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Method for Determining the S-N curve for a Low Probability of Failure
 
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Bydgoszcz University of Science and Technology, Faculty of Mechanical Engineering, Bydgoszcz, Poland
 
 
Submission date: 2023-12-08
 
 
Final revision date: 2024-04-15
 
 
Acceptance date: 2024-09-25
 
 
Online publication date: 2024-10-01
 
 
Corresponding author
Przemysław Strzelecki   

Bydgoszcz University of Science and Technology, Faculty of Mechanical Engineering, Bydgoszcz, Poland
 
 
Journal of Theoretical and Applied Mechanics 2024;62(4):683-694
 
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ABSTRACT
This paper presents a new method for determining the S-N curve for a low probability of failure, e.g., 5%. To apply this method, only eight fatigue tests are needed, which is fewer than standard methods require. This could be achieved because the standard deviation, which is necessary for estimating the normal distribution of fatigue life, was derived from the distribution of logarithm of the yield strength. The tensile tests necessary to get the yield strength are relatively simple and cost-effective. Verification of the method was performed for fatigue tests on S355J2+C structural steel, 1.4301 and 1.4404 stainless steels, medium carbon steel C45 and AW 6063 & AW 2017A aluminium alloys. The results showed that the proposed method gave fatigue strength for 5% failure probability with a more reliable fatigue life than the S-N curve estimated according to ASTM E-739-10, 2015. Considering that the proposed method is conservative and low-cost, it can be used in engineering practice.
 
REFERENCES (25)
1.
Bai X., Zhang P., Zhang Z., Liu R., Zhang Z., 2019, New method for determining P-S-N curves in terms of equivalent fatigue lives, Fatigue and Fracture of Engineering Materials and Structures, 42, 10, 2340-2353.
 
2.
Goedel F., Mezzomo G.P., Pravia Z.M.C., 2018, Fatigue lifespan of a fillet welded joint – Hybrid approach to obtain the S-N curve with a reduced number of tests, Latin American Journal of Solids and Structures, 15, 10.
 
3.
Gope P.C., 1999, Determination of sample size for estimation of fatigue life by using Weibull or log-normal distribution, International Journal of Fatigue, 21, 8, 745-752.
 
4.
Gope P.C., 2012, Scatter analysis of fatigue life and prediction of S-N curve, Journal of Failure Analysis and Prevention, 12, 5, 507-517.
 
5.
Kurek A., Koziarska J., Kluger K., Łagoda T., 2017, Fatigue life of 2017A-T4 aluminium alloy under different types of stress, Journal of Machine Construction and Maintenance, 4, 53-61.
 
6.
Lee Y.-L., Pan J., Hathaway R.B., Barkey M.E., 2005, Fatigue Testing and Analysis – Theory and Practice, Elsevier Butterworth-Heinemann.
 
7.
Lewis G., Sadhasivini A., 2004, Estimation of the minimum number of test specimens for fatigue testing of acrylic bone cement, Biomaterials, 25, 18, 4425-4432.
 
8.
Li C., Wu S., Zhang J., Xie L., Zhang Y., 2020, Determination of the fatigue P-S-N curves – A critical review and improved backward statistical inference method, International Journal of Fatigue, 139, 105789.
 
9.
Ligaj B., Szala G., 2013, Hybrid Method for Fatigue Life Calculations (in Polish), J. Szala (Edit.), Wydawnictwo Naukowe Instytutu Technologii Eksploatacji Państwowego Instytutu Badawczego, Radom.
 
10.
Liu X., Sun Q., 2020, Small sample-based fatigue reliability analysis using non-intrusive polynomial chaos, IEEE Access, 8, 59678-59683.
 
11.
Nanninga N., White C., 2009, The relationship between extrusion die line roughness and high cycle fatigue life of an AA6082 alloy, International Journal of Fatigue, 31, 7, 1215-1224.
 
12.
Pang J.C., Li S.X., Wang Z.G., Zhang Z.F., 2014, Relations between fatigue strength and other mechanical properties of metallic materials, Fatigue and Fracture of Engineering Materials and Structures, 37, 9, 958-976.
 
13.
R Core Team, 2023, R: A Language and Environment for Statistical Computing, The R Foundation for Statistical Computing, Vienna, http://www.r-project.org/.
 
14.
Shen, C., 1994, The statistical analysis of fatigue data, Ph.D. Thesis, The University of Arizona, https://repository.arizona.edu....
 
15.
Skibicki D., Sempruch J., Pejkowski Ł., 2014, Model of non-proportional fatigue load in the form of block load spectrum, Materialwissenschaft und Werkstofftechnik, 45, 2, 68-78.
 
16.
Soh Fotsing B. D., Anago G.F., Fogue M., 2010, Statistical techniques of sample size estimating in fatigue tests, International Journal of Engineering and Technology, 2, 6, 477-481.
 
17.
Strzelecki, P., 2018, Fatigue scatter of the tests results related to error of applied stress, [In:] Advances in Mechanics: Failure, Deformation, Fatigue, Waves and Monitoring. Proceedings of the 11th International Conference on Structural Integrity and Failure, Perth, Australia, 3–6 December 2018, Dyskin, A.V., Pasternak, E. (Edits), University of Western Australia, Perth, WA, Australia, 28–32
 
18.
Strzelecki P., 2021, Determination of standard deviation for fatigue strength based on the tensile test, ICSID 2021 5th International Conference on Structural Integrity and Durability, Željko Božić (Edit.), University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Dubrovnik, 13.
 
19.
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, 1, 63-73.
 
20.
Strzelecki P., Sempruch J., Nowicki K., 2015, Accuracy of analytical-experimental method for determining the fatigue characteristics in a limited life region, Solid State Phenomena, 224, 63-68.
 
21.
Strzelecki P., Wachowski M., 2022, Effect of the stress concentration factor on the final fracture zone of aluminium AW 6063 T6 for rotating bending specimens, Materials Today Communications, 31, 103766.
 
22.
Walpole R.E., Myers R.H., Myers S.L., Ye K.E., 2012, Probability and Statistics for Engineers and Scientists, 9-th ed., Pearson Education, Inc.
 
23.
Wormsen A., Avice M., Fjeldstad A., Reinås L., Macdonald K.A., Muff A.D., 2015, Base material fatigue data for low alloy forged steels used in the subsea industry. Part 1: In air S-N data, International Journal of Fatigue, 80, 477-495.
 
24.
Xie L., Liu J., Wu N., Qian W., 2014, Backwards statistical inference method for P-S-N curve fitting with small-sample experiment data, International Journal of Fatigue, 63, 62-67.
 
25.
Zu T., Kang R., Wen M., Chen Y., 2020, α-S-N curve: A novel S-N curve modeling method under small-sample test data using uncertainty theory, International Journal of Fatigue, 139, 105725.
 
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ISSN:1429-2955
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