PSI - Issue 13

Przemysław Strzelecki / Procedia Structural Integrity 13 (2018) 631 – 635 Author name / Structural Integrity Procedia 00 (2018) 000–000

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4. Summary and conclusions From the analysis presented it may be deduced that the scatter of fatigue life is different for each geometry of specimens. In general, the scatter of the fatigue life is smaller for higher value of K t with exception of notched specimens with K t equal to 2.6. Probably, the scatter of the fatigue life for the specimens was higher for K t 2.6 than K t 2, because the dimensional deviation has more influence for specimens with sharp notch. Making soft notch for construction element can reduce the scatter of fatigue life, but the difference between the stress amplitude for smooth and notched for 0.1 % probability can be small. 11% reduction of stress amplitude was noticed for notched specimens with K t 1.6 comparing to smooth specimens. In addition, experimental tests should be made to estimate the influence size effect on the scatter fatigue life. Tomaszewski and Sempruch (2017) presented the influence size effect on the expected fatigue life, but they didn’t mention the dispersion of the tests result for each geometry. Acknowledgements The research for this article was financially supported by the National Science Centre, project no. DEC-2017/01/X/ST8/00562. References ASTM E-739-91, 2006. Standard Practice for Statistical Analysis of Linear or Linearized Stress-Life (S-N) and Strain-Life (ε-N) Fatigue Data. Gope, P.C., 2012. Scatter analysis of fatigue life and prediction of S-N curve. Journal of Failure Analysis and Prevention 12, 507–517. https://doi.org/10.1007/s11668-012-9590-0 ISO-12107, 2012. Metallic materials - fatigue testing - statistical planning and analysis of data. Geneva. Klemenc, J., Fajdiga, M., 2012. Estimating S-N curves and their scatter using a differential ant-stigmergy algorithm. International Journal of Fatigue 43, 90–97. https://doi.org/10.1016/j.ijfatigue.2012.02.015 Lee, Y.L., Paw, J., Hathaway, Richard, B., Barkey, Mark, E., 2005. Fatigue Testing and Analysis - Theory and Practice. Elsevier Butterworth– Heinemann. PN-EN ISO 6892-1:2016, 2016. Metallic materials - Tensile testing - Part 1: Method of test at room temperature. Rinne, H., 2008. The Weibull Distribution, The Weibull Distribution. Chapman and Hall/CRC. https://doi.org/10.1201/9781420087444 Sarkani, S., Mazzuchi, T. a., Lewandowski, D., Kihl, D.P., 2007. Runout analysis in fatigue investigation. Engineering Fracture Mechanics 74, 2971–2980. https://doi.org/10.1016/j.engfracmech.2006.08.026 Schijve, J., 2009. Fatigue of structures and materials, Second. ed, Fatigue of Structures and Materials. Springer Science+Business Media. Schijve, J., 2005. Statistical distribution functions and fatigue of structures. International Journal of Fatigue 27, 1031–1039. https://doi.org/10.1016/j.ijfatigue.2005.03.001 Strzelecki, P., Sempruch, J., 2016. Verification of analytical models of the S-N curve within limited fatigue life. Journal of Theoretical and Applied Mechanics 54, 63. https://doi.org/10.15632/jtam-pl.54.1.63 Strzelecki, P., Sempruch, J., 2012. Experimental Verification of the Analytical Method for Estimated S-N Curve in Limited Fatigue Life. Materials Science Forum 726, 11–16. https://doi.org/10.4028/www.scientific.net/MSF.726.11 Strzelecki, P., Tomaszewski, T., 2016. Application of Weibull distribution to describe S-N curve with using small number specimens, in: AIP Conference Proceedings. AIP Publishing, p. 020007. https://doi.org/10.1063/1.4965939 Tomaszewski, T., Sempruch, J., 2017. Fatigue life prediction of aluminium profiles for mechanical engineering. Journal of Theoretical and Applied Mechanics 55, 497–507. https://doi.org/10.15632/jtam-pl.55.2.497 Weibull, W., 1949. A statistical representation of fatigue failures in solids Appendix. Transactions of the Royal Institute of Technology Stockholm, Sweden.