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STRUCTURAL RELIABILITY ANALYSIS BASED ON P-BOXES

https://doi.org/10.33979/2073-7416-2020-92-6-51-58

Abstract

The article describes a method for reliability (probability of non-failure) analysis of structural elements based on p-boxes. An algorithm for constructing two p-blocks is shown. First p-box is used in the absence of information about the probability distribution shape of a random variable. Second p-box is used for a certain probability distribution function but with inaccurate (interval) function parameters. The algorithm for reliability analysis is presented on a numerical example of the reliability analysis for a flexural wooden beam by wood strength criterion. The result of the reliability analysis is an interval of the non-failure probability boundaries. Recommendations are given for narrowing the reliability boundaries which can reduce epistemic uncertainty. On the basis of the proposed approach, particular methods for reliability analysis for any structural elements can be developed. Design equations are given for a comprehensive assessment of the structural element reliability as a system taking into account all the criteria of limit states.

About the Author

Sergey Al. Solovyev
Vologda State University
Russian Federation


References

1. Melchers R.E., Beck A.T. Structural reliability analysis and prediction. John Wiley & Sons. 2018. 497 p

2. Karanki D.R., Kushwaha H.S., Verma A.K., Ajit S. Uncertainty analysis based on probability bounds (p-box) approach in probabilistic safety assessment // Risk Analysis: An International Journal. 2009. Vol. 29. No. 5. Pp. 662-675

3. Yang X., Liu Y., Zhang Y., Yue Z. Hybrid reliability analysis with both random and probability-box variables // Acta Mechanica, 2015. Vol. 226. No. 5. Pp. 1341-1357

4. Liu X., Yin L., Hu L., Zhang Z. An efficient reliability analysis approach for structure based on probability and probability box models // Structural and Multidisciplinary Optimization. 2017. Vol. 56. No. 1 Pp. 167-181

5. Золина Т.В., Садчиков П.Н. Моделирование снеговой нагрузки на покрытие промышленного здания // Вестник МГСУ. 2016. №. 8. С. 25-33

6. Rackwitz R., Flessler B. Structural reliability under combined random load sequences // Computers & Structures. 1978. Vol. 9. No. 5. Pp. 489-494

7. Уткин Л.В., Уткин В.С., Редькин А.Н. Расчет надежности стальных рам по критерию устойчивости при многопараметрической нагрузке с использованием неравенства Чебышева // Надежность. 2011. № 3(38). С. 42-52

8. Most T. Efficient structural reliability methods considering incomplete knowledge of random variable distributions // Probabilistic Engineering Mechanics. 2011. Vol. 26. No. 2. Pp. 380-386

9. Cohn T.A., Lane W.L., Stedinger J.R. Confidence intervals for expected moments algorithm flood quantile estimates // Water Resources Research. 2001. Vol. 37. No. 6. Pp. 1695-1706

10. Ditlevsen O., Madsen H.O. Structural reliability methods. New York: John Wiley & Sons Ltd. 1996. 361 p

11. Martin W.E., Bridgmon K.D. Quantitative and statistical research methods: From hypothesis to results. New York: Jossey-Bass, 2012. 496 p

12. Ni Z., Qiu Z. Hybrid probabilistic fuzzy and non-probabilistic model of structural reliability // Computers & Industrial Engineering. 2010. Vol. 58. No. 3. Pp. 463-467

13. Jiang C., Zhang Z., Han X., Liu J. A novel evidence-theory-based reliability analysis method for structures with epistemic uncertainty // Computers & Structures. 2013. Vol. 129. Pp. 1-12

14. Li J., Chen J., Fan W. The equivalent extreme-value event and evaluation of the structural system reliability // Structural safety. 2007. Vol. 29. No. 2. Pp. 112-131

15. Greig G. L. An assessment of high-order bounds for structural reliability // Structural safety. 1992. Vol. 11. No. 3-4. Pp. 213-225


Review

For citations:


Solovyev S.A. STRUCTURAL RELIABILITY ANALYSIS BASED ON P-BOXES. Building and Reconstruction. 2020;(6):51-58. (In Russ.) https://doi.org/10.33979/2073-7416-2020-92-6-51-58

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ISSN 2073-7416 (Print)