075‐T6 samples, indicating the effectiveness of SMAT in improving tribological properties and enhancing component longevity subjected to frictional forces.

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Statistical analysis of high cycle fatigue life and inclusion size distribution in shot peened 300M steel

Cited by 37 publications

References 30 publications

Systematic statistical characterisation of stress-life datasets using 3-Parameter distributions

Systematic statistical characterisation of stress-life datasets using 3-Parameter distributions

Simultaneous Improvement of Toughness and Fatigue Life in a Typical Ultrahigh Strength Steel by a New Deep Cryogenic Treatment Process

Effect of Surface Mechanical Attrition Treatment on Surface Topography and Dry Sliding Wear Performance of AA7075‐T6

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