Reliability analysis in the design of safe nuclear power plants

1989 ◽  
Vol 327 (1596) ◽  
pp. 549-564
Keyword(s):  
Reliability Analysis ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
High Reliability ◽  
Fault Tree Analysis ◽  
Statistical Techniques ◽  
Engineering Systems ◽  
Equipment Reliability ◽  
Fundamental Part

The requirement for all potentially hazardous plant is to achieve high reliability of engineering systems by design . The process of reliability analysis is a fundamental part of the design process in the nuclear power industry. Such analysis recognizes that there is always some possibility of engineering equipment failing and therefore the ability of the plant to be reasonably tolerant of such failures is investigated. In this paper the methods and philosophy underlying reliability analysis are briefly explained with examples of qualitative techniques such as failure modes and effects analysis, and fault tree analysis. In addition some of the quantitative models of equipment reliability are discussed and the need for robust statistical techniques for data analysis explained.

Application of Monte Carlo Methods in Reactor Protection System Reliability Research

2018 ◽  
Author(s):  
Duo Li ◽  
Zhaojun Hao ◽  
Shuqiao Zhou ◽  
Chao Guo
Keyword(s):  
Monte Carlo ◽  
Reliability Analysis ◽  
Monte Carlo Methods ◽  
Nuclear Power ◽  
Power Plants ◽  
Fault Tree Analysis ◽  
Engineering Application ◽  
Protection System ◽  
System States ◽  
Reactor Protection System

Digital Reactor Protection System (RPS) is one of the most important systems in instrumentation and control systems of Nuclear Power Plants (NPP). The reliability analysis of RPS plays an important role both in theory and engineering application. Traditional reliability methods, such as fault tree analysis and Markov chain theory, have many limitations in the research of RPS reliability, since the number of system states increases exponentially with the growth of system complexity. Aiming at the reliability analysis of complex system like RPS, the Monte Carlo method simulates the system behaviors and obtains the reliability calculations through a large number of simulations. This paper takes a preliminary research of RPS reliability based on Monte Carlo Methods, including static reliability analysis based on Monte Carlo simulation of the behavior of every equipment in the RPS, and dynamic characters of the RPS based on the simulation of RPS period tests.

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.

Operating Reliability Assessment of FPGA-Based NPP I&C Systems: Approach, Technique and Implementation

2017 ◽  
Author(s):  
Eugene Babeshko ◽  
Ievgenii Bakhmach ◽  
Vyacheslav Kharchenko ◽  
Eugene Ruchkov ◽  
Oleksandr Siora
Keyword(s):  
Integrated Circuits ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
New Technologies ◽  
Systems Approach ◽  
Reliability Assessment ◽  
Design Stage ◽  
Fpga Design ◽  
Operating Reliability

Operating reliability assessment of instrumentation and control systems (I&Cs) is always one of the most important activities, especially for critical domains like nuclear power plants (NPPs). Intensive use of relatively new technologies like field programmable gate arrays (FPGAs) in I&C which appear in upgrades and in newly built NPPs makes task to develop and validate advanced operating reliability assessment methods that consider specific technology features very topical. Increased integration densities make the reliability of integrated circuits the most crucial point in modern NPP I&Cs. Moreover, FPGAs differ in some significant ways from other integrated circuits: they are shipped as blanks and are very dependent on design configured into them. Furthermore, FPGA design could be changed during planned NPP outage for different reasons. Considering all possible failure modes of FPGA-based NPP I&C at design stage is a quite challenging task. Therefore, operating reliability assessment is one of the most preferable ways to perform comprehensive analysis of FPGA-based NPP I&Cs. This paper summarizes our experience on operating reliability analysis of FPGA based NPP I&Cs.

Digital I&C Operating Experience in the US

2008 ◽  
Author(s):  
Bruce Geddes ◽  
Ray Torok
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Failure Modes ◽  
Operating Experience ◽  
Data Set ◽  
Common Cause ◽  
Hardware Failure ◽  
Common Cause Failure ◽  
Defensive Measures

The Electric Power Research Institute (EPRI) is conducting research in cooperation with the Nuclear Energy Institute (NEI) regarding Operating Experience of digital Instrumentation and Control (I&C) systems in US nuclear power plants. The primary objective of this work is to extract insights from US nuclear power plant Operating Experience (OE) reports that can be applied to improve Diversity and Defense in Depth (D3) evaluations and methods for protecting nuclear plants against I&C related Common Cause Failures (CCF) that could disable safety functions and thereby degrade plant safety. Between 1987 and 2007, over 500 OE events involving digital equipment in US nuclear power plants were reported through various channels. OE reports for 324 of these events were found in databases maintained by the Nuclear Regulatory Commission (NRC) and the Institute of Nuclear Power Operations (INPO). A database was prepared for capturing the characteristics of each of the 324 events in terms of when, where, how, and why the event occurred, what steps were taken to correct the deficiency that caused the event, and what defensive measures could have been employed to prevent recurrence of these events. The database also captures the plant system type, its safety classification, and whether or not the event involved a common cause failure. This work has revealed the following results and insights: - 82 of the 324 “digital” events did not actually involve a digital failure. Of these 82 non-digital events, 34 might have been prevented by making full use of digital system fault tolerance features. - 242 of the 324 events did involve failures in digital systems. The leading contributors to the 242 digital failures were hardware failure modes. Software change appears as a corrective action twice as often as it appears as an event root cause. This suggests that software features are being added to avoid recurrence of hardware failures, and that adequately designed software is a strong defensive measure against hardware failure modes, preventing them from propagating into system failures and ultimately plant events. 54 of the 242 digital failures involved a Common Cause Failure (CCF). - 13 of the 54 CCF events affected safety (1E) systems, and only 2 of those were due to Inadequate Software Design. This finding suggests that software related CCFs on 1E systems are no more prevalent than other CCF mechanisms for which adherence to various regulations and standards is considered to provide adequate protection against CCF. This research provides an extensive data set that is being used to investigate many different questions related to failure modes, causes, corrective actions, and other event attributes that can be compared and contrasted to reveal useful insights. Specific considerations in this study included comparison of 1E vs. non-1E systems, active vs. potential CCFs, and possible defensive measures to prevent these events. This paper documents the dominant attributes of the evaluated events and the associated insights that can be used to improve methods for protecting against digital I&C related CCFs, applying a test of reasonable assurance.

Performance Evaluation of Japanese Nuclear Power Plant Based on Open Data and Information (3)

2010 ◽  
Author(s):  
Tadahisa Nagata ◽  
Ken-ichiro Sugiyama
Keyword(s):  
Renewal Process ◽  
Calculation Method ◽  
Nuclear Power ◽  
Power Plants ◽  
Failure Modes ◽  
Continuous Data ◽  
Weibull Analysis ◽  
Improved Method ◽  
Early Failure ◽  
Restoration Process

The excessive maintenance of the nuclear power plants (NPPs) may cause the early (infant) failure in Japan. An easy analysis; the Weibull analysis was applied to the evaluation of the failure mode. The Weibull analysis needs the hazard data. The maintenance information of the equipment which caused plant shutdown was required for the hazard calculation. However, maintenance information of the equipment was not open. Therefore, all equipment was assumed to be maintained during every shutdown. This assumption was based on renewal process. However, a repair after unplanned shutdown of NPP is generally a restoration of only failed function without system overhaul. The system must be considered to age continuously. The system was not renewed. The operation data must be regarded as one continuous data before and after unplanned shutdown. An improvement of the Weibull analysis was required for NPPs. The model of the Weibull analysis was investigated. The competitive model in which shutdown caused by other than focused equipment/cause may be supposed to be continuous data could not be applied for a comprehensive analysis. Furthermore, the calculation method of the Weibull analysis was investigated. The calculation method of the hazard was viewed. A denominator of the hazard is the number of data which is cut for every continuous data by renewal process. However, multiple considerations of operation periods before unplanned shutdowns might cause underestimation of the failure rate in case of restoration process. Therefore, a dominator of the hazard was not supposed to be the number of data but the number of survived equipments (plants) at each time according to the definition of the hazard. This improved method is for the restoration process. The performance of Japanese NPPs was evaluated by improved method. The failure modes of Japanese NPPs were early failure modes. Moreover, performances of U.S. NPPs was tried to be evaluated by improved method. Operation data was collected from “NRC Power Reactor Status Reports”. However, many “maintenance outage”s which are the shutdowns of unknown origin were found. Therefore, DOE information was supplemented to investigate the “maintenance outage”. Failure modes of U.S. NPPs were the early failure modes, and failure rates were larger than Japanese NPPs.

Reliability Monitor for PWR Safety System Using FMEA and Go-Flow Methodology: Application of Risk Monitor for Nuclear Power Plants

2013 ◽  
Author(s):  
Muhammad Hashim ◽  
Hidekazu Yoshikawa ◽  
Takeshi Matsuoka ◽  
Ming Yang
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Fault Tree Analysis ◽  
Reliability Evaluation ◽  
Safety System ◽  
Severe Accident ◽  
Monitor System ◽  
Dynamic Reliability ◽  
Defense In Depth ◽  
Risk Monitor

Author’s proposed risk monitor system of Nuclear Power Plant (NPP) is based on the idea of Plant Defense-in-Depth (DiD) risk monitor and reliability monitor to monitor what degree of safety functions incorporated in the plant system is maintained by multiple barriers of Defense-in-Depth (DiD). In the risk monitor system, the range of risk state is not limited in core damage accident but includes all kinds of dangerous states brought by severe accident. In present study, method of the reliability monitor of a risk monitor system is applied to the PWR safety system in order to evaluate the risk state numerically by pursuing all conditions of reliability evaluation given by plant DiD risk monitor. Large break LOCA is taken as an initiating accident event and the implementation of method of the reliability monitor is discussed in detail for single loop PWR safety system by considering the Multilevel Flow Model (MFM), Failure Mode and Effect Analysis (FMEA), and the qualitative reliability evaluation by Fault Tree Analysis (FTA) and the dynamic reliability evaluation by GO-FLOW. The summary of reliability results of PWR safety subsystems are also presented.

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