Correlation-based Sensitivity Analysis of Fault Tree
Copyright (c) 2026 Pokorádi László
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Abstract
The Fault Tree Analysis (FTA) is a systematic, top-down logical and diagrammatic risk assessment
tool, which shows the causal relations leading to a given undesired event, so-called Top Event
(TE). The events that cannot be further developed are the Basic Events (BEs). Probabilistic Fault
Tree Analysis (PFTA) is a quantitative analysis method used to calculate the probability of TE
depending on probabilities of BEs. Analysing the correlation coefficients between the reliabilities
of TE and BEs is effective in selecting the critical elements that have the greatest impact on system
reliability. The aim of the study is, on the one hand, to develop a correlation-based method for
examining the sensitivity of probabilistic fault tree analysis. On the other hand, to compare the
sensitivity results obtained in this way with the results of the Linear Fault Tree Sensitivity Model
developed by the Author earlier.
Keywords:
How to Cite
References
[1] I. N. Bronstejn, Matematikai kézi-könyv. Budapest, Typotext, 2005.
[2] IEC 1025 Fault Tree Analysis (FTA). Genf, International Electrotechnical Commission, 1990.
[3] M. H. Kalos, P. A. Whitlock, Monte Carlo Methods. Wiley VCH, 2008. Online: https://doi.org/10.1002/9783527626212
[4] G. A. Korn, T. M. Korn, Mathematical Handbook for Scientists and Engineers. Courier Corporation, 2000.
[5] E. Labašová, „Reliability Assessment oh the Systems with Simple Interconnections,” Research Papers Faculty of Materials Science and Technology Slovak University of Technology, 29. évf. 49. sz. pp. 36–42. 2021. Online: https://doi.org/10.2478/rput-2021-0022
[6] N. Metropolis, S. Ulam, „The Monte Carlo Method,” Journal of the American Statistical Association, 44. évf. 247. sz. pp. 335–341. Online: https://doi.org/10.1080/01621459.1949.10483310
[7] MSZ EN 1050, Gépek biztonsága – A kockázatértékelés elvei. Budapest, Magyar Szab-ványügyi Testület, 1999.
[8] M. E. J., Newman, G. T., Barkema, Monte-Carlo Methods in Statistical Physics. New York, Oxford University Press, 1999, p. 475. Online: https://doi.org/10.1093/oso/9780198517962.001.0001
[9] L. Pokorádi, Rendszerek és folyamatok modellezése. Debrecen, Campus, 2008.
[10] L. Pokorádi, „Mátrixalgebrai Hibafa-érzékenységelemzés,” Multidiszciplináris Tudo-mányok, 103–110. 2011. Online: https://ojs.uni-miskolc.hu/index.php/multi/article/view/68/66
[11] L. Pokorádi, Sensitivity Investigation of Fault Tree Analysis With Matrix-Algebraic Method, Theory and Applications of Mathematics & Computer Science, 1. sz. pp 34–44. 2011.
[12] E. Zio, The Monte Carlo Simulation Method for System Reliability and Risk Analysis. Springer, 2013. Online: https://link.springer.com/book/10.1007/978-1-4471-4588-2