Research on the software reliability quantitative evaluation of nuclear power plant digital control system based on non-homogeneous poisson process model

•A reliability evaluation method of software in NPP DCS is proposed.•TheSRGM and software failures detected in V&V are combined to assess reliability.•The BBNs method is investigated and compared with the NHPP model.•The challenges for NHPP are summarized. With the application of digital technol...

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Vydáno v:Annals of nuclear energy Ročník 144; s. 107589
Hlavní autoři: Zhang, Qing, Ma, Quan, Liu, Mingxing, Zhong, Ke, Xu, Biao, Wu, Liyin
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.09.2020
Témata:
Digital control system
Non-homogeneous poisson process
Software reliability growth model
Software reliability model
Software reliability quantitative evaluation
Software reliability model
RPC
Digital control system
DCS
Software reliability quantitative evaluation
I&C
V&V
PIPS
Software reliability growth model
Non-homogeneous poisson process
BBN
ISSN:0306-4549, 1873-2100
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Shrnutí:•A reliability evaluation method of software in NPP DCS is proposed.•TheSRGM and software failures detected in V&V are combined to assess reliability.•The BBNs method is investigated and compared with the NHPP model.•The challenges for NHPP are summarized. With the application of digital technology, the software used in various systems has become increasingly important, as well as complex. This increase in complexity and scale has led to an increase in the probability of software failure. Quantitative reliability evaluation of the digital instrumentation and control system software used in nuclear power plants represent a significant challenge. This study uses a non-homogeneous Poisson process model for quantitative evaluation of the software reliability of a nuclear power plant safety digital control system (DCS), which is the research object. To analyse the research object, a software test environment is established, and the research object is tested to obtain the software failure data. The software reliability growth model, which is widely used in other industries, is combined with data on nuclear power plant DCS software defects that obey a non-homogeneous Poisson process, to construct a non-homogeneous Poisson process model. The formulas for software reliability indicators such as total failures, remaining failures, failure rate (failures per week), reliability, and time to next failure(s) are derived. The software failure data obtained from the test are used to determine the variables of the model based on maximum likelihood estimation; the estimates are then used to quantitatively evaluate software reliability-related indicators. Finally, the minimum correlation error method is used to analyse the error by comparing the actual and model prediction results. The model can evaluate the current reliability level of software and predict the impact of subsequent reliability test results. The findings from this study can provide data support for evaluating the reliability of nuclear power plant DCS software. Therefore, this study can be significant for further research on the reliability of nuclear power plant DCS software.
ISSN:0306-4549
1873-2100
DOI:10.1016/j.anucene.2020.107589