2017
DOI: 10.1007/s00170-017-1033-3
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Probabilistic methodology for predicting the dispersionof residual stresses and Almen intensity considering shot peening process uncertainties

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Cited by 12 publications
(2 citation statements)
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“…For its characterization, sine 28 or cosine curves 29,30 are mainly used to describe the surface RS and the depth of the RS layer, among other aspects, in combination with the distribution law of SP-induced RS measured experimentally. Considering the variability of the SP parameters, a probabilistic approach to evaluating the induced RS distribution 31 can predict the SP-induced RS profile with a specific probability of occurrence. The ratio between the thickness of the compressive RS layer and the depth of the maximum RS after SP is generally between 3.6 and 4.3.…”
Section: Introductionmentioning
confidence: 99%
“…For its characterization, sine 28 or cosine curves 29,30 are mainly used to describe the surface RS and the depth of the RS layer, among other aspects, in combination with the distribution law of SP-induced RS measured experimentally. Considering the variability of the SP parameters, a probabilistic approach to evaluating the induced RS distribution 31 can predict the SP-induced RS profile with a specific probability of occurrence. The ratio between the thickness of the compressive RS layer and the depth of the maximum RS after SP is generally between 3.6 and 4.3.…”
Section: Introductionmentioning
confidence: 99%
“…Atig et.al. [12] proposed a probabilistic methodology to evaluate the variability of the induced residual stress and Almen intensity of the shot peening parameters. Based beam bending principles, Divid et al [13] quantify the relationship between the several parameters affecting measured Almen intensity.…”
Section: Introductionmentioning
confidence: 99%