Multi-unit Accidents Research Articles

COFUN: A new tool for evaluating containment failure frequency and uncertainty

The feature of the COntainment Failure probability and Uncertainty aNalysis program (COFUN) is the quantification of the containment state. The probability factors used in probabilistic safety assessment (PSA) and the resulting outputs contain probability bands, so it is necessary to present the uncertainty bands as results. The uncertainty analysis process of the level 2 PSA is that a level 1 PSA uncertainty propagates to a level 2 PSA uncertainty. The basic event data including probability distribution were used for the level 1 PSA uncertainty analysis and probability distribution and priority of the fractional branch point were used for uncertainty analysis in a level 2 PSA. Once the input is ready, uncertainty analysis is performed via Monte-Carlo sampling. Finally, the uncertainty analysis can be performed for source term category (STC) and large early release frequency (LERF). One of the outstanding characteristics of the COFUN is to perform level 2 PSA for multi-unit accidents. The one of formats of multi-unit level 2 PSA is the combination of STCs but the combinations could be too many to acquire insight by STC combination itself. The COFUN provides a user-defined combination that makes STC combinations classified and enables the derivation of multi-unit accident LERF result.

Multi-unit PSA based risk evaluation framework for utilizing cross-tie systems for nuclear power plants

The Fukushima accident showed that the safety of multiple nuclear power plants (NPPs) at the same site could be jeopardized simultaneously. Since then, many studies have focused on developing strategies to prevent the spread of multi-unit accidents, with numerous countries establishing strategies to use mobile equipment. However, mobile equipment strategies are inherently accompanied by a high degree of uncertainty regarding operation success and duration because multiple organizations and personnel interact in various ways during multi-unit accident situations. Furthermore, supplementing current fixed equipment with additional mobile equipment requires extra resources. Therefore, cross-tie strategies that use currently installed fixed equipment can provide additional means to manage site risk with relatively few additional costs. This study proposes a multi-unit probabilistic safety assessment–based risk evaluation framework for utilizing cross-tie systems in NPPs and a modeling methodology to quantify the effectiveness of the cross-tie strategies. A case study was conducted to evaluate the risk reduction from using cross-tie strategies for emergency diesel generators and alternate AC diesel generators, which are power systems utilized in multi-unit loss of offsite power initiating events. It is expected that the developed framework and methodology can be utilized for other types of cross-tie strategies as well.

Multi-unit seismic probabilistic risk assessment: A Bayesian network perspective

The Fukushima Dai-ichi highlighted multi-unit accidents in nuclear power plant (NPP) probabilistic risk assessment (PRA). This paper focuses on multi-unit seismic PRA because seismic events are contributors to NPP site risk. This paper integrates works on modeling ground motion spatial variability at a NPP site and dependent seismic failures into a coherent and rigorous framework using Bayesian networks, and explores the relative importance of different types of correlation on NPP site-based risk metrics. A study of a hypothetical dual unit NPP site considered 15 cases with varying degrees of correlation in spatial ground motion (GM) and seismic failures. Based on the results, the current assumption of perfect GM correlation across a NPP site underestimates risk metrics that consider either unit experiencing core damage (CD) (site CD), which is not conservative. The risk metric that considers both units experiencing CD (concurrent CD) shows differences between the partial and perfect GM correlation assumptions when multiple component failures contribute to the CD in each unit. Within a GM correlation assumption, the site CD increases as the fragility correlation increases, a counterintuitive trend. The risk assessment case outlined in this paper provides more realistic results than the cases reflecting the current state of practice.

Development of Dependence Indexes for Multi-Unit Risk Assessment and its Estimation Using Copula

Since the Fukushima nuclear accident, the importance of evaluating risks for multiple units has been emphasized. With this motivation, surrogate metrics such as the core damage frequency (CDF) have been revised to represent those of a site, for instance, the site CDF (SCDF). While SCDF has been proposed to assess the risk of multiple units, it is desirable to provide an additional metric how much dependencies are contributed to the site. The conditional probability of multi-unit accident (CPMA) has also been proposed to describe dependency, however it handles a specific unit, not a site. Therefore, in this paper, the site CPMA and the site dependence index (SDI) are developed to describe inter-unit dependencies. The site CPMA is defined to apply to a site and uses the concept of CPMA. The SDI is derived from the concepts of banking stability used for financial linkages. As an alternative option, this paper also proposes a way to approximately estimate the proposed indexes using copulas and two-unit models for n-units in a site. The SDIs for four units at a site were evaluated using the copula-based model and the fully developed four-unit MUPSA model. The results from each model were comparable.

A preliminary site risk assessment

ABSTRACT Since the Fukushima accident, interest in the site probabilistic safety assessment (PSA) has increased worldwide. However, the standard process for the site risk assessment (SRA) has not yet been established. In addition, most of these studies have focused on the level 1 and 2 PSA. The offsite consequences of the multi-unit accidents may differ from that of the single-unit accidents, so that the full-scope site PSA is essential. In this paper, the preliminary site risk assessment has been performed. The level 1 multi-unit probabilistic safety assessment (MU-PSA) methodology considering the inter-unit dependency was established and carried out. And the mapping table method was adopted in the level 2 MU-PSA. For the level 3 MU-PSA, the grouping method was adopted to reduce the number of the source-term category combinations. Then, the early fatality risk and the latent cancer risk from the accidents in a site were estimated and the tendency of the site risk was analyzed. The process of performing a full-scope site PSA for a site with more than 2 units of varied reactor types presented through this application could contribute to developing the SRA methodology, risk metrics, and safety goals.

Projecting thyroid cancer risk to the general public from radiation exposure following hypothetical severe nuclear accidents in Canada

A robust emergency management framework can limit radiation exposures and effectively minimise the potentially devastating consequences of a nuclear emergency. We projected thyroid cancer risk resulting from two hypothetical severe nuclear accidents occurring at the Darlington nuclear power plant (NPP) located in Ontario, Canada. Single- and multi-unit accidents were considered. A dose assessment was previously performed using the MELCOR Accident Consequences Code System. The generic criteria used to select the appropriate protective actions are described in the Ontario Provincial Nuclear Emergency Response Plan (PNERP). We hypothesised protection actions only within the 10 kilometre (km) radius of the NPP given the time sensitivity of iodine thyroid blocking. The excess risk of developing thyroid cancer was projected using the US National Cancer Institute’s radiation risk assessment tool RadRAT. We projected zero dose, and subsequently zero risk of developing thyroid cancer for people living within 10 km of the NPP, due to effective implementation of selected protective actions. Based on centreline doses, at the 12 km radius, excess childhood thyroid cancer risks for a one-year-old female as the most critical receptor were projected to be approximately 600% and 130% compared to the baseline were projected for the single- and multi-unit scenarios, respectively. The risk of developing thyroid cancer was projected to be low for adults for both scenarios. The results of this modelling study provide insights into the effectiveness of protective actions in reducing radiation-related thyroid cancer risk when considering hypothetical severe nuclear accidents. Implementation of select protective actions protects the population living near the Darlington NPP. The projected increase of developing thyroid cancer for children living beyond 10 km could potentially be eliminated with additional mitigation measures specified in the PNERP.

Multiunit nuclear power plant accident scenarios and improvements including those based upon interviews with TEPCO engineers concerning the 2011 Fukushima accidents

In this work, we identify important multiunit risk factors based upon interviews with Tokyo Electric Power Company (TEPCO) engineers. These results provide first-hand information on multiunit risk factors that were important during the 2011 Fukushima accidents. Majority of the interviewees were involved in Fukushima Daiichi and Daini accident mitigation during March 2011. Interviewees worked at Daiichi and Daini sites and headquarters provided views of the accidents from different perspectives. They explained difficulties during the accident mitigation response phase due to lack of multiunit accident experience, and lack of necessary resources. In addition to the risk factors, corresponding site improvement suggestions are discussed based upon our reviews of the interview results. The identified risk factors and site improvement suggestions can be utilized as analysis subjects in future multiunit risk studies as well as references for nuclear sites to identify important multiunit risk vulnerabilities.

Formulation of A Risk Assessment Framework Capable of Analyzing Nuclear Power Multiunit Accident Scenarios

During the 2011 Fukushima Daiichi and Daini accidents, the interactions of multiple units at the same nuclear power plant site made accident mitigation more difficult compared to single unit sites. The accidents revealed important multiunit risk factors that typically are not identified by risk assessments for single-unit sites. Therefore, in order to obtain an integrated risk evaluation for multiunit sites, it is important to analyze accident scenarios involving interactions of multiple reactor units. However, such analyses are difficult due to the complexity of potential multiunit interactions. In the work reported here, a framework for analyzing multiunit accident scenarios involving inter-unit interactions is presented. The major steps of the framework are illustrated using a simplified two-unit site. The framework is capable of providing accident mitigation suggestions based upon analysis results. In this work, accident scenarios inspired by the Fukushima Daiichi and Daini experiences are selected as analysis subjects. By analyzing these scenarios and providing corresponding accident mitigation suggestions, the capabilities of the framework are illustrated.

A source term binning methodology for multi-unit consequence analyses

Public has concerned on a site risk after the Fukushima nuclear accidents. Therefore, multi-unit probabilistic safety assessment (MUPSA) has been researched actively because it is necessary to perform MUPSA for assessing a site risk. Most of the researches performed until now focus on multi-unit Level 1 PSA because it is the most important issue to model dependencies between units. However, multi-unit Level 3 PSA should be researched because many source term category (STC) combinations exist in multi-unit accidents. A binning methodology to group many STCs into fewer groups was developed in this research for considering this problem. First, a qualitative and quantitative logic tree to group similar STCs into a same group were developed, respectively. Second, five methods to designate representative MACCS inputs of each group were developed. Third, a verification procedure for the binning methodology was developed, and the most appropriate method for each logic tree was selected. The scheme of the binning methodology can be applied to any reactor type with several modifications such as the headings of the logic tree. Conclusively, the binning methodology will be an appropriate example of multi-unit Level 3 PSA and important element of a site risk estimation methodology.

Study on multi-unit level 3 PSA to understand a characteristics of risk in a multi-unit context

Since the Fukushima Daiichi accident in 2011, concerns for the safety of multi-unit Nuclear Power Plant (NPP) sites have risen. This is because more than 70% of NPP sites are multi-unit sites that have two or more NPP units and a multi-unit accident occurred for the first time. After this accident, Probability Safety Assessment (PSA) has been considered in many countries as one of the tools to quantitatively assess the safety for multi-unit NPP sites. One of the biggest concerns for a multi-unit accident such as Fukushima is that the consequences (health and economic) will be significantly higher than in the case of a single-unit accident. However, many studies on multi-unit PSA have focused on Level 1 & 2 PSA, and there are many challenges in terms of public acceptance due to various speculations without an engineering background. In this study, two kinds of multi-unit Level 3 PSA for multi-unit site have been carried out. The first case was the estimation of multi-unit risk with conservative assumptions to investigate the margin between multi-unit risk and QHO, and the other was to identify the effect of time delays in releases between NPP units on the same site. Through these two kinds of assessments, we aimed at investigating the level of multi-unit risk and understanding the characteristics of risk in a multi-unit context.

Human and organizational factors for multi-unit probabilistic safety assessment: Identification and characterization for the Korean case

Since the Fukushima Daiichi accident, there has been an emphasis on the risk resulting from multi-unit accidents. Human reliability analysis (HRA) is one of the important issues in multi-unit probabilistic safety assessment (MUPSA). Hence, there is a need to properly identify all the human and organizational factors relevant to a multi-unit incident scenario in a nuclear power plant (NPP). This study identifies and categorizes the human and organizational factors relevant to a multi-unit incident scenario of NPPs based on a review of relevant literature. These factors are then analyzed to ascertain all possible unit-to-unit interactions that need to be considered in the multi-unit HRA and the pattern of interactions. The human and organizational factors are classified into five categories: organization, work device, task, performance shaping factors, and environmental factors. The identification and classification of these factors will significantly contribute to the development of adequate strategies and guidelines for managing multi-unit accidents. This study is a necessary initial step in developing an effective HRA method for multiple NPP units in a site.

Analysis of the technical status of multiunit risk assessment in nuclear power plants

Abstract Since the Fukushima Daiichi nuclear disaster, concern and worry about multiunit accidents have been increasing. Korea has a higher urgency to evaluate its site risk because its number of nuclear power plants (NPPs) and population density are higher than those in other countries. Since the 1980s, technical documents have been published on multiunit probabilistic safety assessment (PSA), but the Fukushima accident accelerated research on multiunit PSA. It is therefore necessary to summarize the present situation and draw implications for further research. This article reviews journal and conference papers on multiunit or site risk evaluation published between 2011 and 2016. The contents of the reviewed literature are classified as research status, initiators, and methodologies representing dependencies, and the insights and conclusions are consolidated. As of 2017, the regulatory authority and nuclear power utility have launched a full-scale project to assess multiunit risk in Korea. This article provides comprehensive reference materials on the necessary enabling technology for subsequent studies of multiunit or site risk assessment.

Feasibility of shared use of alternative AC diesel generator under dual-unit station blackout

ABSTRACTThe Fukushima accident raised concerns about the preparation level of nuclear power plants against multi-unit accidents. Under dual-unit station blackout (SBO), it is generally considered that the alternate AC diesel generator (AAC DG) is connected to only one unit, and core damage is inevitable in the other unit. Based on the lessons from Fukushima Daiichi Units 5 and 6, which successfully mitigated the situation by sharing one emergency diesel generator, this study investigates the feasibility of shared use of the AAC DG under a dual-unit SBO. A thermal-hydraulic (TH) code analysis with conservative assumptions demonstrated that both units are able to withstand and recover from dual-unit SBO by the shared use of the AAC DG. The review of the TH code analysis results by changing the conservative assumptions to more realistic assumptions also provide strong support for the same conclusion. After being properly incorporated into operational procedures, such as emergency operating procedures, the shared use of the AAC DG under a dual-unit SBO is expected to significantly reduce plant risk.

Multiunit Accident Contributions to Quantitative Health Objectives: A Safety Goal Policy Analysis

In 1986 the U.S. Nuclear Regulatory Commission (USNRC) implemented a safety goal policy in response to the 1979 Three Mile Island accident. This policy addresses the question, “How safe is safe enough?” by specifying quantitative health objectives (QHOs) for comparison with average individual early fatality and latent cancer fatality risk results computed from nuclear power plant (NPP) probabilistic risk assessments (PRAs). Comparisons of PRA results to the QHOs or other subsidiary numerical objectives are used to determine whether proposed regulatory actions should be rejected based on potential safety benefit relative to the level of residual risk to the public, before performing detailed cost-benefit analyses to determine whether they could be justified on their net value basis. Lessons learned from recent operational experience—including the 2011 Fukushima accident—indicate that concurrent accidents involving multiple units at a shared site can occur with non-negligible frequency. Yet, risk contributions from such scenarios are excluded by policy from safety goal evaluations for the nearly 60% of the U.S. NPP sites that include multiple units. The objectives of this paper are to (1) present an approach for estimating multiple unit risk metrics for comparison with the safety goal QHOs using accident scenarios from the State-of-the-Art Reactor Consequence Analyses (SOARCA) Project; and (2) using this approach, evaluate the effects of including risk contributions from concurrent multiunit accidents in safety goal evaluations. The approach is demonstrated using a two-unit case study involving two representative NPP sites that are each comprised of two co-located operating reactor units. This paper (1) summarizes results and insights obtained from the two-unit case study; (2) describes additional considerations for applying methods to sites comprised of two or more units, including other major radiological sources; and (3) identifies potential areas for further research.

Study on Quantification Method Based on Monte Carlo Sampling for Multiunit Probabilistic Safety Assessment Models

Abstract In Korea, many nuclear power plants operate at a single site based on geographical characteristics, but the population density near the sites is higher than that in other countries. Thus, multiunit accidents are a more important consideration than in other countries and should be addressed appropriately. Currently, there are many issues related to a multiunit probabilistic safety assessment (PSA). One of them is the quantification of a multiunit PSA model. A traditional PSA uses a Boolean manipulation of the fault tree in terms of the minimal cut set. However, such methods have some limitations when rare event approximations cannot be used effectively or a very small truncation limit should be applied to identify accident sequence combinations for a multiunit site. In particular, it is well known that seismic risk in terms of core damage frequency can be overestimated because there are many events that have a high failure probability. In this study, we propose a quantification method based on a Monte Carlo approach for a multiunit PSA model. This method can consider all possible accident sequence combinations in a multiunit site and calculate a more exact value for events that have a high failure probability. An example model for six identical units at a site was also developed and quantified to confirm the applicability of the proposed method.

An event classification schema for evaluating site risk in a multi-unit nuclear power plant probabilistic risk assessment

Today, Probabilistic Risk Assessments (PRAs) at multi-unit nuclear power plants consider risk from each unit separately and consider dependencies and interactions between the units informally and on an ad hoc basis. The accident at the Fukushima nuclear power station underlined the importance and possibility of multi-unit accidents. These interactions make the operation of multiple units dependent on each other and should be formally accounted for in PRAs. In order to effectively account for these risks in a multi-unit PRA, six main dependence classifications have been identified: initiating events, shared connections, identical components, proximity dependencies, human dependencies, and organizational dependencies. This paper discusses these six classifications and the nature of their resulting dependence between multiple units. As a validation of the classification, this paper will also discuss multi-unit events that have occurred in operating plants. Finally, the paper will present existing methodologies that could be used to more formally quantify unit-to-unit dependencies in the PRAs for each classification.