The Dependence of the Risk of Research Reactors from Their Operating Schedule–A Case Study

The dependence of the radiological consequences of the "Demokritos" research reactor on the operating schedule of the reactor is assessed in this paper. The 5 MW reactor is located within the limits of Athens city, a large population center with over 3 million inhabitants. The consequences examined would be due to the occurrence of a postulated accident, a 20% core melt loss of coolant accident, that is also considered as the design basis accident of the reactor. Three operating schedules are taken into account: (a) a continuous operation schedule; (b) a 16 hr/day, 5 days/week schedule; and (c) the present 8 hr/day, 5 days/week operating schedule. The assessment of the source term emerges from a conservative estimation of fission product releases to the reactor operating floor, and further under the conservative assumptions of no filter mitigation, and a ground release to the environment. The results of the analysis indicate that there is a direct relation between consequences and duration of operation, the former becoming appreciable as the continuous operation limit is approached. In all cases examined, the thyroid dose and the latent thyroid health effects would be the limiting consequences.     

“What—Me Worry?”1“Why So Serious?”:2 A Personal View on the Fukushima Nuclear Reactor Accidents

Infrequently, it seems that a significant accident precursor or, worse, an actual accident, involving a commercial nuclear power reactor occurs to remind us of the need to reexamine the safety of this important electrical power technology from a risk perspective. Twenty‐five years since the major core damage accident at Chernobyl in the Ukraine, the Fukushima reactor complex in Japan experienced multiple core damages as a result of an earthquake‐induced tsunami beyond either the earthquake or tsunami design basis for the site. Although the tsunami itself killed tens of thousands of people and left the area devastated and virtually uninhabitable, much concern still arose from the potential radioactive releases from the damaged reactors, even though there was little population left in the area to be affected. As a lifelong probabilistic safety analyst in nuclear engineering, even I must admit to a recurrence of the doubt regarding nuclear power safety after Fukushima that I had experienced after Three Mile Island and Chernobyl. This article is my attempt to “recover” my personal perspective on acceptable risk by examining both the domestic and worldwide history of commercial nuclear power plant accidents and attempting to quantify the risk in terms of the frequency of core damage that one might glean from a review of operational history.     

Of Disasters and Dragon Kings: A Statistical Analysis of Nuclear Power Incidents and Accidents

We perform a statistical study of risk in nuclear energy systems. This study provides and analyzes a data set that is twice the size of the previous best data set on nuclear incidents and accidents, comparing three measures of severity: the industry standard International Nuclear Event Scale, the Nuclear Accident Magnitude Scale of radiation release, and cost in U.S. dollars. The rate of nuclear accidents with cost above 20 MM 2013 USD, per reactor per year, has decreased from the 1970s until the present time. Along the way, the rate dropped significantly after Chernobyl (April 1986) and is expected to be roughly stable around a level of 0.003, suggesting an average of just over one event per year across the current global fleet. The distribution of costs appears to have changed following the Three Mile Island major accident (March 1979). The median cost became approximately 3.5 times smaller, but an extremely heavy tail emerged, being well described by a Pareto distribution with parameter α = 0.5–0.6. For instance, the cost of the two largest events, Chernobyl and Fukushima (March 2011), is equal to nearly five times the sum of the 173 other events. We also document a significant runaway disaster regime in both radiation release and cost data, which we associate with the “dragon‐king” phenomenon. Since the major accident at Fukushima (March 2011) occurred recently, we are unable to quantify an impact of the industry response to this disaster. Excluding such improvements, in terms of costs, our range of models suggests that there is presently a 50% chance that (i) a Fukushima event (or larger) occurs every 60–150 years, and (ii) that a Three Mile Island event (or larger) occurs every 10–20 years. Further—even assuming that it is no longer possible to suffer an event more costly than Chernobyl or Fukushima—the expected annual cost and its standard error bracket the cost of a new plant. This highlights the importance of improvements not only immediately following Fukushima, but also deeper improvements to effectively exclude the possibility of “dragon‐king” disasters. Finally, we find that the International Nuclear Event Scale (INES) is inconsistent in terms of both cost and radiation released. To be consistent with cost data, the Chernobyl and Fukushima disasters would need to have between an INES level of 10 and 11, rather than the maximum of 7.     

Managing the Fukushima Challenge

The Fukushima Daiichi accident raises a fundamental question: Can science and technology prevent the inevitability of serious accidents, especially those with low probabilities and high consequences? This question reminds us of a longstanding challenge with the trans‐sciences, originally addressed by Alvin Weinberg well before the Three Mile Island and Chernobyl accidents. This article, revisiting Weinberg's issue, aims at gaining insights from the accident with a special emphasis on the sociotechnical or human behavioral aspects lying behind the accident's causes. In particular, an innovative method for managing the challenge is explored referring to behavioral science approaches to a decision‐making process on risk management; such as managing human behavioral risks with information asymmetry, seeking a rational consensus with communicative action, and pursuing procedural rationality through interactions with the outer environment. In short, this article describes the emerging need for Japan to transform its national safety management institutions so that these might be based on interactive communication with parties inside and outside Japan.     

Effects of the Chernobyl Accident on Public Perceptions of Nuclear Plant Accident Risks

Assessments of public perceptions of the characteristics of a nuclear power plant accident and affective responses to its likelihood were conducted 5 months before and 1 month after the Chernobyl accident. Analyses of data from 69 residents of southwestern Washington showed significant test-retest correlations for only 10 of 18 variables--accident likelihood, three measures of impact characteristics, three measures of affective reactions, and hazard knowledge by governmental sources. Of these variables, only two had significant changes in mean ratings; frequency of thought and frequency of discussion about a nearby nuclear power plant both increased. While there were significant changes only for two personal consequences (expectations of cancer and genetic effects), both of these decreased. The results of this study indicate that more attention should be given to assessing the stability of risk perceptions over time. Moreover, the data demonstrate that experience with a major accident can actually decrease rather than increase perceptions of threat.     

Lessons learned from Toulouse and Buncefield disasters: from risk analysis failures to the identification of atypical scenarios through a better knowledge management

The recent occurrence of severe major accidents has brought to light flaws and limitations of hazard identification (HAZID) processes performed for safety reports, as in the accidents at Toulouse (France) and Buncefield (UK), where the accident scenarios that occurred were not captured by HAZID techniques. This study focuses on this type of atypical accident scenario deviating from normal expectations. The main purpose is to analyze the examples of atypical accidents mentioned and to attempt to identify them through the application of a well-known methodology such as the bow-tie analysis. To these aims, the concept of atypical event is accurately defined. Early warnings, causes, consequences, and occurrence mechanisms of the specific events are widely studied and general failures of risk assessment, management, and governance isolated. These activities contribute to outline a set of targeted recommendations, addressing transversal common deficiencies and also demonstrating how a better management of knowledge from the study of past events can support future risk assessment processes in the identification of atypical accident scenarios. Thus, a new methodology is not suggested; rather, a specific approach coordinating a more effective use of experience and available information is described, to suggest that lessons to be learned from past accidents can be effectively translated into actions of prevention.     

Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks

This article develops a Bayesian belief network model for the prediction of accident consequences in the Tianjin port. The study starts with a statistical analysis of historical accident data of six years from 2008 to 2013. Then a Bayesian belief network is constructed to express the dependencies between the indicator variables and accident consequences. The statistics and expert knowledge are synthesized in the Bayesian belief network model to obtain the probability distribution of the consequences. By a sensitivity analysis, several indicator variables that have influence on the consequences are identified, including navigational area, ship type and time of the day. The results indicate that the consequences are most sensitive to the position where the accidents occurred, followed by time of day and ship length. The results also reflect that the navigational risk of the Tianjin port is at the acceptable level, despite that there is more room of improvement. These results can be used by the Maritime Safety Administration to take effective measures to enhance maritime safety in the Tianjin port.     

Chernobyl's Effects on the Perceived Risks of Nuclear Power: A Small Sample Test

This paper presents the results of two risk perception surveys, one taken just before and one just after the accident at Chernobyl in May, 1985. The results show that Chernobyl affected short-term perceptions of nuclear power risks in ways that are predictable and measureable. In this sample, perceived levels of dread of nuclear power increased, perceived knowledge increased, and perceived severity decreased. Overall, the results are informative about how a single event could affect perceived risk characteristics.     

Probabilistic Analysis of Dam Accidents Worldwide: Risk Assessment for Dams of Different Purposes in OECD and Non-OECD Countries with Focus on Time Trend Analysis

This study presents probabilistic analysis of dam accidents worldwide in the period 1911–2016. The accidents are classified by the dam purpose and by the country cluster, where they occurred, distinguishing between the countries of the Organization for Economic Cooperation and Development (OECD) and nonmember countries (non-OECD without China). A Bayesian hierarchical approach is used to model distributions of frequency and severity for accidents. This approach treats accident data as a multilevel system with subsets sharing specific characteristics. To model accident probabilities for a particular dam characteristic, this approach samples data from the entire data set, borrowing the strength across data set and enabling to model distributions even for subsets with scarce data. The modelled frequencies and severities are combined in frequency-consequence curves, showing that accidents for all dam purposes are more frequent in non-OECD (without China) and their maximum consequences are larger than in OECD countries. Multipurpose dams also have higher frequencies and maximum consequences than single-purpose dams. In addition, the developed methodology explicitly models time dependence to identify trends in accident frequencies over the analyzed period. Downward trends are found for almost all dam purposes confirming that technological development and implementation of safety measures are likely to have a positive impact on dam safety. The results of the analysis provide insights for dam risk management and decision-making processes by identifying key risk factors related to country groups and dam purposes as well as changes over time.     

Uncertainty Assessment in the Quantification of Risk Rates of Occupational Accidents

Occupational risk rates per hour of exposure have been quantified for 63 occupational accident types for the Dutch working population. Data were obtained from the analysis of more than 9,000 accidents that occurred over a period of six years in the Netherlands and resulted in three types of reportable consequences under Dutch law: (a) fatal injury, (b) permanent injury, and (c) serious recoverable injury requiring at least one day of hospitalization. A Bayesian uncertainty assessment on the value of the risk rates has been performed. Annual risks for each of the 63 occupational accident types have been calculated, including the variability in the annual exposure of the working population to the corresponding hazards. The suitability of three risk measures—individual risk rates, individual annual risk, and number of accidents—is examined and discussed.     

Who by Accident? The Social Morphology of Car Accidents

Prior studies in the sociology of accidents have shown that different social groups have different rates of accident involvement. This study extends those studies by implementing Bourdieu's relational perspective of social space to systematically explore the homology between drivers’ social characteristics and their involvement in specific types of motor vehicle accident. Using a large database that merges official Israeli road‐accident records with socioeconomic data from two censuses, this research maps the social order of road accidents through multiple correspondence analysis. Extending prior studies, the results show that different social groups indeed tend to be involved in motor vehicle accidents of different types and severity. For example, we find that drivers from low socioeconomic backgrounds are overinvolved in severe accidents with fatal outcomes. The new findings reported here shed light on the social regularity of road accidents and expose new facets in the social organization of death.     

Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning

Compared to the remarkable progress in risk analysis of normal accidents, the risk analysis of major accidents has not been so well‐established, partly due to the complexity of such accidents and partly due to low probabilities involved. The issue of low probabilities normally arises from the scarcity of major accidents’ relevant data since such accidents are few and far between. In this work, knowing that major accidents are frequently preceded by accident precursors, a novel precursor‐based methodology has been developed for likelihood modeling of major accidents in critical infrastructures based on a unique combination of accident precursor data, information theory, and approximate reasoning. For this purpose, we have introduced an innovative application of information analysis to identify the most informative near accident of a major accident. The observed data of the near accident were then used to establish predictive scenarios to foresee the occurrence of the major accident. We verified the methodology using offshore blowouts in the Gulf of Mexico, and then demonstrated its application to dam breaches in the United Sates.     

Learning from Nuclear Accident Experience

Statistical procedures are developed to estimate accident occurrence rates from historical event records, to predict future rates and trends, and to estimate the accuracy of the rate estimates and predictions. Maximum likelihood estimation is applied to several learning models and results are compared to earlier graphical and analytical estimates. The models are based on (1) the cumulative number of operating years, (2) the cumulative number of plants built, and (3) accidents (explicitly), with the accident rate distinctly different before and after an accident. The statistical accuracies of the parameters estimated are obtained in analytical form using the Fisher information matrix. Using data on core damage accidents in electricity producing plants , it is estimated that the probability for a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the equivalent frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year, partly due to the increasing population of plants.     

Insights into the Societal Risk of Nuclear Power Plant Accidents

The elements of societal risk from a nuclear power plant accident are clearly illustrated by the Fukushima accident: land contamination, long‐term relocation of large numbers of people, loss of productive farm area, loss of industrial production, and significant loss of electric capacity. NUREG‐1150 and other studies have provided compelling evidence that the individual health risk of nuclear power plant accidents is effectively negligible relative to other comparable risks, even for people living in close proximity to a plant. The objective of this study is to compare the societal risk of nuclear power plant accidents to that of other events to which the public is exposed. We have characterized the monetized societal risk in the United States from major societally disruptive events, such as hurricanes, in the form of a complementary cumulative distribution function. These risks are compared with nuclear power plant risks, based on NUREG‐1150 analyses and new MACCS code calculations to account for differences in source terms determined in the more recent SOARCA study. A candidate quantitative societal objective is discussed for potential adoption by the NRC. The results are also interpreted with regard to the acceptability of nuclear power as a major source of future energy supply.     

Intersystem Common Cause Analysis of a Diesel Generator Failure

The methodology and results reported in this paper are based on an analysis of a hypothetical accident occurring in a two unit power plant with shared systems (i.e., the diesel generator, the emergency service water, and the residual heat removal service water systems). The accident postulated is a loss of coolant accident (LOCA) in one out of two nuclear units in conjunction with a loss of offsite power (LOOP) and a failure of one out of four diesel generators to start. To analyze the intersystem effects, we needed to develop and apply a new methodology, intersystem common cause analysis (ICCA). The ICCA methodology revealed problems which were not identified by the traditional intrasystem failure modes and effects analysis (FMEA) performed earlier by the design teams. The first potential problem arises if one unit experiences a LOCA and diesel generator failure while one loop of its residual heat removal system is in the suppression pool cooling mode (SPCM); in this event, it is likely that minimum emergency core cooling system (ECCS) requirements will not be met. The second potential problem arises if a diesel generator fails while both units are simultaneously subjected to a controlled forced shutdown (a LOCA need not be postulated for either unit); in this event, it is likely that one unit will be required to use a heat removal path identified as off-normal in the final safety analysis report (FSAR) for the two unit plant. These and other potential concerns identified through application of the ICCA presented here were resolved early in the design phase.     

GIS‐Based Integration of Social Vulnerability and Level 3 Probabilistic Risk Assessment to Advance Emergency Preparedness,Planning, and Response for Severe Nuclear Power Plant Accidents

In the nuclear power industry, Level 3 probabilistic risk assessment (PRA) is used to estimate damage to public health and the environment if a severe accident leads to large radiological release. Current Level 3 PRA does not have an explicit inclusion of social factors and, therefore, it is not possible to perform importance ranking of social factors for risk‐informing emergency preparedness, planning, and response (EPPR). This article offers a methodology for adapting the concept of social vulnerability, commonly used in natural hazard research, in the context of a severe nuclear power plant accident. The methodology has four steps: (1) calculating a hazard‐independent social vulnerability index for the local population; (2) developing a location‐specific representation of the maximum radiological hazard estimated from current Level 3 PRA, in a geographic information system (GIS) environment; (3) developing a GIS‐based socio‐technical risk map by combining the social vulnerability index and the location‐specific radiological hazard; and (4) conducting a risk importance measure analysis to rank the criticality of social factors based on their contribution to the socio‐technical risk. The methodology is applied using results from the 2012 Surry Power Station state‐of‐the‐art reactor consequence analysis. A radiological hazard model is generated from MELCOR accident consequence code system, translated into a GIS environment, and combined with the Center for Disease Control social vulnerability index (SVI). This research creates an opportunity to explicitly consider and rank the criticality of location‐specific SVI themes based on their influence on risk, providing input for EPPR.     

Workplace Accidents and Workplace Safety: On Under‐reporting and Temporary Jobs

Statistics on workplace accidents do not always reflect workplace safety because workers under‐report for fear of job‐loss if they report having had an accident. Based on an analysis of fatal and non‐fatal workplace accidents and road accidents in 15 EU‐countries over the period 1995–2012, we conclude that there seems to be cyclical fluctuations in reporting of non‐fatal workplace accidents. Workers are less likely to report a workplace accident when unemployment is high. Furthermore, analyzing data from Italy and Spain on both workplace accidents and commuting accidents, we conclude that workers on temporary jobs are likely to under‐report accidents.     

Probabilistic Analysis of Domino Effects by Using a Matrix-Based Simulation Approach

Major industrial accidents occurring at so-called major hazard installations may cause domino accidents which are among the most destructive industrial accidents existing at present. As there may be many hazard installations in an area, a primary accident scenario may potentially propagate from one installation to another, and correlations exist in probability calculations of domino effects. In addition, during the propagation of a domino effect, accidents of diverse types may occur, some of them having a synergistic effect, while others do not. These characteristics make the analytical formulation of domino accidents very complex. In this work, a simple matrix-based modeling approach for domino effect analysis is proposed. Matrices can be used to represent the mutual influences of different escalation vectors between installations. On this basis, an analysis approach for accident propagation as well as a simulation-based algorithm for probability calculation of accidents and accident levels is provided. The applicability and flexibility of this approach is discussed while applying it to estimate domino probabilities in a case study.     

The Health Risks of Energy Production

Any personal or societal activity, besides bringing us benefits, also carries some risk. Energy production and use are no exceptions. In order to judge these risks, they must be quantified, and the risks of all alternative methods of producing this energy must then be compared among each other. These risks originate in many parts of the energy cycle; they are diverse in character and involve different parts of the population. It is therefore necessary to discriminate between many aspects of risk so that only reasonably comparable categories are compared. The results of a critical analysis of the international risk literature are presented, which are applicable to power production plants as they could be built today in central European countries. This review pays special attention to the possibility of severe accidents occurring, which attract so much attention in our modern societies. It turns out that the health risks of routine nuclear energy production are lower than the risks of other energy options, particularly for the general public. The probability of a severe accident occurring is far higher for all conventional energy options. Only the renewable systems utilizing the energy of the sun and the wind are not susceptible to severe accidents.