2010
DOI: 10.1016/j.wear.2009.07.020
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Surface initiated tooth flank damage. Part II: Prediction of micropitting initiation and mass loss

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Cited by 34 publications
(26 citation statements)
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“…Other numerical approaches for prediction of micropitting in gear teeth include those of Brandão et al [11,12] and Li and Kahraman [13][14][15]. Evans et al [16] use a mixed lubrication model to predict the micropitting damage accumulation during a single mesh cycle in a pair of helical gears.…”
Section: Introductionmentioning
confidence: 99%
“…Other numerical approaches for prediction of micropitting in gear teeth include those of Brandão et al [11,12] and Li and Kahraman [13][14][15]. Evans et al [16] use a mixed lubrication model to predict the micropitting damage accumulation during a single mesh cycle in a pair of helical gears.…”
Section: Introductionmentioning
confidence: 99%
“…One of their key results was that the lowest film thickness occurred because of surface valleys, which helped the lubricant oil to escape between the contact surfaces in the transverse direction. Brandão et al [17] presented a numerical model and compared with a FZG testing of gear surface-initiated damages, to predict the micropitting and gear tooth wear loss. The predictions and measurement of wear losses were correlated, but the surface roughness results did not match well.…”
Section: Review Of Recent Micropitting Researchmentioning
confidence: 99%
“…As can be observed, the model is comprised of two great blocks: one for the calculation of the elastic stresses at each instant of the meshing of the gears and another for the application of the Dang-Van high cycle fatigue initiation model to each point within the depth of 30 µm inside the tooth surface. It is not within the scope of this document to explain the model in detail, which is fully exposed in [4]. Instead, the readers attention is directed to several elements that must be provided if the model is to have adequate accuracy:…”
Section: Numerical Modelmentioning
confidence: 99%
“…The first through third item are resolved through measurement. In particular, the third item is pointed to the reader's attention because it was the source of some uncertainty in [4] that [5] has dispelled. As for the remaining items, as well as the actual fatigue initiation criterion, they will be briefly discussed in what follows for the convenience of the reader.…”
Section: Numerical Modelmentioning
confidence: 99%
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