Markov/CCMT Dynamic Reliability Analysis of the Main and Startup Feedwater Control System in Nuclear Power Plant

2018 ◽  
Vol 4 (4) ◽  
Author(s):  
Wentao Li ◽  
Danying Gu ◽  
Henan Zhang
Keyword(s):  
Control System ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Reliability Analysis ◽  
Nuclear Power ◽  
Failure Modes ◽  
Engineering Application ◽  
Dynamic Reliability ◽  
Mapping Technology ◽  
Cut Set

The dynamic reliability of the main and startup feedwater control system in nuclear power plant is evaluated by conducting the Markov cell-to-cell mapping technology (Markov/CCMT) methodology. All the equipment failure modes and potential failure states within the system are analyzed. This process illustrates the uncertainty in the physical process of the system. Furthermore, the failure probability and cut-set of the system can be computed to provide a more comprehensive and accurate response to the system characteristics and reflect the two types of interaction within the system. In contrast to the traditional static probability safety assessment, the Markov/CCMT methodology remedies the defect in terms of event sequence setting, control loop, multiple top event competition, uncertainty of the analysis result, as well as the insufficient analysis of human-caused failure. The reliability analysis of the main and startup feedwater control system (FWCS) based on the self-developed Markov/CCMT reliability analysis software verifies the feasibility and engineering application value of the methodology and software.

Markov/CCMT Dynamic Reliability Analysis of the Main and Startup Feedwater Control System in Nuclear Power Plant

2017 ◽  
Author(s):  
Wentao Li ◽  
Danying Gu ◽  
Henan Zhang
Keyword(s):  
Control System ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Reliability Analysis ◽  
Nuclear Power ◽  
Failure Modes ◽  
Engineering Application ◽  
Dynamic Reliability ◽  
Mapping Technology ◽  
Cut Set

The dynamic reliability of the main and startup feedwater control system in nuclear power plant is evaluated by conducting the Markov Cell-to-Cell Mapping Technology (Markov/CCMT) methodology. All the equipment failure modes and potential failure states within the system are analyzed. This process illustrates the uncertainty in the physical process of the system. Furthermore, the failure probability and cut-set of the system can be computed to provide a more comprehensive and accurate response to the system characteristics and reflect the two types of interaction within the system. In contract to the traditional static Probability Safety Assessment (PSA), the Markov/CCMT methodology remedies the defect in terms of event sequence setting, control loop, multiple top event competition, uncertainty of the analysis result as well as the insufficient analysis of human-caused failure. The reliability analysis of the main and startup feedwater control system (FWCS) based on the self-developed Markov/CCMT reliability analysis software verifies the feasibility and engineering application value of the methodology and software.

Reliability Analysis of the Automatic Control System of Reactor Power in Nuclear Power Plant Based on DFM

2016 ◽  
Author(s):  
Wang Hao ◽  
Tian Cong ◽  
Zhou Shiliang ◽  
Liu Yu Yuan ◽  
Shahroze Ahmad
Keyword(s):  
Control System ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Reliability Analysis ◽  
Nuclear Power ◽  
Boolean Logic ◽  
Type I ◽  
Type Ii ◽  
Sensor Failure ◽  
Sequence Of Events

Instrumentation and control (I&C) system is central nervous system of nuclear power plant (NPP), so its reliability is very important for the safety of NPP. Now Digital I&C system (DICS) is widely used in NPP, its reliability should be analyzed more carefully due to the more complex interaction among its components than analog I&C system. The interaction among DICS can be divided into type I and type II. The former is the interaction among sensor failure, controller failure and actuator failure, the latter is the interaction among hardware\software components of DICS. Limited by static Boolean logic, traditional fault tree is hard to model the dynamic interaction among DICS, so dynamic modelling method is required. In this paper, Dynamic flowgraph methodology (DFM) is used for reliability analysis of a subsystem of NPP DICS, namely APC (Automatic Power Control System). The proposed dynamic flowgraph modelled type I and type II interaction among APC and reliability of APC is assessed via inductive and deductive analysis. In the inductive analysis, three basic events (user defined combination of states) are considered, which includes sensor failure, SRB failure and master\checker processor failure, and the sequence of events caused by these basic events are tracked. In the deductive analysis, top event (combinations of possible system parameters and/or component states) is defined as actual control rod position is lower than demanded, and four combinations of basic events are tracked according to occurrence probability of their corresponding event.

Sensitivity Analysis for Human Errors of a Chemical and Volume Control System at Nuclear Power Plant by Soft Control

2017 ◽  
Author(s):  
Zhang Yuxin ◽  
Yang Kunze
Keyword(s):  
Control System ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
Sensitivity Analyses ◽  
Volume Control ◽  
Pressurized Water ◽  
Human Errors

The introduction of soft controls into the main control room may provide a more convenient environment for operations, but also may introduce new types of human errors and new risks into the nuclear power plants. In this paper, taking the Chemical and Volume Control System (CVCS) at pressurized water reactor nuclear power plant as an example, the task analysis of operating procedures for starting the CVCS under a normal shut-down operation condition, the potential failure modes during operators executing each step of operating procedures and the dependency analysis of sub-tasks are presented. Furthermore, the sensitivity analyses are conducted for identifying probability importance and critical importance of each model parameter. The countermeasures for preventing and reducing the human errors of soft controls are discussed.

Human reliability in non-destructive inspections of nuclear power plant components: modeling and analysis

2019 ◽  
Vol 7 (2B) ◽  
Author(s):  
Vanderley Vasconcelos ◽  
Wellington Antonio Soares ◽  
Raissa Oliveira Marques ◽  
Silvério Ferreira Silva Jr ◽  
Amanda Laureano Raso
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Human Factors ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
Cooling System ◽  
Human Reliability ◽  
Non Destructive ◽  
Plant Components

Non-destructive inspection (NDI) is one of the key elements in ensuring quality of engineering systems and their safe use. This inspection is a very complex task, during which the inspectors have to rely on their sensory, perceptual, cognitive, and motor skills. It requires high vigilance once it is often carried out on large components, over a long period of time, and in hostile environments and restriction of workplace. A successful NDI requires careful planning, choice of appropriate NDI methods and inspection procedures, as well as qualified and trained inspection personnel. A failure of NDI to detect critical defects in safety-related components of nuclear power plants, for instance, may lead to catastrophic consequences for workers, public and environment. Therefore, ensuring that NDI is reliable and capable of detecting all critical defects is of utmost importance. Despite increased use of automation in NDI, human inspectors, and thus human factors, still play an important role in NDI reliability. Human reliability is the probability of humans conducting specific tasks with satisfactory performance. Many techniques are suitable for modeling and analyzing human reliability in NDI of nuclear power plant components, such as FMEA (Failure Modes and Effects Analysis) and THERP (Technique for Human Error Rate Prediction). An example by using qualitative and quantitative assessesments with these two techniques to improve typical NDI of pipe segments of a core cooling system of a nuclear power plant, through acting on human factors issues, is presented.

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