PSA model with consideration of the effect of fault-tolerant techniques in digital I&amp;C systems

Lee, Seung Jun; Jung, Woo‐Sik; Yang, Joon-Eon

doi:10.1016/j.anucene.2015.07.039

Cited by 12 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…But in fact, DCS failure and maintenance process do not fully obey the exponential distribution. In addition, with the increase of the number of components, the number of state space of Markov model increases exponentially, and the model becomes extremely large, leading to the difficulty of calculation [8].The NUREG/CR-6901 report compared analogue and digital I&C systems and described the problems that need to be solved by modelling the reliability of digital I&C systems and embedding the reliability of digital I&C systems into the existing PRA model in order to increase the contribution of digital I&C systems to power plant risk informed decision making [9].This report summarized the reliability modelling methods of digital systems, and the comparison results of various methods show that none of the reliability modelling methods can completely meet the reliability modeling requirements of digital systems [10][11][12][13][14]. Guo of Tsinghua University used a variety of methods to analyze the reliability of digital I&C systems in NPPs, including failure mode and effects analysis (FMEA), failure tree method (FT), dynamic flow graph mode (DFM) and Markov/CCMT (Cell-to-Cell Mapping Technique) to analyze the digital I&C systems.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Reliability Analysis of DCS in HTR-PM Considering Fault Self-Check Rate Based on Petri Net

2022

Proceedings of WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications

View full text Add to dashboard Cite

Digital distributed control system (DCS) is the most important monitoring and control platform in a nuclear power plant (NPP). The reliability and availability modeling and analysis of digital DCS are of great significance to ensure the stable and reliable operation of NPPs and to improve the economy of NPPs. With the continuous development of control system technology, the fault self-check rate of DCS equipment is getting higher and higher. It is necessary to consider the influence of this factor in the DCS reliability model and improve the model architecture. In this paper, a dynamic reliability model of DCS based on Petri Net is proposed by considering the factor of fault self-check rate. The DCS of High Temperature Gas-Cooled Reactor -Pebble bed Module (HTR-PM) was adopted for model verification, and the reliability of the DCS was calculated by Monte Carlo method. The calculation results show that the higher the fault self-check rate, the lower the unavailability of the DCS. When the fault self-check rate exceeds 40%, the unavailability of DCS will be reduced by an order of magnitude. This conclusion has important engineering practical significance.

show abstract

Section: Introductionmentioning

confidence: 99%

Dynamic Reliability Analysis of DCS in HTR-PM Considering Fault Self-Check Rate Based on Petri Net

2022

Proceedings of WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications

View full text Add to dashboard Cite

show abstract

“…Furthermore, the application of a dynamic method needs substantial effort and the method generally suffers from the incompatibility with the existing PSA framework. On this viewpoint, the ET/FT method that has a mature theory and is easy-to-use got much attention and had been used in research about reliability assessments of digital systems in NPPs and yielded satisfactory results [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Reliability Assessment for a Safety-Related Digital Reactor Protection System Using Event-Tree/Fault-Tree (ET/FT) Method

Liang

Liu

Xiao

et al. 2020

Science and Technology of Nuclear Installations

View full text Add to dashboard Cite

The aim of this study is to verify if the reliability of a digital four-channel RPS under the design phase satisfies the specified target and to identify the weakness of system design and potential solutions for system reliability improvement. The event-tree/fault-tree (ET/FT), which is the method used in the current probabilistic safety assessment (PSA) framework of nuclear power plants (NPPs), was adopted to developed reliability modeling for the RPS with the Top Events defined as the system failure to generate reactor trip signal and the system generating spurious trip signal. The evaluation results indicate that the probability of the system failure on demand and the frequency of spurious trip signal generation are 1.47 × 10−6 with a 95% upper bound of 4.63 × 10−6 and 7.94 × 10−4/year with a 95% upper bound of 2.50 × 10−3/year, respectively. The importance and sensitivity analyses were conducted and it was found that undetected unsafe common cause failures (CCFs) of signal conditioning modules (SCMs) dominate the system reliability. Two preliminary optimization schemes relative to reducing periodic test interval and adapting two kinds of diverse SCMs were proposed. Results of the quantitive evaluation of the schemes show that neither of them could determinedly improve the system reliability to the target level. In the future, more detailed optimization analysis shall be required to determine a feasible system design optimization scheme.

show abstract

“…To model common failure causes between components in digital systems, traditional probabilistic safety assessments (PSA) methods have been presented by the U.S. Nuclear Regulatory Commission (NRC) (Chu, Martinez-Guridi, Yeu, Lehner, and Samanta, 2008). The PSA methods have been applied to model reliability of the digital system of feedwater control systems (Chu, Yeu, Martinez-Guridi, Mernick, Lehner, and Kuritzky, 2009) and nuclear safety-related digital instrumentation and control systems (Shi, Enzinna, Yang, and Blodgett, 2010, Authen and Holmberg, 2012, Bjorkman, Lahtinen, Tyrvainen, and Holmberg, 2015, Lee, Jung, and Yang, 2016. In addition to the conventional approaches to model reliability, prognosis of DIO modules is emerging to predict the reliability of complex automation systems accurately based on systems' conditions.…”

Section: Introductionmentioning

confidence: 99%

Lifetime Prediction of Optocouplers in Digital Input and Output Modules based on Bayesian tracking approaches

Shin,

Kwon

2017

PHMAP_CONF

View full text Add to dashboard Cite

In recent years, reliability of DIO modules has been drawing much attention from manufacturing companies under the growing complexity of automation systems for smart factory establishment. In manufacturing systems, DIO modules have been widely used to pass sensor measurements and configuration input signals for controlling actuators. Because sensor measurement and control signals pass through DIO modules, the faults of DIO modules would cause malfunctions or failures of the smart manufacturing systems and eventually lead to unexpected downtime in the manufacturing process. For predictive maintenance of DIO modules, this paper proposes a method of predicting the remaining useful life of a critical component in DIO modules based on the Bayesian tracking approaches. Optocouplers are one of the critical components in DIO modules that uses a short optical transmission path including light sources and photo-sensors to transfer an electrical signal. The performance of optocouplers may be degraded overtime with damages in a light source or a photo-sensor and eventually cause the faults of control systems. Extended Kalman Filter and Particle Filter are used in nonlinear degradation modeling to predict the lifetime of optocouplers, evaluating those filters by accuracy-based prognostic metrics and showing the effectiveness of Bayesian tracking approaches for lifetime prediction of optocouplers.

show abstract

PSA model with consideration of the effect of fault-tolerant techniques in digital I&C systems

Cited by 12 publications

References 9 publications

Dynamic Reliability Analysis of DCS in HTR-PM Considering Fault Self-Check Rate Based on Petri Net

Dynamic Reliability Analysis of DCS in HTR-PM Considering Fault Self-Check Rate Based on Petri Net

Reliability Assessment for a Safety-Related Digital Reactor Protection System Using Event-Tree/Fault-Tree (ET/FT) Method

Lifetime Prediction of Optocouplers in Digital Input and Output Modules based on Bayesian tracking approaches

Contact Info

Product

Resources

About