Issues related to structural aging in probabilistic risk assessment of nuclear power plants

Structural components and systems have an important safety function in nuclear power plants. Although they are essentially passive under normal operating conditions, they play a key role in mitigating the impact of extreme environmental events such as earthquakes, winds, fire and floods on plant safety. Moreover, the importance of structural components and systems in accident mitigation is amplified by common-cause effects. Reinforced concrete structural components and systems in NPPs are subject to a phenomenon known as aging, leading to time-dependent changes in strength and stiffness that may impact their ability to withstand various challenges during their service lives from operation, the environment and accidents. Time-dependent changes in structural properties as well as challenges to the system are random in nature. Accordingly, condition assessment of existing structures should be performed within a probabilistic framework. The mathematical formalism of a probabilistic risk assessment (PRA) provides a means for identifying aging structural components that may play a significant role in mitigating plant risk. Structural condition assessments supporting a decision regarding continued service can be rendered more efficient if guided by the logic of a PRA.     

Seismic PSA method for multiple nuclear power plants in a site

The maximum number of nuclear power plants in a site is eight and about 50% of power plants are built in sites with three or more plants in the world. Such nuclear sites have potential risks of simultaneous multiple plant damages especially at external events. Seismic probabilistic safety assessment method (Level-1 PSA) for multi-unit sites with up to 9 units has been developed. The models include Fault-tree linked Monte Carlo computation, taking into consideration multivariate correlations of components and systems from partial to complete, inside and across units. The models were programmed as a computer program CORAL reef. Sample analysis and sensitivity studies were performed to verify the models and algorithms and to understand some of risk insights and risk metrics, such as site core damage frequency (CDF per site-year) for multiple reactor plants. This study will contribute to realistic state of art seismic PSA, taking consideration of multiple reactor power plants, and to enhancement of seismic safety.     

A remark on data for defects used in probabilistic analyses of failure of nuclear pressure vessels

In a fracture mechanical probabilistic analysis of the failure of nuclear pressure vessels, data are needed for the presence of defects that may have escaped detection during non-destructive examination. At present such statistical data can be obtained only by subjective estimates. A review has been made of the data on the effectiveness of defect detection on which the most widely cited probabilistic analysis of the safety of nuclear pressure vessels has been based. It seems justified to use considerably lower values for effectiveness. Correspondingly, the calculated probabilities for failure of nuclear pressure vessels should be raised. Consequently, this type of failure would become of greater concern than presently assumed considering the risks associated with nuclear power plants.     

A historical overview of probabilistic risk assessment development and its use in the nuclear power industry: a tribute to the late Professor Norman Carl Rasmussen

This paper reviews the historical development of the probabilistic risk assessment (PRA) methods and applications in the nuclear industry. A review of nuclear safety and regulatory developments in the early days of nuclear power in the United States has been presented. It is argued that due to technical difficulties for measuring and characterizing uncertainties and concerns over legal challenges, safety design and regulation of nuclear power plants has primarily relied upon conservative safety assessment methods derived based on a set of design and safety principles. Further, it is noted that the conservatism adopted in safety and design assessments has allowed the use of deterministic performance assessment methods. This approach worked successfully in the early years of nuclear power epoch as the reactor design proved to be safe enough. However, it has been observed that as the conservative approach to design and safety criteria proved arbitrary, and yielded inconsistencies in the degree to which different safety measures in nuclear power plants protect safety and public heath, the urge for a more consistent assessment of safety became apparent in the late 1960s. In the early 1970s, as a result of public and political pressures, then the US Atomic Energy Commission initiated a new look at the safety of the nuclear power plants through a comprehensive study called ‘Reactor Safety Study’ (WASH-1400, or ‘Rasmussen Study’—after its charismatic study leader Professor Norman Rasmussen of MIT) to demonstrate safety of the nuclear power plants. Completed in October 1975, this landmark study introduced a novel probabilistic, systematic and holistic approach to the assessment of safety, which ultimately resulted in a sweeping paradigm shift in safety design and regulation of nuclear power in the United States in the turn of the Century. Technical issues of historic significance and concerns raised by the subsequent reviews of the Rasmussen Study have been discussed. Effect of major events and developments such as the Three Mile Island accident and the Nuclear Regulatory Commission and the Nuclear Industry sponsored studies on the tools, techniques and applications of the PRA that culminated in the present day risk-informed initiatives has been discussed.     

Probabilitically based decision support

Probabilistic Safety Assessment, usually referred to by the acronym PSA, has by now become a recognized tool for safety analysis of nuclear power plants. In recent years, an increasing number of plants have been analysed, and as the technique has matured, the area of application of PSA based analyses has been expanded. Thus, probabilistic methods are now used increasingly in the day-to-day work concerning the safety, maintenance and operation of plants. In this context, the question of interpretation and application of analysis results in various decision situations has become crucial. This paper gives some comments concerning the basis for decision making involving probabilistic analyses.     

Seismic probabilistic risk assessment and seismic margins studies for nuclear power plants

This paper reviews the seismic probabilistic risk assessment and seismic margins studies for nuclear power plants in the United States. The techniques employed in these studies are briefly described. A few comments on the evaluation of the fragility of structures and equipment are discussed. Seismic PRA is a systematic process to evaluate the safety of nuclear power plants. In the process, it integrates all the elements such as seismic hazard, component fragility and plant system. Thus, it provides the overall view of the safety of an entire plant under a seismic event.

The major tasks of a seismic PRA such as the evaluation of hazard curves, component fragility and plant system are also present in probabilistic analyses of nonnuclear facilities. The concept and technique embodied in seismic PRA for nuclear power plants can be applied to other types of engineering facilities.     

Development of a dynamical systems model of plant programmatic performance on nuclear power plant safety risk

Application of probabilistic risk assessment (PRA) techniques to model nuclear power plant accident sequences has provided a significant contribution to understanding the potential initiating events, equipment failures and operator errors that can lead to core damage accidents. Application of the lessons learned from these analyses has resulted in significant improvements in plant operation and safety. However, this approach has not been nearly as successful in addressing the impact of plant processes and management effectiveness on the risks of plant operation. The research described in this paper presents an alternative approach to addressing this issue. In this paper we propose a dynamical systems model that describes the interaction of important plant processes on nuclear safety risk. We discuss development of the mathematical model including the identification and interpretation of significant inter-process interactions. Next, we review the techniques applicable to analysis of nonlinear dynamical systems that are utilized in the characterization of the model. This is followed by a preliminary analysis of the model that demonstrates that its dynamical evolution displays features that have been observed at commercially operating plants. From this analysis, several significant insights are presented with respect to the effective control of nuclear safety risk. As an important example, analysis of the model dynamics indicates that significant benefits in effectively managing risk are obtained by integrating the plant operation and work management processes such that decisions are made utilizing a multidisciplinary and collaborative approach. We note that although the model was developed specifically to be applicable to nuclear power plants, many of the insights and conclusions obtained are likely applicable to other process industries.     

A Bayesian approach to modeling and predicting pitting flaws in steam generator tubes

Steam generators in nuclear power plants have experienced varying degrees of under-deposit pitting corrosion. A probabilistic model to accurately predict pitting damage is necessary for effective life-cycle management of steam generators. This paper presents an advanced probabilistic model of pitting corrosion characterizing the inherent randomness of the pitting process and measurement uncertainties of the in-service inspection (ISI) data obtained from eddy current (EC) inspections. A Markov chain Monte Carlo simulation-based Bayesian method, enhanced by a data augmentation technique, is developed for estimating the model parameters. The proposed model is able to predict the actual pit number, the actual pit depth as well as the maximum pit depth, which is the main interest of the pitting corrosion model. The study also reveals the significance of inspection uncertainties in the modeling of pitting flaws using the ISI data: Without considering the probability-of-detection issues and measurement errors, the leakage risk resulted from the pitting corrosion would be under-estimated, despite the fact that the actual pit depth would usually be over-estimated.     

Historical perspective on failure rates for US commercial reactor components

To support the development of probabilistic risk assessments of US commercial nuclear power plants, significant effort has been expended to develop generic failure rates for components. Generic failure rates indicate industry-average performance of components, rather than component performance at a specific plant. Most publicly available, generic failure rate databases are typically based on data collected in the 1970s and 1980s for US nuclear power plants. Recent data analysis programs sponsored by the US Nuclear Regulatory Commission and data collection programs sponsored by the Institute of Nuclear Power Operations provide an opportunity to compare more recent failure rate estimates with those obtained in the 1970s and 1980s. These recent results indicate that many component generic failure rates are now lower than observed in the 1970s and 1980s. Suggestions for up-to-date failure rates are presented. Also, failure to run rates for standby components are presented for both short- and longer-term run times.     

Current practices for risk zoning around nuclear power plants in comparison to other industry sectors

This paper analyses the background and current status of the information basis leading to the definition of risk and emergency zones around nuclear power plants (NPPs) in different countries in Europe and beyond. Although dependable plant-specific probabilistic safety assessment (PSA) of level 2 and/or level 3 could in principle provide sufficiently detailed input to define the geographical dimension of a NPP's risk and emergency zones, the analysis of the status in some European and other countries shows that other, "deterministic" approaches using a reference accident are actually used in practice. Regarding use of level 2 PSA for emergency planning, the approach so far has been to use the level 2 PSA information retrospectively to provide the justification for the choice of reference accident(s) used to define the emergency plans and emergency planning zones (EPZs). There are significant differences in the EPZs that are defined in different countries, ranging from a few up to 80km. There is a striking contrast in the extent of using probabilistic information to define emergency zones between the nuclear and other high risk industry sectors, such as the chemical process industry, and the reasons for these differences are not entirely clear, since the risk of chemical industry is similar as that of the nuclear sector. The differences seem to be more related to risk perception than to the actual risk potential. Therefore, there is a strong need to be able to communicate risk information to the Public both before and following an accident. In addition, there is a need to educate the Public so that they can understand risk information in a comparative sense. Finally, based on the consensus discussions at a recent JRC/OECD International Seminar on Risk and Emergency Zoning around NPPs, a set of recommendations is given in the areas of: -a more comprehensive use of the available risk information for risk zoning purposes, -risk communication; -comparative (energy) risk assessment.     

Calculating and addressing uncertainty for risk-based allowable outage times

This article examines the calculation and treatment of uncertainty in risk-based allowable outage times (AOTs) for operational control at nuclear power plants, where an AOT is defined as the time that a component or system is permitted to be out of service. The US Nuclear Regulatory Commission (NRC) has explored the possibility of using a nuclear power plant's probabilistic risk assessment results to determine component or system AOTs. The analysis and results from previous work prepared for the NRC on determining risk-based AOTs are presented. As part of the discussion, the article examines the inherent uncertainty in calculating risk-based AOTs and presents the difficulties in calculating these risk-based AOTs. It is noted that care should be taken when dealing with uncertainty analysis results where a time-interval is the outcome of the analysis. In addition, potential improvements in the mechanism of calculating risk-based AOTs are suggested.     

基于PSHA的核电厂近断层抗震设计谱构建方法

核电是一种高效、清洁的能源,随着核电厂未来向内陆区的发展,其可能会遭遇到近断层地震动的影响,但是目前我国核电厂抗震规范设计谱并未考虑近断层地震动。该文首先基于大量实际近断层脉冲型和相应无脉冲地震动记录,研究了脉冲对反应谱的放大效应,建立了修正的近断层脉冲放大系数模型;继而将地震动脉冲效应引入到近断层概率地震危险性分析中,并基于设定断层模型,给出了不同场地类型的一致危险性反应谱;通过对地震危险性结果的分解,分析了对场地最危险震级和距离,并将结果引入地震动衰减关系中得到设计谱,最后通过近断层脉冲放大系数对设计谱进行修正,得到考虑近断层脉冲效应的核电厂抗震设计谱。通过研究,建立了一种基于概率地震危险性分析框架下,考虑近断层脉冲型地震动的工程场地核电厂抗震设计谱的构建方法。     

Optimization of safety equipment outages improves safety

Testing and maintenance activities of safety equipment in nuclear power plants are an important potential for risk and cost reduction. An optimization method is presented based on the simulated annealing algorithm. The method determines the optimal schedule of safety equipment outages due to testing and maintenance based on minimization of selected risk measure. The mean value of the selected time dependent risk measure represents the objective function of the optimization. The time dependent function of the selected risk measure is obtained from probabilistic safety assessment, i.e. the fault tree analysis at the system level and the fault tree/event tree analysis at the plant level, both extended with inclusion of time requirements. Results of several examples showed that it is possible to reduce risk by application of the proposed method. Because of large uncertainties in the probabilistic safety assessment, the most important result of the method may not be a selection of the most suitable schedule of safety equipment outages among those, which results in similarly low risk. But, it may be a prevention of such schedules of safety equipment outages, which result in high risk. Such finding increases the importance of evaluation speed versus the requirement of getting always the global optimum no matter if it is only slightly better that certain local one.     

NAROAS: a neural network-based advanced operator support system for the assessment of systems reliability

We have developed and implemented a computerized reliability monitoring system for nuclear power plant applications, based on a neural network. The developed computer program is a new tool related to operator decision support systems, in case of component failures, for the determination of test and maintenance policies during normal operation or to follow an incident sequence in a nuclear power plant. The NAROAS (Neural Network Advanced Reliability Advisory System) computer system has been developed as a modularized integrated system in a C++ Builder environment, using a Hopfield neural network instead of fault trees, to follow and control the different system configurations, for interventions as quickly as possible at the plant. The observed results are comparable and similar to those of other computer system results. As shown, the application of this neural network contributes to the state of the art of risk monitoring systems by turning it easier to perform online reliability calculations in the context of probabilistic safety assessments of nuclear power plants.     

Conversion of a mainframe simulation for maintenance performance to a PC environment

This paper presents a brief review of a mainframe version of a computer code for simulating maintenance crew performance crew and introduces advantages realized with the recent implementation of a personal computer (PC) version. The basic computer model—the maintenance personnel performance simulation (MAPPS)—has been developed and validated by the US nuclear Regulatory Commission (NRC) in order to improve maintenance practices and procedures at nuclear power plants. The simulation model is stochastically based, and users are able to model 2 to 15 person crews. Maintenance crew performance is varied as a function of task, environment, and personnel factors. MAPPS produces human error probabilities (HEPs) suitable for use in probabilistic risk assessments. These HEPs are also a potentially important source of information for risk management data bases such as the NRC sponsored Nuclear Computerized Library for Assessing Reactor Reliability (NUCLARR).     

Examination of issues related to the development and implementation of real-time operational safety monitoring tools in the nuclear power industry

In recent years, risk and reliability techniques have been increasingly used to optimize deterministic requirements and to improve the operational safety of nuclear power stations. This paper discusses the historical development and current status of implementation of real-time operational safety monitoring tools in the nuclear power industry worldwide. A safety monitor is defined as a PC-based risk management tool, based on a plant specific PSA, which can be used to manage plant safety during the day-to-day operation of a nuclear power plant by planning maintenance activities and providing advisory information to plant operational staff in order to avoid high risk plant configurations. As this technique has only been applied in a few plants worldwide, the technology is still evolving and there are several technical and implementation-related issues which still need to be resolved. This paper attempts to summarize all such issues and describe how they have been addressed in several different applications of this technology around the world.     

Use of risk assessment in the nuclear industry with specific reference to the Australian situation

The use of risk assessment in the nuclear industry began in the 1970s as a complementary approach to the deterministic methods used to assess the safety of nuclear facilities. As experience with the theory and application of probabilistic methods has grown, so too has its application. In the last decade, the use of probabilistic safety assessment has become commonplace for all phases of the life of a plant, including siting, design, construction, operation and decommissioning. In the particular case of operation of plant, the use of a ‘living’ safety case or probabilistic safety assessment, building upon operational experience, is becoming more widespread, both as an operational tool and as a basis for communication with the regulator. In the case of deciding upon a site for a proposed reactor, use is also being made of probabilistic methods in defining the effect of design parameters. Going hand in hand with this increased use of risk based methods has been the development of assessment criteria against which to judge the results being obtained from the risk analyses. This paper reviews the use of risk assessment in the light of the need for acceptability criteria and shows how these tools are applied in the Australian nuclear industry, with specific reference to the probabilistic safety assessment (PSA) performed of HIFAR.     

A quantitative analysis of a risk impact due to a starting time extension of the emergency diesel generator in optimized power reactor-1000

An emergency diesel generator (EDG) is the ultimate electric power supply source for the operation of emergency engineered safety features when a nuclear power plant experiences a loss of off-site power (LOOP). If a loss of coolant accident (LOCA) with a simultaneous LOOP occurs, the EDG should be in the state of a full power within 10 s, which is a prescribed regulatory requirement in the technical specifications (TS) of the Optimized Power Reactor-1000 (OPR-1000).Recently, the US nuclear regulatory commission (NRC) has been preparing a new risk-informed emergency core cooling system (ECCS) rule called 10 CFR 50.46. The new rule redefines the size for the design basis LOCA and it relaxes some of the requirements such as the single failure criteria, simultaneous LOOP, and the methods of analysis. The revision of the ECCS rule will provide flexibility for plant changes if the plant risks are checked and balanced with the specified criteria.The present study performed a quantitative analysis of the plant risk impact due to the EDG starting time extension given that the new rule will be applied to OPR-1000. The thermal-hydraulic analysis and OPR-1000 probabilistic safety assessment (PSA) model were combined to estimate the whole plant risk impact. Also, sensitivity analyses were implemented for the important uncertainty parameters.