A Unified Approach for Calculating Core Melt Frequency Caused by Internal and External Initiating Events

A unified approach for calculating the core melt frequency of a specific reactor caused by both internal and external accident initiators is demonstrated. Two classes of internal initiators are examined: transients, of which turbine trip is the chosen example, and loss-of-coolant events of various sizes. The concepts of hazard and fragility analysis first proposed for seismic risk analysis are linked to the frequencies of internal initiating events, and to the plant response as a function of the event intensity. Uncertainties are propagated using discrete probability distribution (DPD) arithmetic. Advantages of this approach include mathematical and conceptual consistency, and an improved uncertainty analysis, which are important considerations if risk studies are to be utilized in decision-making based on quantitative safety goals.     

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.     

Risk-Based Ranking of Dominant Contributors to Maritime Pollution Events

This report describes a conceptual approach for identifying dominant contributors to risk from maritime shipping of hazardous materials. Maritime transportation accidents are relatively common occurrences compared to more frequently analyzed contributors to public risk. Yet research on maritime safety and pollution incidents has not been guided by a systematic, risk-based approach. Maritime shipping accidents can be analyzed using event trees to group the accidents into "bins," or groups, of similar characteristics such as type of cargo, location of accident (e.g., harbor, inland waterway), type of accident (e.g., fire, collision, grounding), and size of release. The importance of specific types of events to each accident bin can be quantified. Then the overall importance of accident events to risk can be estimated by weighting the events' individual bin importance measures by the risk associated with each accident bin.     

All The Same? On a Certain Pattern in Cross-National Death Risk

This article considers whether a nation that fares relatively well (or badly) on a particular dimension of mortality risk tends also to do so on others. Working with 2016 data from the Global Burden of Disease (GBD) Study, we focus on six causes of premature death: transport accidents, other accidents, homicide, early-childhood diseases, and both communicable and noncommunicable diseases beyond early childhood. We consider data from all 26 nations that had populations of at least 50 million in 2016, as well as 15 clusters of smaller nations that are similar in longevity (e.g., Scandinavia). We use an analytic method that facilitates useful comparisons across nations, for it recognizes that some potential death risks can be underestimated because citizens die sooner from other causes. We estimate reductions in lifespan from each of the six causes relative to natural lifespan as defined by GBD. It emerges that, for all 15 pairings among the six causes, these reductions are positively correlated. We introduce metrics to summarize a nation's overall “safety status,” and find that losses of longevity because of premature deaths are nearly three decades fewer in the safest countries than in the least safe ones. Turning to possible explanations for the cross-national differences, we find a strong association between a nation's safety status and both its economic wherewithal as indicated by the 2016 GDP per capita (adjusted for purchasing power parity) and its income inequality as reflected by its Gini coefficient.     

Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel‐Induced Pipeline Damage

Tunneling excavation is bound to produce significant disturbances to surrounding environments, and the tunnel‐induced damage to adjacent underground buried pipelines is of considerable importance for geotechnical practice. A fuzzy Bayesian networks (FBNs) based approach for safety risk analysis is developed in this article with detailed step‐by‐step procedures, consisting of risk mechanism analysis, the FBN model establishment, fuzzification, FBN‐based inference, defuzzification, and decision making. In accordance with the failure mechanism analysis, a tunnel‐induced pipeline damage model is proposed to reveal the cause‐effect relationships between the pipeline damage and its influential variables. In terms of the fuzzification process, an expert confidence indicator is proposed to reveal the reliability of the data when determining the fuzzy probability of occurrence of basic events, with both the judgment ability level and the subjectivity reliability level taken into account. By means of the fuzzy Bayesian inference, the approach proposed in this article is capable of calculating the probability distribution of potential safety risks and identifying the most likely potential causes of accidents under both prior knowledge and given evidence circumstances. A case concerning the safety analysis of underground buried pipelines adjacent to the construction of the Wuhan Yangtze River Tunnel is presented. The results demonstrate the feasibility of the proposed FBN approach and its application potential. The proposed approach can be used as a decision tool to provide support for safety assurance and management in tunnel construction, and thus increase the likelihood of a successful project in a complex project environment.     

A Review of Plant Specific PRAs

A large number of PRA studies have been completed for specific plants at specific sites. From these studies, taken individually or collectively, many significant insights have evolved into items important to risk and safety. The content of this paper is primarily based on the material contained in the EPRI funded review of five PRA studies: Big Rock Point, Zion, Limerick, Grand Gulf, and Arkansas Nuclear One. The first three were the utility sponsored studies publicly available at the time of project initiation while the other two were deemed representative of the NRC's RSSMAP and IREP programs respectively. The results of PRA studies are usually expressed in terms of core melt frequencies, radionuclide release frequencies, and frequencies of occurrence of different reactor accident consequences (e.g., early and latent fatalities) depending on the level of PRA. These subjects are prominently addressed in this paper. One of the results of a PRA study is identification of a relatively small number of accident sequences that represent the dominant contributors to core melt. An analysis of the salient features of the dominant accident sequences from eleven PRA's yielded a characterization of accident sequence categories discussed at some length. Impact of external events is discussed very briefly. Next to an explicit quantification of public risk or core melt frequency, the identification of specific safety concerns and the evaluation of possible solutions to implement risk management are probably the best recognized and most widely used applications of PRA. Several illustrative examples are briefly discussed. Human interactions are extremely important contributors to safety and reliability of the plants. A review of PRA studies concluded that it was necessary to account for five types of human interactions; some of which may mitigate while others may exacerbate an accident sequence.     

Risk Management of Domino Effects Considering Dynamic Consequence Analysis

Domino effects are low‐probability high‐consequence accidents causing severe damage to humans, process plants, and the environment. Because domino effects affect large areas and are difficult to control, preventive safety measures have been given priority over mitigative measures. As a result, safety distances and safety inventories have been used as preventive safety measures to reduce the escalation probability of domino effects. However, these safety measures are usually designed considering static accident scenarios. In this study, we show that compared to a static worst‐case accident analysis, a dynamic consequence analysis provides a more rational approach for risk assessment and management of domino effects. This study also presents the application of Bayesian networks and conflict analysis to risk‐based allocation of chemical inventories to minimize the consequences and thus to reduce the escalation probability. It emphasizes the risk management of chemical inventories as an inherent safety measure, particularly in existing process plants where the applicability of other safety measures such as safety distances is limited.     

Safety Management and Public Spaces: Restoring Balance

Since 2000, the reputation of health and safety in the United Kingdom has been tarnished, so much so that it has become the subject of both a media circus and a government inquiry. This not only threatens the worthy goals of health and safety, but also impacts upon the associated tool of risk assessment itself such that "risk assessment" is increasingly seen by the public at large as a term inviting ridicule, even abuse. The main thrust of the government's examination of health and safety has been its concern that safety requirements were placing a disproportionate burden on business. However, there is another source of discontent, which is public chagrin over the impact of injury control measures upon life beyond the conventional workplace, in particular upon the public spaces that people frequent in their leisure time and on the activities they engage in there. This article provides a perspective on this second dimension of the crisis in confidence. It describes how many U.K. agencies with responsibilities for a wide portfolio of public amenities ranging from the provision of play spaces for the young to the management of publicly accessible countryside, the maintenance of urban and rural trees, the stewardship of sites of cultural heritage, and the pursuit of outdoor educational activities have responded to some conflicts posed to their services by the new safety culture. It concludes with a discussion of implications for the management of public space and for risk assessment itself.     

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.     

“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.     

Risk Prevention and Policy-Making in Automatic Systems

Accidents with automatic production systems are reported to be on the order of one in a hundred or thousand robot-years, while fatal accidents are found to occur one or two orders of magnitude less frequently. Traditions in occupational safety tend to seek for safety targets in terms of zero severe accidents for automatic systems. Decision-making requires a risk assessment balancing potential risk reduction measures and costs within the cultural environment of a production company. This paper presents a simplified procedure which acts as a decision tool. The procedure is based on a risk concept approaching prevention both in a deterministic and in a probabilistic manner. Eight accident scenarios are shown to represent the potential accident processes involving robot interactions with people. Seven prevention policies are shown to cover the accident scenarios in principle. An additional probabilistic approach may indicate which extra safety measures can be taken against what risk reduction and additional costs. The risk evaluation process aims at achieving a quantitative acceptable risk level. For that purpose, three risk evaluation methods are discussed with respect to reaching broad consensus on the safety targets.     

Deep Learning Models for Health and Safety Risk Prediction in Power Infrastructure Projects

Inappropriate management of health and safety (H&S) risk in power infrastructure projects can result in occupational accidents and equipment damage. Accidents at work have detrimental effects on workers, company, and the general public. Despite the availability of H&S incident data, utilizing them to mitigate accident occurrence effectively is challenging due to inherent limitations of existing data logging methods. In this study, we used a text-mining approach for retrieving meaningful terms from data and develop six deep learning (DL) models for H&S risks management in power infrastructure. The DL models include DNN_classify (risk or no risk), DNN_reg1 (loss time), DNN_reg2 (body injury), DNN_reg3 (plant and fleet), DNN_reg4 (equipment), and DNN_reg5 (environment). An H&S risk database obtained from a leading UK power infrastructure construction company was used in developing the models using the H2O framework of the R language. Performances of DL models were assessed and benchmarked with existing models using test data and appropriate performance metrics. The overall accuracy of the classification model was 0.93. The average R² value for the five regression models was 0.92, with mean absolute error between 0.91 and 0.94. The presented results, in addition to the developed user-interface module, will help practitioners obtain a better understanding of H&S challenges, minimize project costs (such as third-party insurance and equipment repairs), and offer effective strategies to mitigate H&S risk.     

An Evaluation of Alternative Safety Criteria for Nuclear Power Plants

Safety criteria for frequency of nuclear-reactor accidents and for reactor-induced risk to individuals and to society are evaluated on the basis of their comprehensiveness, clarity, recognition of uncertainty, practicability, defensibility, simplicity, and internal consistency. Many criteria were found to be comprehensive and practicable; few completely satisfied the other evaluation standards. A consensus inferred from the most favorably evaluated criteria would allow between 1.0time10^-4 and 1.0time10^-3 core melts per reactor year, between 1.0time10^-6 and 2.0time10^-5 fatalities per reactor year per individual, and a total exposure in the United States of between 1000 and 10,000 person rems per reactor year. This consensus is consistent with the criteria proposed in NUREG0880.     

The Management of Risk: Application to the Welding Industry

The management of health risk in the welding industry is considered based on a discussion of the major sources of harm to welders arising from their employment (e.g., accidents and inhalation of fumes and gases). It is shown that present methods neither enable the assessment of the societal and human costs involved, nor permit the specific association of delayed health effects to occupational fume exposures. Reported accidents usually occur early in the working experience and contribute to a large number of working days lost, while fume exposures may contribute to a reduction in life quality which is poorly defined. It is concluded that risk management can only be attempted after much more information is made available concerning the origin, nature, and duration of health effects, especially as related to individual welding technologies and applications.     

Perceived Risks of Conventional and Organic Produce: Pesticides, Pathogens, and Natural Toxins

Public risk perceptions and demand for safer food are important factors shaping agricultural production practices in the United States. Despite documented food safety concerns, little attempt has been made to elicit consumers' subjective risk judgments for a range of food safety hazards or to identify factors most predictive of perceived food safety risks. In this study, over 700 conventional and organic fresh produce buyers in the Boston area were surveyed for their perceived food safety risks. Survey results showed that consumers perceived relatively high risks associated with the consumption and production of conventionally grown produce compared with other public health hazards. For example, conventional and organic food buyers estimated the median annual fatality rate due to pesticide residues on conventionally grown food to be about 50 per million and 200 per million, respectively, which is similar in magnitude to the annual mortality risk from motor vehicle accidents in the United States. Over 90% of survey respondents also perceived a reduction in pesticide residue risk associated with substituting organically grown produce for conventionally grown produce, and nearly 50% perceived a risk reduction due to natural toxins and microbial pathogens. Multiple regression analyses indicate that only a few factors are consistently predictive of higher risk perceptions, including feelings of distrust toward regulatory agencies and the safety of the food supply. A variety of factors were found to be significant predictors of specific categories of food hazards, suggesting that consumers may view food safety risks as dissimilar from one another. Based on study findings, it is recommended that future agricultural policies and risk communication efforts utilize a comparative risk approach that targets a range of food safety hazards.     

Communicating Worst-Case Scenarios: Neighbors'' Views of Industrial Accident Management

The prospect of industrial accidents motivated the U.S. Congress to require in the Clean Air Act of 1990 that manufacturing facilities develop Risk Management Plans (RMP) to submit to the U.S. Environmental Protection Agency (USEPA) by July 1999. Industry worried that the requirement to communicate to the public a "worst-case scenario" would arouse unnecessary and counterproductive fears among industry neighbors. We report here the results of focus groups and surveys with such neighbors, focusing particularly upon their reactions to messages about a hypothetical worst-case scenario and management of these risks by industry, government, and other parties. Our findings confirmed our hypotheses that citizens would be skeptical of the competence and trustworthiness of these managers and that this stance would color their views of industrial-facility accident risks. People with job ties to industry or who saw industrial benefits to the community as exceeding its risks had more positive views of industrial risks, but still expressed great concern about the risk and doubt about accident management. Notwithstanding these reactions, overall respondents welcomed this and other related information, which they wanted their local industries to supply. Respondents were not more reassured by additional text describing management of accidents by government and industry. However, respondents did react very positively to the concept of community oversight to review plant safety. Claims about the firm's moral obligation or financial self-interest in preventing accidents were also received positively. Further research on innovative communication and management of accident risks is warranted by these results, even before recent terrorist attacks made this topic more salient.     

Sensitivity Analysis for Critical Control Points Determination and Uncertainty Analysis to Link FSO and Process Criteria: Application to Listeria monocytogenes in Soft Cheese Made from Pasteurized Milk

Microbiological food safety is an important economic and health issue in the context of globalization and presents food business operators with new challenges in providing safe foods. The hazard analysis and critical control point approach involve identifying the main steps in food processing and the physical and chemical parameters that have an impact on the safety of foods. In the risk‐based approach, as defined in the Codex Alimentarius, controlling these parameters in such a way that the final products meet a food safety objective (FSO), fixed by the competent authorities, is a big challenge and of great interest to the food business operators. Process risk models, issued from the quantitative microbiological risk assessment framework, provide useful tools in this respect. We propose a methodology, called multivariate factor mapping (MFM), for establishing a link between process parameters and compliance with a FSO. For a stochastic and dynamic process risk model of in soft cheese made from pasteurized milk with many uncertain inputs, multivariate sensitivity analysis and MFM are combined to (i) identify the critical control points (CCPs) for throughout the food chain and (ii) compute the critical limits of the most influential process parameters, located at the CCPs, with regard to the specific process implemented in the model. Due to certain forms of interaction among parameters, the results show some new possibilities for the management of microbiological hazards when a FSO is specified.     

Benchmarking Safety Climate in Hazardous Environments: A Longitudinal, Interorganizational Approach

Safety climate is an important element of organizational reliability. This study applied benchmarking strategies for monitoring safety climate across nine North Sea oil and gas installations that were surveyed in consecutive years. Examination of absolute changes in safety climate complemented the benchmarking approach. Discriminant function analyses (DFA) identified the elements of safety climate predictive of self-reported accidents; correlational analyses were applied to the scale scores and accident proportions across the year period. Absolute improvements were substantial, with safety climate profiles converging in the second year. Large relative improvements were also observed. DFA highlighted perceived management commitment to safety and willingness to report accidents as significant predictors of personal accident involvement. Changes in perceived management commitment to safety were closely associated with changes in safety behavior.