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International Journal of Steel Structures

, Volume 19, Issue 1, pp 71–81 | Cite as

Fatigue Reliability Analysis of Steel Welded Member Using Probabilistic Stress-Life Method

  • Yeon-Soo ParkEmail author
Article
  • 56 Downloads

Abstract

This paper attempts to develop an analytical technique for fatigue reliability evaluation of a steel welded member. The probabilistic stress-life method is an important one for the fatigue reliability evaluation of a steel welded member. In this method, the stress range frequency distribution of the stress history of a steel welded member defined as a loading block is obtained from the stress frequency analysis and the parameters of the probability distribution for the stress range frequency distribution are used for numerical simulation. The probability of failure of the steel welded member under loading block is obtained from the Monte Carlo Simulation in conjunction with the Miner’s rule, the Modified Miner’s rule, and the Haibach’s rule for fatigue damage evaluation. Through this procedure, a fatigue reliability evaluation that can predict the number of loading block of failure and the residual fatigue life is possible. Also according to the 50, 90, and 99% reliability, failure times are indicated respectively.

Keywords

Fatigue Reliability Stress range frequency distribution Steel welded member Failure 

References

  1. Ariduru, S. (2004). Fatigue life calculation by rainflow cycle counting method, Ph.D. Dissertation, The Graduate School of Natural and Applied Sciences of Middle East Technical University.Google Scholar
  2. Barsom, J. M., & Rolfe, S. T. (1999). Fracture and fatigue control in structures, applications of fracture mechanics. Englewood Cliffs: Prentice-Hall, Inc.CrossRefGoogle Scholar
  3. Ellyin, F. (2001). Fatigue damage, crack growth and life prediction. Boca Raton: Chapman & Hall.Google Scholar
  4. Fricke, W., & Kahl, A. (2005). Comparison of different structural stress approaches for fatigue assessment of welded ship structures. Marine Structures, 18, 473–488.CrossRefGoogle Scholar
  5. Fuchs, H. O., & Stephen, R. I. (2000). Metal fatigue in engineering. New York: Wiley.Google Scholar
  6. Gentle, J. E. (2004). Random number generation and Monte Carlo methods (2nd ed.)., Statics and Computing Berlin: Springer.zbMATHGoogle Scholar
  7. Hosseini, A., Sahrapeyma, A., & Marefat, M. S. (2013). A reliability-based methodology for considering corrosion effects on fatigue deterioration in steel bridges–part I: methodology. International Journal of Steel Structures, 13(4), 645–656.CrossRefGoogle Scholar
  8. Korea Ministry of Construction & Transportation. (2005). Korea design standard of highway bridge. Seoul: Korea Road & Transportation Association.Google Scholar
  9. Li, Z., & Zhang, Y. (2014). Fatigue life prognosis study of welded tubular joints in signal support structures. International Journal of Steel Structures, 14(2), 281–292.MathSciNetCrossRefGoogle Scholar
  10. Limbrunner, J. F., Vogel, R. M., & Linfield, C. B. (2000). Estimation of harmonic mean of a lognormal variable. Journal of Hydrologic Engineering, 5(1), 59–66.CrossRefGoogle Scholar
  11. Lukic, M., & Cremona, C. (2001). Probabilistic assessment of welded Joints versus fatigue and fracture. Journal of Structural Engineering, 127(2), 211–212.CrossRefGoogle Scholar
  12. Mohammad, A. (2000). Methods for estimating the parameters of the Weibull distribution (pp. 1–11). Riyadh: King Abdulaziz City for Science and Technology.Google Scholar
  13. Park, J. Y., & Kim, H. K. (2014). Fatigue life assessment for a composite box girder. International Journal of Steel Structures, 14(4), 843–853.CrossRefGoogle Scholar
  14. Pourzeynali, S., & Datta, T. K. (2005). Reliability analysis of suspension bridges against fatigue failure from the gusting of wind. Journal of Bridge Engineering, 10(3), 262–271.CrossRefGoogle Scholar
  15. Sahrapeyma, A., Hosseini, A., & Marefat, M. S. (2013). Life-cycle prediction of steel bridges using reliability-based fatigue deterioration profile; case study of Neka bridge. International Journal of Steel Structures, 13(2), 229–242.CrossRefGoogle Scholar
  16. Sutherland H. J. and Mandell J. F. (2004). The effect of mean stress on damage predictions for spectral loading of fiberglass composite coupons. In EWEA, Special topic conference, The Science of Making Torque from the Wind, Delft (pp. 546-555). April 19–21.Google Scholar
  17. Wang, Z., Tan, L., & Wang, Q. (2013). Fatigue strength evaluation of welded structural details in corrugated steel web girders. International Journal of Steel Structures, 13(4), 707–721.CrossRefGoogle Scholar
  18. Weibull, W. (1961). Fitting of Curves to Observations. In W. Weibull (Ed.), Fatigue testing and analysis of results (pp. 201–203). New York: Pergamon Press.Google Scholar
  19. Yang, Y. S., Seo, Y. S., & Lee, J. O. (1999). Structure reliability engineering. Seoul: Seoul National University Publication.Google Scholar
  20. Zhou, Y. E. (2006). Assessment of bridge remaining fatigue life through field strain measurement. Journal of Bridge Engineering, 11(6), 737–744.CrossRefGoogle Scholar

Copyright information

© Korean Society of Steel Construction 2018

Authors and Affiliations

  1. 1.Department of Civil EngineeringChonnam National UniversityGwang-JuKorea

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