Building confidence in the reliability assessment of thermal-hydraulic passive systems

Thermal-hydraulic (T-H) passive systems play a crucial role in the development of future solutions for nuclear power plant technologies. A fundamental issue still to be resolved is the quantification of the reliability of such systems.The difficulty comes from the uncertainties in the evaluation of their performance, because of the lack of experimental and operational data and of validated models of the phenomena involved. The uncertainties concern the deviations of the underlying physical principles from the expected T-H behaviour, due to the onset of physical phenomena infringing the system performance or to changes in the initial/boundary conditions of system operation.In this work, some insights resulting from a survey on the technical issues associated with estimating the reliability of T-H passive systems in the context of nuclear safety are first provided. It is concluded that the most realistic assessment of the passive system response to the uncertain accident conditions can be achieved by Monte-Carlo (MC) sampling of the system uncertain parameters followed by the simulation of the accident evolution by a detailed mechanistic T-H code. This procedure, however, requires considerable and often prohibitive computational efforts for achieving acceptable accuracies, so that a limitation on the MC sample size, i.e. on the number of code runs, is necessarily forced onto the analysis. As a consequence, it becomes mandatory to provide quantitative measures of the uncertainty of the computed estimates.To this aim, two classes of statistical methods are proposed in the paper to quantify, in terms of confidence intervals, the uncertainties associated with the reliability estimates. The first method is based on the probability laws of the binomial distribution governing the stochastic process of system success or failure. The second method is founded on the concept of bootstrapping, suitable to assess the accuracy of estimators when no prior information on their distributions is available. To the authors’ knowledge, it is the first time that these methods are applied to quantitatively bracket the confidence on the estimates of the reliability of passive systems by MC simulation.The two methods are demonstrated by an application to a real passive system of literature.     

An operator support system for research reactor operations and fault diagnosis through a connectionist framework and PSA based knowledge based systems

During reactor upset/abnormal conditions, emphasis is placed on the plant operator's ability to quickly identify the problem and perform diagnosis and initiate recovery action to ensure the safety of the plant. However, the reliability of human action is adversely affected at the time of crisis due to time stress and psychological factors. The availability of operational aids capable of monitoring the status of the plant and quickly identifying the deviation from normal operation is expected to significantly improve the operator reliability.The development of operator support systems using probabilistic safety assessment (PSA) techniques and information is finding wide application in nuclear plant operation. Often it is observed that most of the applications use a rule-based approach for diagnosis as well as safety status/transient conditions monitoring. A more efficient approach using artificial neural networks for safety status/transient condition monitoring and rule-based systems for diagnosis and emergency procedure generation has been applied for the development of a prototype operator adviser (OPAD) system for a 100 MW(th) heavy water moderated, cooled and natural uranium fueled research reactor. The development objective of this system is to improve the reliability of operator action and hence the reactor safety at the time of crisis as well as in normal operation. In order to address safety objectives at various stages of development of OPAD, the PSA techniques and tools have been used for knowledge representation. It has been demonstrated, with recall tests on the artificial neural network, that it can efficiently identify the reactor status in real-time scenario. This paper discusses various issues related to the development of an operator support system in a comprehensive way, right from the study of safety objectives, to data collection, to implementation of such a system.     

Determination of design alternatives and performance criteria for safety systems in a nuclear power plant via simulated annealing

This study presents an efficient methodology that derives design alternatives and performance criteria for safety functions/systems in commercial nuclear power plants. Determination of the design alternatives and intermediate-level performance criteria is posed as a reliability allocation problem. The reliability allocation is performed in a single step by means of the concept of two-tier noninferior solutions in the objective and risk spaces within the top-level probabilistic safety criteria (PSC). Two kinds of two-tier noninferior solutions are obtained: desirable design alternatives and intolerable intermediate-level PSC of safety functions/systems.The weighted Chebyshev norm (WCN) approach with an improved Metropolis algorithm in simulated annealing is used to find the two-tier noninferior solutions. This is very efficient in searching for the global minimum of the difficult multiobjective optimization problem (MOP) which results from strong nonlinearity of a probabilistic safety assessment (PSA) model and nonconvexity of the problem. The methodology developed in this study can be used as an efficient design tool for desirable safety function/system alternatives and for the determination of intermediate-level performance criteria.The methodology is applied to a realistic streamlined PSA model that is developed based on the PSA results of the Surry Unit 1 nuclear power plant. The methodology developed in this study is very efficient in providing the intolerable intermediate-level PSC and desirable design alternatives of safety functions/systems.     

Organizational processes and nuclear power plant safety

This paper describes an integrated effort to define and measure organizational factors related to nuclear power plant safety. The research began by reviewing previously conducted studies looking at nuclear power operations and operations in other high reliability industries for indications of common safety-related, performance dimensions. Having established a list of 20 common dimensions, the project went on to fully define these dimensions and develop methods for their assessment. The methods of assessment developed for this application were employee survey—a series of self report questions answered by employees, behavioral checklist—sets of statements about the plant and its operations that observers respond to by answering yes or no, structured interview—a set of questions and interviewer asks of an employee and built around the 20 dimensions identified, and behaviorally anchored rating scales—an extension of the methodology used for assessing the performance of individuals to the process of assessing a nuclear power plant. Each of the methodologies is described as it applies to the assessment within the nuclear power environment and examples of each method are presented. Pilot tests of the feasibility of using these assessment methods were conducted in two nuclear power plants and the results are encouraging both in terms of the immediate identification of potential safety issues and as valuable additions to probabilistic risk assessment. Implications of this work for the future assessment of organizational factors related to nuclear power safety are discussed.     

From LESSEPS to the workstation for reliability engineers

Three Mile Island and Chernobyl in the nuclear industry, Challenger, in the space industry, Seveso and Bhopal in the chemical industry—all these accidents show how difficult it is to forecast all likely accident scenarios that may occur in complex systems. This was, however, the objective of the probabilistic safety assessment (PSA) performed by EDF at the Paluel nuclear power plant. The full computerization of this study led to the LESSEPS project, aimed at automating three different steps: generation of reliability models—based on the use of expert systems, qualitative and quantitative processing of these models using computer codes, and overall management of PSA studies. This paper presents the results obtained and the gradual transformation of this first generation of tools into a workstation aimed at integrating reliability studies at all stages of an industrial process.     

Adjoint operator approach to functional reliability analysis of passive fluid dynamical systems

Reliability analysis of passive systems mainly involves quantification of the margin to safety limits in probabilistic terms. For systems represented by complex models, propagating input uncertainty to get the response uncertainty and hence probability information requires intensive computational effort. Here a computationally efficient method for the functional reliability analysis of passive fluid dynamical systems is presented. The approach is based on continuous adjoint operator technique to generate a response surface approximating the given system model from the sensitivity coefficients. A numerical application of this method to the reliability analysis of heat transport in an asymmetrical natural convection loop is demonstrated. Computational efficiency and accuracy compared with the direct Monte-Carlo and forward response surface methods.     

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.     

Different sets of reliability data and success criteria in a probabilistic safety assessment for a plant producing nitroglycol

The lack of plant-specific reliability data for probabilistic safety assessments usually makes it necessary to use generic reliability data. Justifiably different assessments of plant behaviour (success criteria) lead to different models of plant systems. Both affect the numerical results of a probabilistic safety assessment. It is shown how these results change, if different sets of reliability data and different choices of success criteria for the safety system are employed. Differences in results may influence decisions taken on their basis and become especially important if compliance with a safety goal has to be proved, e.g. a safety integrity level. For the purpose of demonstration an accident sequence from a probabilistic safety assessment of a plant producing nitroglycol is used. The analysis relies on plant-specific reliability data so that it provides a good yardstick for comparing it with results obtained using generic data. The superiority of plant-specific data, which should of course be acquired, cannot be doubted. Nevertheless, plant safety can be improved even if generic data are used. However, the assignment to a safety integrity level may be affected by differences in both data and success criteria.     

An approach for assessing human decision reliability

This paper presents a method to study human reliability in decision situations related to nuclear power plant disturbances. Decisions often play a significant role in handling of emergency situations. The method may be applied to probabilistic safety assessments (PSAs) in cases where decision making is an important dimension of an accident sequence. Such situations are frequent e.g. in accident management. In this paper, a modelling approach for decision reliability studies is first proposed. Then, a case study with two decision situations with relatively different characteristics is presented. Qualitative and quantitative findings of the study are discussed. In very simple decision cases with time pressure, time reliability correlation proved out to be a feasible reliability modelling method. In all other decision situations, more advanced probabilistic decision models have to be used. Finally, decision probability assessment by using simulator run results and expert judgement is presented.     

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.     

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.     

Passive detectors for neutron personal dosimetry: state of the art

Passive, solid-state detectors still dominate the field of neutron personal dosimetry, mainly thanks to their low cost, high reliability and elevated throughput. However, the recent appearance in the market of several electronic personal dosemeters for neutrons presents a challenge to the exclusive use of passive systems for primary or official dosimetry. This scenario drives research and development activities on passive dosemeters towards systems offering greater accuracy of response and lower detection limits. In addition, further applications and properties of the passive detectors, which are not met by the electronic devices, are also being explored. In particular, extensive investigations are in progress on the use of solid-state detectors for aviation and space dosimetry, where high-energy neutron fields are encountered. The present situation is also stimulating an acceleration in the development of international standards on performance and test requirements for passive dosimetry systems, which can expedite significantly the implementation of techniques in commercial personal dosimetry services. Upcoming standards will cover thermoluminescence albedo dosemeters, etched-track detectors, superheated emulsions and direct ion storage chambers, attesting to the level of maturity reached by these techniques. This work reviews the developments in the field of passive neutron dosimetry emerged since the previous Neutron Dosimetry Symposium, reporting on the current status of the subject and indicating the direction of ongoing research.     

Probabilistic safety assessment in Canada

The original basis for licensing power reactors in Canada was probabilistic, from which deterministic requirements were derived and developed. The AECB currently regulates in part by imposing unavailability targets on four special safety systems. In recent years, a number of Probabilistic Safety Assessment (PSA) studies have been performed in Canada, although a PSA is not yet formally required yet in licensing. These PSAs are used to derive the fault tree models for special safety systems, to show that their reliability targets are met. A policy and regulatory guides for using PSA in licensing are currently being developed. This article describes the evolution of safety objectives, the current status of PSA, future applications of PSA, and the regulatory aspects of PSA in Canada.     

Reliability Prediction Based on Variation Mode and Effect Analysis

The possibility of predicting the reliability of hardware for both components and systems is important in engineering design. Today, there are several methods for predicting the reliability of hardware systems and for identifying the causes of failure and failure modes, for example, fault tree analysis and failure mode and effect analysis. Many failures are caused by variations resulting in a substantial effect on safety or functional requirements. To identify, to assess and to manage unwanted sources of variation, a method called probabilistic variation mode and effect analysis (VMEA) has been developed. With a prescribed reliability, VMEA can be used to derive safety factors in different applications. However, there are few reports on how to derive the reliability based on probabilistic VMEA, especially for transmission clutch shafts. Hence, the objective of this article was to show how to derive system reliability based on probabilistic VMEA. In particular, wheel loader automatic transmission clutch shaft reliability is investigated to show how different sources of variation affect reliability. In this article, a new method for predicting system reliability based on probabilistic VMEA is proposed. The method is further verified by a case study on a clutch shaft. It is shown that the reliability of the clutch shaft was close to 1.0 and that the most significant variation contribution was due to mean radius of the friction surface and friction of the disc. Copyright © 2012 John Wiley & Sons, Ltd.     

Quantification of margins and uncertainties: Conceptual and computational basis

In 2001, the National Nuclear Security Administration of the U.S. Department of Energy in conjunction with the national security laboratories (i.e., Los Alamos National Laboratory, Lawrence Livermore National Laboratory and Sandia National Laboratories) initiated development of a process designated Quantification of Margins and Uncertainties (QMU) for the use of risk assessment methodologies in the certification of the reliability and safety of the nation's nuclear weapons stockpile. This presentation discusses and illustrates the conceptual and computational basis of QMU in analyses that use computational models to predict the behavior of complex systems. The following topics are considered: (i) the role of aleatory and epistemic uncertainty in QMU, (ii) the representation of uncertainty with probability, (iii) the probabilistic representation of uncertainty in QMU analyses involving only epistemic uncertainty, and (iv) the probabilistic representation of uncertainty in QMU analyses involving aleatory and epistemic uncertainty.     

Reliability of safety-critical systems: A state-of-the-art review

Safety-critical systems are designed to prevent catastrophic consequences from failure, such as injury or death to humans and environmental damage. These must be carefully designed to ensure reliability requirements. The purpose of this paper is to identify the number of models in the reliability analysis of safety-critical systems. To achieve this goal, we conducted a systematic review of 40 shortlisted studies. The selected studies are classified based on various techniques used in safety-critical systems. This paper summarizes the literature review in the field of reliability of safety-critical systems. The limitations of the literature are exquisitely represented. The international safety norms and applications of safety-critical systems are discussed systematically in this paper. This paper emerges research trends, research challenges and insights of the researcher for future research direction in the area of safety-critical systems.     

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.     

Risk analysis of surveillance requirements including their adverse effects

Technical specifications for nuclear power plants require periodic surveillance testing of the standby systems important to safety. This regulatory requirement is imposed to assure that the systems will start and perform their intended functions in the event of plant abnormality. However, operating experience suggests that, in addition to the beneficial effects of detecting latent faults, the tests may have adverse effects on the plant's operation or equipment. This paper defines those adverse effects of testing from a risk perspective, and then presents a method to quantify their associated risk impact, focusing on plant transients and the wear-out of safety systems. The method, based on probabilistic safety assessment, is demonstrated by applying it to several surveillance tests conducted at boiling water reactors. The insights from this evaluation can be used to determine risk-effective intervals for surveillance tests.     

Important issues using PSA technology for design of new systems and plants

Modern engineering design of new systems or plants needs not only the specification of the function of the system during various life cycle periods, but also the consideration of additional requirements and the demonstration of the compliance with it based on a predictive model considering measurable properties and possible malfunctions of the system parts. Additional requirements can be high availability, low emissions or high safety level. PSA technology provides a framework and tools to establish design targets and to demonstrate their compliance. In this paper important issues using this technology are discussed. Issues are targeted at various levels—the basic evaluation of reliability for active and passive components and the entire system, the general process to show the compliance of the given system characteristics with the characteristics required. This paper does not deal with the details of all these issues, but provides references for further information.