Abstract
In this study, the effects of salt solution, the presence of notch on fatigue life scatter, and sample size selection for estimation of fatigue life under different probabilities and confidence levels have been investigated. Comparison has been made with smooth specimen tested in air medium. It is seen that notches have significantly higher effect than other factors (salt solutions, smooth geometry, etc.). The minimum number of specimens required for fatigue life estimation within tolerable error, R o, at different fatigue testing conditions has also been presented both for log normal and Weibull distribution models. It has been found that estimation of fatigue life using Weibull model needs higher sample size than log normal model. Beyond a certain sample size, fatigue life estimation is independent of sample size. The article also presents a method for minimum sample size selection procedure to estimate fatigue life or to draw S–N curve.
Similar content being viewed by others
References
Salivar, G.C., Creighton, D.L., Hoeppner, D.W.: Effect of frequency and environment on fatigue crack propagation of SA533B-1 steel. Eng. Fract. Mech. 14, 337–352 (1981)
Amzallag, C., Rabbe, P., Desestret, A.: Corrosion fatigue behavior of some special stainless steel. In: Corrosion Fatigue Technology, ASTM, STP 642, pp. 117–132. American Society for Testing and Materials, Philadelphia (1978)
Vosikovsky, O.: Frequency, stress ratio, and potential effects on fatigue crack growth of HY130 steel in salt water. J. Test. Eval. 6(3), 175–182 (1978)
Kondo, T., Kikuyama, T., Nakajima, H., Shindo M., Nagasaki, R.: Corrosion fatigue of ASTM A-302B steel in high temperature water, the simulated nuclear reactor environment. NACE, pp. 539–556 (1971)
Scott, P.M., Thorpe, T.W., Carney, R.A.F.: Corrosion fatigue crack initiation from blunt notches in structural steel exposed to sea water. Adv. Fract. Res. 2, 1595–1602 (1989)
Gope, P.C.: Determination of sample size for estimation of fatigue life by using Weibull and log normal distribution. Int. J. Fatigue 18(8), 745–752 (1999)
Parida, N., Das, S.K., Gope, P.C., Mohanty, O.N.: Probability, confidence, and sample size in fatigue testing. J. Test. Eval. 18(6), 385–389 (1990)
Chuliang, Y.A.N., Kege, L.I.U.: Theory of economic life prediction and reliability assessment of aircraft structures. Chin. J. Aeronaut. 24, 164–170 (2011)
Rinaldi, A., Peralta, P., Krajcinovic, D., Lai, Y.-C.: Prediction of scatter in fatigue properties using discrete damage mechanics. Int. J. Fatigue 28, 1069–1080 (2006)
Schijve, J.: Statistical distribution functions and fatigue of structures. Int. J. Fatigue 27, 1031–1039 (2005)
Mohd, S., Mutoh, Y., Otsuka, Y., Miyashita, Y., Koike, T., Suzuki, T.: Scatter analysis of fatigue life and pore size data of die-cast AM60B magnesium alloy. Eng. Fail. Anal. 22, 64–72 (2012)
DuQuesnay, D.L., Underhill, P.R.: Fatigue life scatter in 7xxx series aluminum alloys. Int. J. Fatigue 32, 398–402 (2010)
Montgomery, D.C.: Design and Analysis of Experiments. Wiley, New York (1976)
Little, R.E., Jebe, E.H.: Statistical Design of Fatigue Experiments. Applied Science, London (1975)
Nakayasu, H.: Method of pooling fatigue data and its application to the data base on fatigue strength. In: Tanaka, T., Nishijima, S., Ichikawa, M. (eds.) Current Japanese Materials Research, vol. 2, pp. 21–43. Elsevier Applied Science, London (1987)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Gope, P.C. Scatter Analysis of Fatigue Life and Prediction of S–N Curve. J Fail. Anal. and Preven. 12, 507–517 (2012). https://doi.org/10.1007/s11668-012-9590-0
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11668-012-9590-0