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Fault tree analysis in the R programming environment. Treatmentof common cause failures

https://doi.org/10.21683/1729-2646-2018-18-3-3-9

Abstract

Aim. This paper is the continuation of [1] that proposes using the R programming language for fault tree analysis (FTA). In [1], three examples are examined: fault tree (FT) calculation per known probabilities, dynamic FT calculation per known distributions of times to failure for a system’selements. In the latter example, FTA is performed for systems with elements that are described by different functional and service models. Fault tree analysis (FTA) is one of the primary methods of dependability analysis of complex technical systems. This process often utilizes commercial software tools like Saphire, Risk Spectrum, PTC Windchill Quality, Arbitr, etc. Practically each software tool allows calculating the dependability of complex systems subject to possible common cause failures (CCF). CCF are the associated failures of a group of several elements that occur simultaneously or within a short time interval (i.e. almost simultaneously) due to one common cause (e.g. a sudden change in the climatic service conditions, flooding of the premises, etc.). An associated failure is a multiple failure of several system elements, of which the probability cannot be expressed simply as the product of the probabilities of unconditional failures of individual elements. There are several generally accepted models used in CCF probability calculation: the Greek letters model, the alpha, beta factor models, as well as their variations. The beta factor model is the most simple in terms of associated failures simulation and further dependability calculation. The other models involve combinatorial search associated events in a group of n events, that becomes labor-consuming if the number n is large. Therefore, in the above software tools there are some restrictions on the n, beyond which the probability of CCF is calculated approximately. In the current R FaultTree package version there are no above CCF models, therefore all associated failures have to be simulated manually, which is not complicated if the number of associated events is small, as well as useful in terms of understanding the various CCF models. In this paper, for the selected diagram a detailed analysis of the procedure of associated failures simulation is performed for alpha and beta factor models. The Purposeof this paper consists in the detailed analysis of the alpha and beta factor methods for a certain diagram, in the demonstration of fault tree creation procedure taking account of ССF using R’s FaultTree package.

Methods. R’s FaultTree scripts were used for the calculations and FTA capabilities demonstration.

Conclusions. Two examples are examined in detail. In the first example, for the selected block diagram that contains two groups of elements subject to associated failures, the alpha factor model is applied. In the second example, the beta factor model is applied. The deficiencies of the current version of FaultTree package are identified. Among the main drawbacks we should indicate the absence of some basic logical gates.

About the Authors

A. V. Antonov
JSC RASU
Russian Federation

Alexander V. Antonov, Doctor of Engineering, Professor, Chief Expert, Division for Justifying Calculations of Design Solutions, JSC RZSU.

Moscow.



E. Yu. Galivets
JSC RASU
Russian Federation

Evgeny Yu. Galivets, Deputy Director of Department, Head of Design Division, JSC RASU.

Moscow.



V. A. Chepurko
JSC RZSU
Russian Federation

Valery A. Chepurko, Candidate of Physics and Mathematics, Associate Professor, Chief Specialist, Division for Justifying Calculations of Design Solutions. 

Moscow.



A. N. Cherniaev
JSC RZSU
Russian Federation

Alexey N. Cherniaev, Candidate of Engineering, Deputy Technical Director, Director of Design Department.

Moscow.



References

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Antonov A.V., Galivets E.Yu., Chepurko V.A., Cherniaev A.N. Fault tree analysis in the R programming environment. Treatmentof common cause failures. Dependability. 2018;18(3):3-9. https://doi.org/10.21683/1729-2646-2018-18-3-3-9

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ISSN 1729-2646 (Print)
ISSN 2500-3909 (Online)