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A concept for application of B-spline algorithm to density estimation of fatigue failures in 18Ni300 steel

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EN
Abstrakty
EN
P-s-n curves detailing fatigue are basic data required to ensure high reliability design. Since fatigue testing requires significant time and resource costs, the development of reliable small-sample methods is crucial to ensure the reduction in time and costs of design process. This paper investigates the possibility for applying B-spline interpolation basis functions to approximate the probability density functions on various levels of high-cycle uniaxial fatigue using the sample data of only selected stress levels. It was found that using the proposed model an iterative approach can be used to ensure acceptable fitting accuracy and to predict fatigue life on the desired probability level. As a result, the findings show the possibility for rapid modeling of the probability density function and the resulting reliability in high-cycle fatigue by using the well-known interpolation techniques based only on the basic dispersion parameters. The proposed approach provides a robust framework for fatigue life prediction, paving the way for broader applications in engineering analysis. The proposed data augmentation method seems to demonstrate the potential to reduce fatigue testing costs and simplify testing procedures.
Twórcy
  • Faculty of Mechanical Engineering, Opole University of Technology, ul. Mikołajczyka 5, 45-271 Opole, Poland
  • Faculty of Production Engineering and Logistics, Opole University of Technology, ul. Ozimska 75, 45-370 Opole, Poland
  • Faculty of Mechanical Engineering and Mechatronics, West Pomeranian University of Technology in Szczecin, al. Piastów 19, 70-310 Szczecin, Poland
Bibliografia
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  • 3. Pook, L. Metal fatigue, solid mechanics and its applications. Springer Netherlands, Dordrecht; 2007. https://doi.org/10.1007/978-1-4020-5597-3
  • 4. Kufoin, E., Susmel, L. Quantitative review of probabilistic approaches to fatigue design in the medium cycle fatigue regime. Probabilistic Engineering Mechanics. 2024; 75: 103589. https://doi. org/10.1016/j.probengmech.2024.103589
  • 5. Tomaszewski, T., Skibicki, A. Probabilistic prediction of the size effect on the fatigue strength for variable length specimens of selective laser melted 316L stainless steel. International Journal of Fatigue. 2024; 182: 108225. https://doi.org/10.1016/j. ijfatigue.2024.108225
  • 6. Kowal M., Szala M. Diagnosis of the microstructural and mechanical properties of over century-old steel railway bridge components. Engineering Failure Analysis. 2020 Mar 1; 110: 104447. https://doi. org/10.1016/j.engfailanal.2020.104447
  • 7. Rui S.S., Wei S., Sun C. Microstructure evolution, crack initiation and early growth of high-strength martensitic steels subjected to fatigue loading. International Journal of Fatigue. 2024 Nov 1; 188: 108534. https://doi.org/10.1016/j. ijfatigue.2024.108534https://doi.org/10.1016/j. ijfatigue.2024.108534
  • 8. Lehner P., Blinn B., Beck T. Changes in microstructure and mechanical properties of ferritic high chromium steel and P91 induced by isothermal fatigue. Materials Science and Engineering: A. 2025 Feb 1; 923: 147713. https://doi.org/10.1016/j. msea.2024.147713
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  • 10. Macek W., Sampath D., Pejkowski Ł., Żak K. A brief note on monotonic and fatigue fracture events investigation of thin-walled tubular austenitic steel specimens via fracture surface topography analy- sis (FRASTA). Engineering Failure Analysis. 2022 Apr 1; 134: 106048. https://doi.org/10.1016/j. engfailanal.2022.106048
  • 11. Macek W., Branco R., de Jesus J., Costa J.D., Zhu S.P., Masoudi Nejad R., et al. Strain energy density and entire fracture surface parameters relationship for LCF life prediction of additively manufactured 18Ni300 steel. International Journal of Damage Mechanics. 2024 Sep 1; 33(9): 725–47. https://doi. org/10.1177/10567895241245879
  • 12. Schijve, J. A normal distribution or a weibull distribution for fatigue lives. Fatigue & Fracture of Engineering Materials & Structures. 1993; 16: 851–859. https://doi.org/10.1111/j.1460-2695.1993.tb00124.x
  • 13. D’Antuono, P. An analytical relation between the Weibull and Basquin laws for smooth and notched specimens and application to constant amplitudę fatigue. Fatigue & Fracture of Engineering Materials & Structures. 2024; 43: 991–1004. https://doi. org/10.1111/ffe.13175
  • 14. Blacha, Ł., Karolczuk, A. Validation of the weak-est link approach and the proposed Weibull based probability distribution of failure for fatigue design of steel welded joints. Engineering Failure Analysis. 2016; 67: 46–62. https://doi.org/10.1016/j. engfailanal.2016.05.022
  • 15. Little, R. Mechanical reliability improvement: Probability and statistics for experimental testing. CRC Press, Roca Baton, USA; 2002. https:// doi.org/10.1201/9780203910993
  • 16. Banjevic, D. Remaining useful life in theory and practice. Metrika. 2009; 69: 337–349. https://doi. org/10.1007/s00184-008-0220-5
  • 17. Blacha, Ł., Derda, Sz. Fatigue life for 18Ni300 steel under uniaxial fully reversed loading, Mendeley Data, V1. 2024. https://doi.org/10.17632/r8pwh9ygn5.2
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  • 20. Weibull, W. A statistical representation of fatigue failures in solids, vol. 27. Transaction of The Royal Institute of Technology, Stockholm; 1949.
  • 21. EOS Maraging Steel MS1 Material Data Sheet. EU - EOS Store. https://www.eos.info/ website (Ac- cessed: 23.04.2024).
  • 22. ASTM E 466-15. Standard Practice for Conducting Force Controlled Constant Amplitude Axial Fatigue Tests of Metallic Materials; ASTM International.
  • 23. Yu, Y., Lee, B., Cho, Y. Multiaxial fatigue reliability assessment using a differential ant-stigmergy algorithm. Journal of Mechanical Science and Technology. 2019; 33: 2093–2099. https://doi.org/10.1007/ s12206-019-0413-z
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  • 26. Gofuku, S., Tamura, S., Maekawa, T. Point-tangent/ point-normal B-spline curve interpolation by geometric algorithms. Computer-Aided Design. 2009; 41: 412– 422. https://doi.org/10.1016/j.cad.2009.02.005
  • 27. Zhao, Y., Zhang, M., Ni, Q., Wang, X. Adaptive Nonparametric Density Estimation with B-Spline Bases. Mathematics. 2023; 11. https://doi. org/10.3390/math11020291
  • 28. Wang, X., Zhao, Y., Ni, Q., Tang, S. Nonparametric density estimation with nonuniform B-spline bases. Journal of Computational and Applied Mathematics. 2024; 440: 115648. https://doi.org/10.1016/j. cam.2023.115648
  • 29. Blacha, Ł. A B-spline based density estimation of fatigue failures in SLM 18Ni300 steel. In: Engieering Mechanics, 2024; 30, Fuis, V., Hajek, P. (ed.); Brno University of Technology, Institute of Solid Mechanics, Mechatronics and Biomechanics. https://doi.org/10.21495/em2024-050
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-851df61a-d773-4a76-8486-f425e762cddb
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