The inverse search determination of the strain-energy–density (SED) control radius R1 devised in Benedetti et al. Int J Fatigue 2019;126:306–318 and based on the knowledge of the notch fatigue factor estimated using an optimal V-notch specimen geometry is here reformulated to take into account the statistical properties of the input fatigue properties. It was found that R1 exhibits a non-symmetric probability density function that is well represented by a skew-normal distribution. The uncertainty in R1 can be attributed to the uncertainty in the inverse search procedure and to the material variability in notch sensitivity. By applying the devised procedure to real experimental data, it was found that the former contribution is preponderant in the assessment of very sharp notches, while the latter dictates the fatigue strength of blunt notches, especially in the case of intrinsically flawed materials, such as those additively manufactured.

Statistical significance of notch fatigue prognoses based on the strain-energy-density method: Application to conventionally and additively manufactured materials

Santus C.
Ultimo
2020-01-01

Abstract

The inverse search determination of the strain-energy–density (SED) control radius R1 devised in Benedetti et al. Int J Fatigue 2019;126:306–318 and based on the knowledge of the notch fatigue factor estimated using an optimal V-notch specimen geometry is here reformulated to take into account the statistical properties of the input fatigue properties. It was found that R1 exhibits a non-symmetric probability density function that is well represented by a skew-normal distribution. The uncertainty in R1 can be attributed to the uncertainty in the inverse search procedure and to the material variability in notch sensitivity. By applying the devised procedure to real experimental data, it was found that the former contribution is preponderant in the assessment of very sharp notches, while the latter dictates the fatigue strength of blunt notches, especially in the case of intrinsically flawed materials, such as those additively manufactured.
2020
Benedetti, M.; Dallago, M.; Santus, C.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1052073
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