Probabilistic Risk Analyses: NRC Programs and Perspectives

The historical basis and more recent activities and products of probabilistic risk analysis (PRA) in the Atomic Energy Commission and Nuclear Regulatory Commission (NRC) are reviewed. Current NRC program activities and objectives are described. The author's opinions on the best uses of PRA are presented.     

A Discourse on the Incorporation of Organizational Factors into Probabilistic Risk Assessment: Key Questions and Categorical Review

This article presents a discourse on the incorporation of organizational factors into probabilistic risk assessment (PRA)/probabilistic safety assessment (PSA), a topic of debate since the 1980s that has spurred discussions among industry, regulatory agencies, and the research community. The main contributions of this article include (1) identifying the four key open questions associated with this topic; (2) framing ongoing debates by considering differing perspectives around each question; (3) offering a categorical review of existing studies on this topic to justify the selection of each question and to analyze the challenges related to each perspective; and (4) highlighting the directions of research required to reach a final resolution for each question. The four key questions are: (I) How significant is the contribution of organizational factors to accidents and incidents? (II) How critical, with respect to improving risk assessment, is the explicit incorporation of organizational factors into PRA? (III) What theoretical bases are needed for explicit incorporation of organizational factors into PRA? (IV) What methodological bases are needed for the explicit incorporation of organizational factors into PRA? Questions I and II mainly analyze PRA literature from the nuclear domain. For Questions III and IV, a broader review and categorization is conducted of those existing cross-disciplinary studies that have evaluated the effects of organizational factors on safety (not solely PRA-based) to shed more light on future research needs.     

Uncertainties in Nuclear Probabilistic Risk Analyses

There are many uncertainties in a probabilistic risk analysis (PRA). We identify the different types of uncertainties and describe their implications. We then summarize the uncertainty analyses which have performed in current PRAs and characterize results which have been obtained. We draw conclusions regarding interpretations of uncertainties, areas having largest uncertainties, and needs which exist in uncertainty analysis. We finally characterize the robustness of various utilizations of PRA results.     

A Nuclear Utility's Views on the Use of Probabilistic Risk Assessment

Probabilistic risk assessment (PRA) is a relatively new tool in the nuclear industry. The Reactor Safety Study started the present trend of conducting PRAs for nuclear power plants when it was published in 1975. Now, nine years later, those in the industry currently using PRA techniques are frequently asked the same question: Why should the nuclear utility industry, with so many accepted analytical tools already available, invest the time and manpower to develop a new technique with so many uncertainties?     

Probabilistic Risk Analysis and Game Theory

The behavioral dimension matters in Probabilistic Risk Analysis (PRA) since players throughout a system incur costs to increase system reliability interpreted as a public good. Individual strategies at the subsystem level generally conflict with collective desires at the system level. Game theory, the natural tool to analyze individual-collective conflicts that affect risk, is integrated into PRA. Conflicts arise in series, parallel, and summation systems over which player(s) prefer(s) to incur the cost of risk reduction. Frequently, the series, parallel, and summation systems correspond to the four most common games in game theory, i.e., the coordination game, the battle of the sexes and the chicken game, and prisoner's dilemma, respectively.     

The Risk Criteria for Assessment of Temporary Changes in a Nuclear Power Plant

Risk criterion is a term that may distinguish between what is considered as an acceptable level of safety and what is not. One of the ways of determining quantitative risk criteria for temporary changes in a nuclear power plant considering probabilistic safety assessment is presented. Risk criteria are based on timing and on time duration of the change. Several examples of temporary changes in a nuclear power plant were examined to evaluate the criteria. Results show that it is possible to determine a set of risk criteria for temporary changes. Risk criteria can represent a standpoint for risk-informed decision making.     

Exploring the Uncertainties in Cancer Risk Assessment Using the Integrated Probabilistic Risk Assessment (IPRA) Approach

Current methods for cancer risk assessment result in single values, without any quantitative information on the uncertainties in these values. Therefore, single risk values could easily be overinterpreted. In this study, we discuss a full probabilistic cancer risk assessment approach in which all the generally recognized uncertainties in both exposure and hazard assessment are quantitatively characterized and probabilistically evaluated, resulting in a confidence interval for the final risk estimate. The methodology is applied to three example chemicals (aflatoxin, N‐nitrosodimethylamine, and methyleugenol). These examples illustrate that the uncertainty in a cancer risk estimate may be huge, making single value estimates of cancer risk meaningless. Further, a risk based on linear extrapolation tends to be lower than the upper 95% confidence limit of a probabilistic risk estimate, and in that sense it is not conservative. Our conceptual analysis showed that there are two possible basic approaches for cancer risk assessment, depending on the interpretation of the dose‐incidence data measured in animals. However, it remains unclear which of the two interpretations is the more adequate one, adding an additional uncertainty to the already huge confidence intervals for cancer risk estimates.     

Health Risk Assessment for Planned Waste Incinerators: Getting the Right Science and the Science Right

Health risk assessment is widely advocated in the United Kingdom as the most comprehensive means of assessing the health risks posed by the emissions of a planned waste incinerator. Its main advantage over other methods of assessment, such as air quality impact assessment, is its ability to address explicitly the direct (inhalation) and indirect (ingestion and dermal contact) health risks posed by different chemicals, including those that are not thought to have a threshold below which no adverse effect will take place. This article examines the level and quality of the emissions assessments included in 61 waste incinerator environmental statements (ESs); in particular, it focuses on the quality of the exposure assessment and risk characterization stages of the health risk assessment process. The article concludes that the ES has not always provided interested stakeholders with the best available information upon which to determine the tolerability of the health risks posed by waste incinerator emissions Some recommendations are made as to how this problem might be addressed in future environmental impact assessment (EIA) processes.     

Probabilistic Models for Risk Assessment

Recent concern with the potential for stray carbon fibers to damage electronic equipment and cause economic losses has led to the development of advanced risk-assessment methods. Risk assessment often requires the synthesis of risk profiles which represent the probability distribution of total annual losses due to a certain set of events or activities. A number of alternative probabilistic models are presented which the authors have used to develop such profiles. Examples are given of applications of these methods to assessment of risk due to conductive fibers released from aircraft or automobile fires. These assessments usually involve a two-stage approach: estimation of losses for several subclassifications of the overall process, and synthesis of the results into an aggregate risk profile. The methodology presented is capable of treating a wide variety of situations involving sequences of random physical events.     

Probabilistic Health Risk Assessment for Exposures to Estuary Sediments and Biota Contaminated with Polychlorinated Biphenyls, Polychlorinated Terphenyls and Other Toxic Substances

A Latin Hypercube probabilistic risk assessment methodology was employed in the assessment of health risks associated with exposures to contaminated sediment and biota in an estuary in the Tidewater region of Virginia. The primary contaminants were polychlorinated biphenyls (PCBs), polychlorinated terphenyls (PCTs), polynuclear aromatic hydrocarbons (PAHs), and metals released into the estuary from a storm sewer system. The exposure pathways associated with the highest contaminant intake and risks were dermal contact with contaminated sediment and ingestion of contaminated aquatic and terrestrial biota from the contaminated area. As expected, all of the output probability distributions of risk were highly skewed, and the ratios of the expected value (mean) to median risk estimates ranged from 1.4 to 14.8 for the various exposed populations. The 99th percentile risk estimates were as much as two orders of magnitude above the mean risk estimates. For the sediment exposure pathways, the stability of the median risk estimates was found to be much greater than the stability of the expected value risk estimates. The interrun variability in the median risk estimate was found to be +/-1.9% at 3000 iterations. The interrun stability of the mean risk estimates was found to be approximately equal to that of the 95th percentile estimates at any number of iterations. The variation in neither contaminant concentrations nor any other single input variable contributed disproportionately to the overall simulation variance. The inclusion or exclusion of spatial correlations among contaminant concentrations in the simulation model did not significantly effect either the magnitude or the variance of the simulation risk estimates for sediment exposures.     

Integration of Probabilistic Exposure Assessment and Probabilistic Hazard Characterization

A method is proposed for integrated probabilistic risk assessment where exposure assessment and hazard characterization are both included in a probabilistic way. The aim is to specify the probability that a random individual from a defined (sub)population will have an exposure high enough to cause a particular health effect of a predefined magnitude, the critical effect size ( CES ). The exposure level that results in exactly that CES in a particular person is that person's individual critical effect dose ( ICED ). Individuals in a population typically show variation, both in their individual exposure ( IEXP ) and in their ICED . Both the variation in IEXP and the variation in ICED are quantified in the form of probability distributions. Assuming independence between both distributions, they are combined (by Monte Carlo) into a distribution of the individual margin of exposure ( IMoE ). The proportion of the IMoE distribution below unity is the probability of critical exposure ( PoCE ) in the particular (sub)population. Uncertainties involved in the overall risk assessment (i.e., both regarding exposure and effect assessment) are quantified using Monte Carlo and bootstrap methods. This results in an uncertainty distribution for any statistic of interest, such as the probability of critical exposure ( PoCE ). The method is illustrated based on data for the case of dietary exposure to the organophosphate acephate. We present plots that concisely summarize the probabilistic results, retaining the distinction between variability and uncertainty. We show how the relative contributions from the various sources of uncertainty involved may be quantified.     

A Methodology for Grouping Source Terms for Consequence Calculations in Probabilistic Risk Assessments

The individual plant analyses in the U.S. Nuclear Regulatory Commission's reassessment of the risk from commercial nuclear power plants (NUREG-1150) consist of four parts: systems analysis, accident-progression analysis, source-term analysis, and consequence analysis. Careful definition of the interfaces between these parts is necessary for both information flow and computational efficiency. This paper describes the procedure used to define the interface between the source-term analysis and the consequence analysis. This interface is accomplished by forming groups of source terms with similar properties and then performing one set of MACCS calculations for each group.     

Measures of Compounding Conservatism in Probabilistic Risk Assessment

Concern about the degree of uncertainty and potential conservatism in deterministic point estimates of risk has prompted researchers to turn increasingly to probabilistic methods for risk assessment. With Monte Carlo simulation techniques, distributions of risk reflecting uncertainty and/or variability are generated as an alternative. In this paper the compounding of conservatism⁽¹⁾ between the level associated with point estimate inputs selected from probability distributions and the level associated with the deterministic value of risk calculated using these inputs is explored. Two measures of compounded conservatism are compared and contrasted. The first measure considered, F , is defined as the ratio of the risk value, R _d, calculated deterministically as a function of n inputs each at the j th percentile of its probability distribution, and the risk value, R _j that falls at the j th percentile of the simulated risk distribution (i.e., F=R_d/R_j). The percentile of the simulated risk distribution which corresponds to the deterministic value, R_d , serves as a second measure of compounded conservatism. Analytical results for simple products of lognormal distributions are presented. In addition, a numerical treatment of several complex cases is presented using five simulation analyses from the literature to illustrate. Overall, there are cases in which conservatism compounds dramatically for deterministic point estimates of risk constructed from upper percentiles of input parameters, as well as those for which the effect is less notable. The analytical and numerical techniques discussed are intended to help analysts explore the factors that influence the magnitude of compounding conservatism in specific cases.     

Recent Case Studies and Advancements in Probabilistic Risk Assessment

During the period from 1977 to 1984, Pickard, Lowe and Garrick, Inc., had the lead in preparing several full scope probabilistic risk assessments for electric utilities. Five of those studies are discussed from the point of view of advancements and lessons learned. The objective and trend of these studies is toward utilization of the risk models by the plant owners as risk management tools. Advancements that have been made are in presentation and documentation of the PRAs, generation of more understandable plant level information, and improvements in methodology to facilitate technology transfer. Specific areas of advancement are in the treatment of such issues as dependent failures, human interaction, and the uncertainty in the source term. Lessons learned cover a wide spectrum and include the importance of plant specific models for meaningful risk management, the role of external events in risk, the sensitivity of contributors to choice of risk index, and the very important finding that the public risk is extremely small. The future direction of PRA is to establish less dependence on experts for in-plant application. Computerizing the PRAs such that they can be accessed on line and interactively is the key.     

Probabilistic Reliability Analysis, Quantitative Safety Goals, and Nuclear Licensing in the United Kingdom

Although unpublicized, the use of quantitative safety goals and probabilistic reliability analysis for licensing nuclear reactors has become a reality in the United Kingdom. This conclusion results from an examination of the process leading to the licensing of the Sizewell B PWR in England. The licensing process for this reactor has substantial implications for nuclear safety standards in Britain, and is examined in the context of the growing trend towards quantitative safety goals in the United States.     

How Probabilistic Risk Assessment Can Mislead Terrorism Risk Analysts

Traditional probabilistic risk assessment (PRA), of the type originally developed for engineered systems, is still proposed for terrorism risk analysis. We show that such PRA applications are unjustified in general. The capacity of terrorists to seek and use information and to actively research different attack options before deciding what to do raises unique features of terrorism risk assessment that are not adequately addressed by conventional PRA for natural and engineered systems—in part because decisions based on such PRA estimates do not adequately hedge against the different probabilities that attackers may eventually act upon. These probabilities may differ from the defender's (even if the defender's experts are thoroughly trained, well calibrated, unbiased probability assessors) because they may be conditioned on different information. We illustrate the fundamental differences between PRA and terrorism risk analysis, and suggest use of robust decision analysis for risk management when attackers may know more about some attack options than we do.     

Asteroid Risk Assessment: A Probabilistic Approach

Following the 2013 Chelyabinsk event, the risks posed by asteroids attracted renewed interest, from both the scientific and policy‐making communities. It reminded the world that impacts from near‐Earth objects (NEOs), while rare, have the potential to cause great damage to cities and populations. Point estimates of the risk (such as mean numbers of casualties) have been proposed, but because of the low‐probability, high‐consequence nature of asteroid impacts, these averages provide limited actionable information. While more work is needed to further refine its input distributions (e.g., NEO diameters), the probabilistic model presented in this article allows a more complete evaluation of the risk of NEO impacts because the results are distributions that cover the range of potential casualties. This model is based on a modularized simulation that uses probabilistic inputs to estimate probabilistic risk metrics, including those of rare asteroid impacts. Illustrative results of this analysis are presented for a period of 100 years. As part of this demonstration, we assess the effectiveness of civil defense measures in mitigating the risk of human casualties. We find that they are likely to be beneficial but not a panacea. We also compute the probability—but not the consequences—of an impact with global effects (“cataclysm”). We conclude that there is a continued need for NEO observation, and for analyses of the feasibility and risk‐reduction effectiveness of space missions designed to deflect or destroy asteroids that threaten the Earth.     

Nuclear Plant PRA: How Far Has It Come?

Nearly ten years have passed since the publication in August 1974 of the draft Reactor Safety Study (WASH 1400), the first detailed attempt to apply probabilistic risk assessment (PRA) techniques to estimate the public risks posed by commercial nuclear power plants. Now is an opportune time to look back and see how PRA has fared over these ten years. We will not attempt to pass judgement on how the Reactor Safety Study report itself has withstood the test of time, as that task is best left to others less directly involved in preparing the report. Instead, we will examine advances in the understanding, acceptance, and utilization of PRA techniques, as well as technical advances in PRA methods. Some of the significant insights gained from PRAs will be discussed. Finally, some observations on the future of PRA will be offered.     

Site-Specific Applications of Probabilistic Health Risk Assessment: Review of the Literature Since 2000

Whether and to what extent contaminated sites harm ecologic and human health are topics of considerable interest, but also considerable uncertainty. Several federal and state agencies have approved the use of some or many aspects of probabilistic risk assessment (PRA), but its site-specific application has often been limited to high-profile sites and large projects. Nonetheless, times are changing: newly developed software tools, and recent federal and state guidance documents formalizing PRA procedures, now make PRA a readily available method of analysis for even small-scale projects. This article presents and discusses a broad review of PRA literature published since 2000.     

Ensuring the Quality of Occupational Safety Risk Assessment

In work environments, the main aim of occupational safety risk assessment (OSRA) is to improve the safety level of an installation or site by either preventing accidents and injuries or minimizing their consequences. To this end, it is of paramount importance to identify all sources of hazards and assess their potential to cause problems in the respective context. If the OSRA process is inadequate and/or not applied effectively, it results in an ineffective safety prevention program and inefficient use of resources. An appropriate OSRA is an essential component of the occupational safety risk management process in industries. In this article, we performed a survey to elicit the relative importance for identified OSRA tasks to enable an in‐depth evaluation of the quality of risk assessments related to occupational safety aspects on industrial sites. The survey involved defining a questionnaire with the most important elements (tasks) for OSRA quality assessment, which was then presented to safety experts in the mining, electrical power production, transportation, and petrochemical industries. With this work, we expect to contribute to the main question of OSRA in industries: “What constitutes a good occupational safety risk assessment?” The results obtained from the questionnaire showed that experts agree with the proposed OSRA process decomposition in steps and tasks (taxonomy) and also with the importance of assigning weights to obtain knowledge about OSRA task relevance. The knowledge gained will enable us, in the near future, to build a framework to evaluate OSRA quality for industrial sites.