Research and Application to Risk-Informed NPP Events Trend Analysis Method

2017 ◽  
Author(s):  
Chen Shijun ◽  
Zhang Sifan ◽  
Chen Peifeng ◽  
Zhang Kuan
Keyword(s):  
Trend Analysis ◽  
Nuclear Power ◽  
Power Plants ◽  
Event Analysis ◽  
Analysis Method ◽  
Common Cause ◽  
Analysis Techniques ◽  
Analysis Process ◽  
The Common ◽  
Safety Operation

The method of the event trend analysis is a so-called analyzed process that will begin with a statistics on a certain characteristic for a set of events over a period of time, and then identify and analyze its variation trend and the reason for its existence so as to develop the corresponding corrective actions. this paper combined with both the traditional event trend analysis and probabilistic safety analysis methods, develops a set of risk-informed trend analysis techniques applicable to the domestic NPPs. This method aims to highlight the significance of the events by placing larger weight on the abnormal incidents of high risk significance, and use the strategy of level management to control the common cause events so that the plant will keep a watchful eye on and give priority to eliminate these events. In addition, this paper also provides an application case to illustrate the practical use of this method. It is shown that some plants have already obtained several benefits through adopting this method into their event analysis programs. In reality, it will benefit the application of this method into subsequent NPPs event trend analysis process and provide reference and assistance for the safety operation of the nuclear power plants.

Common cause failure model updating for risk monitoring in nuclear power plants based on alpha factor model

2017 ◽  
Vol 231 (3) ◽  
pp. 209-220 ◽  
Author(s):  
Min Zhang ◽  
Zhijian Zhang ◽  
Ali Mosleh ◽  
Sijuan Chen
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Model Updating ◽  
Factor Model ◽  
Failure Model ◽  
Common Cause ◽  
Common Cause Failure ◽  
Risk Monitoring ◽  
Common Cause Failures ◽  
The Common

Common cause failure model updating (both qualitatively and quantitatively) is a key factor in risk monitoring for nuclear power plants when configuration changes (e.g. components become unavailable) occur among a redundant configuration. This research focuses on the common cause failure updating based on the alpha factor model method, which is commonly used in the living probabilistic safety assessment models for nuclear power plant risk monitoring. This article first discusses the common cause failure model updating in an ideal condition, which evaluates the common cause failure model parameters for the configurationally changed system in different ways, based on the causes of the detected failures. Then, two alternative updating processes are proposed considering the difficulty to identify failure causes immediately during plant operation: one is to update the common cause failure models with the assumption that the failures detected are independent failures and the other is to update the common cause failure models with the parameters as expectations of the values for all possible failure causes. Finally, a case study is given to illustrate the common cause failure updating process and to compare these two alternative processes. The results show that (1) common cause failures can be reevaluated automatically by the methods proposed in this article and (2) the second process is more conservative and reasonable but with more data requirements compared with the first approach. Considering limitations in accessibility of the data, the first strategy is suggested currently. More future work on data acquisition is demanded for better assessment of common cause failures during nuclear power plant risk monitoring.

Inter-Unit Common Cause Failure Analysis Based on Data From Intra-Unit Cases

2020 ◽  
Author(s):  
Eishiro Higo ◽  
Shota Soga ◽  
Hiromichi Miura
Keyword(s):  
Failure Analysis ◽  
Nuclear Power ◽  
Power Plants ◽  
Analysis Method ◽  
Common Cause ◽  
Common Cause Failure ◽  
Coupling Factors ◽  
A Site ◽  
Multiple Units ◽  
Degree Of Similarity

Abstract This study provides an inter-unit common cause failure (CCF) analysis method utilizing the international CCF database. The inter-unit CCF is one of the possible major risks at a site with multiple units. The conventional CCF analysis is based on the CCF database, in which inter-unit CCF events rarely occur in real nuclear power plants. The conventional approach cannot be directly applied to inter-unit CCF cases because of the lack of data. The method ignores the asymmetricity among units, so it may lead to overly conservative outcomes if it is applied to inter-unit CCF. We have proposed a new concept, “commonality factor,” which represents the degree of similarity among components in different units and showed a concept that the inter-unit CCF probability can be expressed in terms of the intra-unit CCF probability with the commonality factor. The commonality factor is approximated based on CCF coupling factors, which tie two or more failures together as a CCF. This study explains how to estimate the commonality factor by analyzing the conventional CCF database and judging commonality among components from different units. The proposed method is demonstrated through two preliminary examples.

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.

Effective Software Verification and Validation Approach for Nuclear Power Plant Digital Instrumentation and Control Systems

2010 ◽  
Author(s):  
Steve Yang ◽  
Jun Ding ◽  
Huifang Miao ◽  
Jianxiang Zheng
Keyword(s):  
Life Cycle ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Software Verification ◽  
Verification And Validation ◽  
Common Cause ◽  
Digital Instrumentation ◽  
And Control ◽  
Software Verification And Validation

All 1000 MW nuclear power plants currently in construction or projected to-be-built in China will use the digital instrumentation and control (I&C) systems. Safety and reliability are the ultimate concern for the digital I&C systems. To obtain high confidence in the safety of digital I&C systems, rigorous software verification and validation (V&V) life-cycle methodologies are necessary. The V&V life-cycle process ensures that the requirements of the system and software are correct, complete, and traceable; that the requirements at the end of each life-cycle phase fulfill the requirements imposed by the previous phase; and the final product meets the user-specified requirements. The V&V process is best illustrated via the so-called V-model. This paper describes the V-model in detail by some examples. Through the examples demonstration, it is shown that the process detailed in the V-model is consistent with the IEEE Std 1012-1998, which is endorsed by the US Regulatory Guide 1.168-2004. The examples show that the V-model process detailed in this paper provides an effective V&V approach for digital I&C systems used in nuclear power plants. Additionally, in order to obtain a qualitative mathematical description of the V-model, we study its topological structure in graph theory. This study confirms the rationality of the V-model. Finally, the V&V approach affording protection against common-cause failure from design deficiencies, and manufacturing errors is explored. We conclude that rigorous V&V activities using the V-model are creditable in reducing the risk of common-cause failures.

Research of Ageing and Life Assessment Methods of Power Transformers in Nuclear Power Plants

2012 ◽  
Vol 614-615 ◽  
pp. 1109-1115 ◽  
Author(s):  
Cheng Feng Yang
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Assessment Method ◽  
Thermal Ageing ◽  
Degree Of Polymerization ◽  
Transformer Oil ◽  
Life Assessment ◽  
Power Transformers ◽  
Analysis Method

The effective methods of the ageing and life assessment for large and medium-sized power transformers used in nuclear power plants are analyzed and described, including the thermal ageing life assessment method for transformer solid insulation, the gas analysis method of CO and CO2 in the transformer oil, the average degree of polymerization method, furfural content analysis method, and the analysis method based on the insulation ageing-related electrical parameters. The analysis results show that the methods used can reasonably assess the remaining life of the transformers. These methods have important reference value to the ageing and life management for the large and medium-sized power transformers in nuclear power plants.

Nonlinear analysis techniques of block masonry walls in nuclear power plants

1986 ◽  
Vol 91 (1) ◽  
pp. 13-16
Author(s):  
Ahmad A. Hamid ◽  
Harry G. Harris ◽  
Vu N. Con ◽  
Nilesh C. Chokshi
Keyword(s):  
Nonlinear Analysis ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Masonry Walls ◽  
Analysis Techniques

The Autoignition of Nuclear Reactor Power Plant Explosions

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Robert A. Leishear
Keyword(s):  
Power Plant ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Reactor ◽  
Nuclear Reactions ◽  
High Energy ◽  
Reactor Power ◽  
Common Cause ◽  
Fluid Transients ◽  
Accident Conditions

Abstract Explosive research proves that there is a common cause for most explosions in nuclear reactor power plants during normal operations and accident conditions. The autoignition of flammable hydrogen is a common cause for nuclear power plant explosions, where complex corrosion processes, nuclear reactions, and thermal-fluid transients autoignite explosions. Research evaluated increasingly complicated accidents. First, piping explosions occurred at Hamaoka and Brunsbuttel. Fluid transients compressed oxygen and flammable hydrogen to heat these gases to autoignition, where resultant explosions shredded steel pipes. This identical mechanism was responsible for pipe and pump damages to U.S. reactor systems since the 1950s, where water hammer alone has been assumed to cause damages. Small explosions inside the piping actually cause damages during nuclear reactor startups and flow rate changes. Second, explosions are caused by thermal-fluid transients during nuclear reactor restarts, following accidental nuclear reactor meltdowns. Disastrous explosions destroyed nuclear reactor buildings (RBs) at Fukushima Daiichi. Previously considered to be a fire, a 319 kilogram hydrogen explosion occurred at Three Mile Island (TMI). The explosion cause following each of these loss-of-coolant accidents was identical, i.e., after meltdowns, pump operations heated gases, which in turn acted as the heat source to autoignite sequential hydrogen explosions in reactor systems to ignite RBs. Third, the Chernobyl explosion followed a reactor meltdown that was complicated by a high energy nuclear criticality. The hydrogen ignition and explosion causes are more complicated as well, where two sequential hydrogen explosions were ignited by high-temperature reactor fuel.

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