Scheduling Updates of Probabilistic Risk Assessments: The Arkansas Nuclear One-Unit 1 Experience

This paper presents the results of a study that identified how often a probabilistic risk assessment (PRA)should be updated to accommodate the changes that take place at nuclear power plants. Based on a 7-year analysis of design and procedural changes at one plant, we consider 5 years to be the maximum interval for updating PRAs. This conclusion is preliminary because it is based on the review of changes that occurred at a single plant, and it addresses only PRAs that involve a Level 1 analysis (i.e., a PRA including calculation of core damage frequency only). Nevertheless, this conclusion indicates that maintaining a useful PRA requires periodic updating efforts. However, the need for this periodic update stems only partly from the number of changes that can be expected to take place at nuclear power plants–changes that individually have only a moderate to minor impact on the PRA, but whose combined impact is substantial and necessitates a PRA update. Additionally, a comparison of two generations of PRAs performed about 5 years apart indicates that PRAs must be periodically updated to reflect the evolution of PRA methods. The most desirable updating interval depends on these two technical considerations as well as the cost of updating the PRA. (Cost considerations, however, were beyond the scope of this study.)     

京郊民俗生态旅游发展探讨——以怀柔区北宅村为例

民俗生态旅游是京郊乡村旅游的一种重要形式。本文运用参与式快速评估(PRA)方法,结合访谈和问卷调查,从村落尺度的微观角度,对北宅村民俗生态旅游发展现状进行了快速诊断。针对基础设施和村域规划、客源可持续性、产品设计和营销、内部管理和运营机制、村域协调发展和收入均衡等方面的问题,提出了相关的对策建议。     

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.     

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.     

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.     

Probabilistic Risk Assessment of Wastes Buried in the Ground

The differences between probabilistic risk assessment (PRA) and safety analysis (SA) are discussed, and it is shown that PRA is more suitable than SA for determining the acceptability of a technology. Since a PRA by the fault tree-event tree analysis method used for reactor safety studies does not seem to be practical for buried waste, an alternative approach is suggested using geochemical analogs. This method is illustrated for the cases of high-level and low-level radioactive waste and for chemical carcinogens released in coal burning.     

Integrating Software into PRA: A Software-Related Failure Mode Taxonomy

Probabilistic risk assessment is a methodology to assess the probability of failure or success of a mission. Results provided by the risk assessment methodology are used to make decisions concerning choice of upgrades, scheduling of maintenance, decision to launch, etc. However, current PRA neglects the contribution of software to the risk of failure of the mission. Our research has developed a methodology to account for the impact of software to system failure. This article focuses on an element of the approach: a comprehensive taxonomy of software-related failure modes. Application of the taxonomy is discussed in this article. A validation of the taxonomy and conclusions drawn from this validation effort are described. Future research is also summarized.     

Importance of Uncertainty and Variability to Predicted Risks from Trophic Transfer of PCBs in Dredged Sediments

Biomagnification of organochlorine and other persistent organic contaminants by higher trophic level organisms represents one of the most significant sources of uncertainty and variability in evaluating potential risks associated with disposal of dredged materials. While it is important to distinguish between population variability (e.g., true population heterogeneity in fish weight, and lipid content) and uncertainty (e.g., measurement error), they can be operationally difficult to define separately in probabilistic estimates of human health and ecological risk. We propose a disaggregation of uncertain and variable parameters based on: (1) availability of supporting data; (2) the specific management and regulatory context (in this case, of the U.S. Army Corps of Engineers/U.S. Environmental Protection Agency tiered approach to dredged material management); and (3) professional judgment and experience in conducting probabilistic risk assessments. We describe and quantitatively evaluate several sources of uncertainty and variability in estimating risk to human health from trophic transfer of polychlorinated biphenyls (PCBs) using a case study of sediments obtained from the New York-New Jersey Harbor and being evaluated for disposal at an open water off-shore disposal site within the northeast region. The estimates of PCB concentrations in fish and dietary doses of PCBs to humans ingesting fish are expressed as distributions of values, of which the arithmetic mean or mode represents a particular fractile. The distribution of risk values is obtained using a food chain biomagnification model developed by Gobas by specifying distributions for input parameters disaggregated to represent either uncertainty or variability. Only those sources of uncertainty that could be quantified were included in the analysis. Results for several different two-dimensional Latin Hypercube analyses are provided to evaluate the influence of the uncertain versus variable disaggregation of model parameters. The analysis suggests that variability in human exposure parameters is greater than the uncertainty bounds on any particular fractile, given the described assumptions.     

Management Errors and System Reliability: A Probabilistic Approach and Application to Offshore Platforms

Probabilistic risk analysis, based on the identification of failure modes, points to technical malfunctions and operator errors that can be direct causes of system failure. Yet component failures and operator errors are often rooted in management decisions and organizational factors. Extending the analysis to identify these factors allows more effective risk management strategies. It also permits a more realistic assessment of the overall failure probability. An implicit assumption that is often made in PRA is that, on the whole, the system has been designed according to specified norms and constructed as designed. Such an analysis tends to overemphasize scenarios in which the system fails because it is subjected to a much higher load than those for which it was designed. In this article, we find that, for the case of jacket-type offshore platforms, this class of scenarios contributes only about 5% of the failure probability. We link the PRA inputs to decisions and errors during the three phases of design, construction, and operation of platforms, and we assess the contribution of different types of error scenarios to the overall probability of platform failure. We compute the benefits of improving the design review, and we find that, given the costs involved, improving the review process is a more efficient way to increase system safety than reinforcing the structure.