Multi-unit Site Research Articles

MUPSA-based evaluation of portable equipment utilization for risk reduction in nuclear power plants: Framework and case study

Based on the lessons from the Fukushima accident, new strategies to mitigate the spread of accidents in nuclear power plants have been established that consider portable equipment. The diverse and flexible coping strategies (FLEX) and multi-barrier accident coping strategy (MACST) based on the utilization of portable equipment are being adopted in case of an extended loss of all AC power and loss of ultimate heat sink. In this context, the establishment of specific strategies for utilizing portable equipment has emerged as an important issue. This study proposes a multi-unit probabilistic safety assessment (MUPSA)-based evaluation framework consisting of several steps to quantitatively assess the reduction in risk from the use of portable equipment at a multi-unit site, which can provide a basis for establishing optimal portable equipment strategies. According to the framework, after first defining the scope of the evaluation, risk-significant types of portable equipment are selected and the scenarios are analyzed. Risk reduction is then evaluated using modified MUPSA models according to the deployment of the portable equipment. A case study was conducted for an internal loss of off-site power (LOOP) and seismic LOOP focusing on how to evaluate the effectiveness of portable equipment through the developed framework.

Human reliability analysis of shared equipment in multi-unit site

ABSTRACT Currently, there is no mature method for calculating the probability of human failure that occurs in multi-unit. In this study, the single-unit HRA is expanded and improved, and we have compiled a method flow suitable for human reliability analysis in multi-unit. This method considers the communication of commands between different organizations and analyzes the equipment shared by multiple units. This research demonstrates the feasibility of the THERP+HCR method to calculate the human-caused failure probability of multiple units. In this paper, the human failure probability of the fifth emergency diesel engine is investigated during a station blackout at a multi-unit site. The calculated failure probability of personnel deploying a fifth diesel-engine between two units is 0.1061, which is higher than the failure probability of a single unit, and the consequences of failure of a dual-unit invocation would be more severe. Due to the uncertainty of some conditions and parameters, the variation of the failure probability after sensitivity analysis ranges from–0.0846–0.2083. Involvement of more organizations during the accident increases the risk of the plant site. Among the most influential factors on the probability of failure are the presence of inspection clauses in the operating procedures and the level of tension of personnel.

Assessing the Impact of Common Cause Failures on Site Risk within Level 1 Multi-Unit PSA

Common cause failures (CCFs) may lead to the simultaneous unavailability or failure of numerous components in the nuclear power plant because of the existence of a shared cause when an initiating event disrupts the normal functioning of nuclear power plants. The presence of common cause failures (intra-unit and inter-unit) can be recognized in a multi-unit probabilistic safety assessment (MUPSA) as a crucial dependency factor that can influence accident scenarios and the core damage frequency (CDF), as CCF may affect the availability and proper operation of mitigating systems. Since such failures are likely to significantly undermine the benefits of the concept of redundancy in nuclear power plant systems, it is necessary to identify the CCFs that contribute to the core damage in a multi-unit site and analyse their overall quantitative magnitude and qualitative proportions. In this study, a twin-unit generic pressurized water reactor (PWR) nuclear plant is modeled using the AIMS-PSA software. For the loss-of-offsite-power (LOOP) and station blackout (SBO) events, the site CDF was calculated, and the cut-sets produced by this quantification were examined for the modeled CCF basic events in the fault trees. The quantitative and qualitative contributions of the CCFs to the frequency of site core damage were examined. CCFs in the modeled fault trees contributed to 4.58% to the site CDF of the combined LOOP followed by SBO event. In the LOOP event alone that leads to core damage, the CCF contributed 4.58% to the site CDF while CCFs contributed 17.19% to the site CDF in the SBO event alone that leads to core damage. With CCF events considered in the modeling process, the site CDF estimated with CCF events increased by 7.53% in the combined LOOP followed by SBO event. In the LOOP event alone that leads to core damage, inclusion of CCF events in the modeling increased the site CDF by 7.42%. A 15.66% increase in site CDF was recorded in the SBO event alone that leads to core damage as compared to modeling without CCF events. The results show how crucial the common cause failure contribution is to site CDF. The safety of the nuclear plant at a site is impacted by an increase in site CDF when common cause failures are considered. The various CCF fundamental event compositions and their percentage contributions were explicitly examined by the minimal cut-sets which leads to core damage in the units. In conclusion, this study’s findings can help us better understand how CCFs increase multi-unit site risk and can also act as a starting point for future studies on the qualitative and quantitative categorizations of CCF effects within MUPSA.

Estimating the adverse effects of inter-unit radioactive release on operator actions at a multi-unit site

Radioactive materials released from a nuclear power plant can degrade the performance of plant operators by disturbing their physical actions, complicating the mitigation procedures, or heightening their psychological stress. This study provides an approach to quantitatively estimate the inter-unit radioactive influence at a multi-unit site by using a conventional probabilistic safety analysis (PSA) model. Three steps are suggested as follows: (1) select the risk-significant core damage sequences of the unit(s) that release radioactive materials, (2) select the risk-significant human failure events (HFEs) at the unit(s) that are affected by the radioactive releases, and (3) develop an integrated PSA model with a fault tree linking approach. The effects of release timing and operator action timing are also considered, called timing effects. To demonstrate the applicability of the approach, the risk of five identical units at a multi-unit site was quantitatively evaluated with a loss of offsite power initiating event as case studies. The multi-unit core damage frequency increased by a maximum factor of 5.7 without consideration of timing effects, while it increased up to 19 percent with consideration of timing effects.

Studies on the optimal mitigation strategy of extended SBO for the isolated multi-unit NPP site

The Nuclear Power Plant in the isolated Multi-Unit site eventually reaches the core damage if it undergoes the extended Station Blackout with the depletion of available resources. However, the coping time can be maximized by the optimal strategy with proper operator’s actions so that the operator can prepare further mitigation action to prevent core damage. The resources-based mitigation strategy framework was developed from the insights of the probabilistic model and deterministic model, which consider monitoring of plant conditions, available decay heat removal systems, available power sources, and water sources depending on the time. The maximum coping time is estimated for various cases with MARS-KS1.4 code for APR1400 and combined with a corresponding probabilistic model for each accident sequence based on the accident conditions and the resources with additional human actions.

Calculation approach to building DCGLs of waste treatment facilility for Kori unit 1 decommissioning and comparative analysis of the results

The Derived Concentration Guideline Levels (DCGLs) of remaining buildings in decommissioning site realistically need to be considered because all nuclear power plants in Korea are operated with the adjacent plant in multi-unit site. In addition, a few buildings are expected to be utilized for the decommissioning such as waste treatment facility to reduce the final disposal volume of radioactive waste. Therefore, DCGLs of buildings postulated for the decommissioning of Kori site have been assessed by using RESRAD-BUILD code. As a result, DCGLs were derived, reflecting the site reuse criteria and input prameters based on site conditions and assumptions, and compared and analyzed how they differ from DCGLs of other nuclear plants depending on radionuclides. The occupancy and renovation scenarios were applied and more than half of the target radionuclides were conservatilvely evaluated in the occupancy scenarion, while some were evaluated in the renovation scenario. The approach and methodology presented in this paper, which can be considered at the level of the transition phase, can be utilized for deriving results that reflect reality at the time of license termination.

The risk analysis of the electrical Cross-tie for extended Station Blackout in Multi-Unit site

The SBO is defined as the events of Loss of Offsite Power (LOOP) combined by loss of dedicated Emergency Diesel Generators(EDGs) for each unit. The SBO can be also extended when the shared Diesel Generator (AAC-DG) is lost additionally. The Electrical Cross-tie (ECT) is the concept of sharing other unit’s dedicated EDG to the unit under extended SBO in the multi-unit NPP site. We re-evaluate the risk of the extended SBO with the ECT option in Single Unit PRA considering Multi-Unit Features. To get a more realistic estimation of Core Damage Frequency (CDF), we developed the KU-PRA model using the AIMS-PSA code. We examined the factor of redundancy of the AC sources on the CDF by adding additional EDGs to the reference KU-PRA Model. We developed methodology and modeling of the Electrical Cross-tie for Multi-units PRA considering Common Cause Failure, Human Reliability Analyses, Battery load shedding, and Occupancy factor.

Extension of probabilistic seismic hazard analysis to account for the spatial variability of ground motions at a multi-unit nuclear power plant hard-rock site

Nuclear power plant (NPP) sites typically consist of multiple reactors (units). When earthquakes occur in the vicinity of these sites, effects will be experienced at all units. However, a seismic probabilistic risk assessment (PRA) of a multi-unit site typically only considers the possibility of adverse conditions at a single unit or, if multiple unit impacts are considered, typically assumes that all units at the site experience the same ground motion. This assumption of perfect correlation in ground motion is inconsistent with data from dense seismic arrays, which show that there is spatial variability in the ground motion between closely-spaced locations during the same earthquake. Moreover, such an assumption is not inherently conservative as is often assumed. To facilitate more realistic assessments, this paper proposes a method for capturing the effects of spatial variability of ground motion at an NPP site in the seismic PRA. The proposed method uses the results from an existing probabilistic seismic hazard analysis (PSHA) performed for a reference location at the site (e.g., the site seismic hazard curve and magnitude disaggregation) and then estimates the conditional probability distribution of the ground motion at a non-reference location. The proposed method accounts for the spatial variability in ground motion amplitude and includes mathematical formulations for NPP sites classified as “hard-rock.” The proposed method is developed using Bayesian networks because their graphical structure facilitates model transparency and communication. Moreover, Bayesian networks facilitate efficient probabilistic modeling and inference involving dependent random variables. However, the proposed method can be implemented more generally without using Bayesian networks as the calculation framework and commentary is provided regarding these alternative calculation options. This paper concludes with an example application using a PSHA for a hypothetical hard-rock site in the Central United States. Based on the results from the example application, we note that the perfect correlation assumption with respect to the ground motion at multiple locations/units at an NPP site may not necessarily be conservative.

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.

Multi-unit dynamic PRA

Dynamic Probabilistic Risk Analysis (PRA) methods couple stochastic methods (e.g., RAVEN) with safety analysis codes (e.g., RELAP5-3D) to determine risk associated to complex systems such as nuclear plants. Compared to classical PRA methods, which are based on static logic structures (e.g., Event-Trees, Fault-Trees), they can evaluate with higher resolution the safety impact of timing and sequencing of events on the accident progression. Recently, special attention has been given to nuclear plant sites which consist of multiple units and, in particular, on the safety impact of system dependencies, shared systems and common resources on core damage frequencies. In the literature, classical PRA methods have been employed to model multi-unit sites in a limited number of cases while Dynamic PRA methods have never been applied to analyze a full multi-unit model. This paper presents a PRA analysis of a multi-unit plant using Dynamic PRA methods. We employ RAVEN as stochastic tool coupled with RELAP5-3D. The site under consideration consists of three units (each unit is composed by a reactor and its associated spent fuel pool) while the considered initiating event is a seismic induced station blackout event. This paper describes in detail how the multi-unit site has been constructed and, in particular, how unit dependencies and shared resources are modeled from both a deterministic and stochastic point of view.

AIMS-MUPSA software package for multi-unit PSA

The need for a PSA (Probabilistic Safety Assessment) for a multi-unit at a site is growing after the Fukushima accident. Many countries have been studying issues regarding a multi-unit PSA. One of these issues is the problem of many combinations of accident sequences in a multi-unit PSA. This paper deals with the methodology and software to quantify a PSA scenarios for a multi-unit site. Two approaches are developed to quantify a multi-unit PSA. One is to use a minimal cut set approach, and the other is to use a Monte Carlo approach.

Analysis of Primary Containment Capture System for the propose Advanced Modern 600 nuclear power plant

Analysis of global electric markets shows that the electrical grid size of many developing countries is too small or too distributed to accommodate nuclear power plants (NPP) with large unit sizes. Thus a modern NPP design with a smaller output (∼600MWe) as well as with proper confidence of public safety is of interest. But as the Fukushima Daiichi NPP accident demonstrates, natural disasters can severely challenge the existing safety philosophy of defense in depth at NPPs. To improve and reinforce defense in depth, a new barrier to fission product release, a long-term and passive system against environmental release - a Primary Containment Capture System (PCCS) for Advanced Modern 600MW (AM600) is proposed. This system is designed to confine ex-containment release and to prevent containment failure from overpressure. In this study the thermal-hydraulics behavior of the PCCS of different length is studied. Analysis results show that a 1-km length with 8m diameter gravel filled tunnel (PCCS) can maintain safe conditions for containment for 10days following extended Station Blackout (SBO), and consequently the higher length for longer period without any release to the environment. The concept of the tunnel that is connected with containment will be suitable for multiunit site.

Holistic Approach to Multi-Unit Site Risk Assessment: Status and Issues

Abstract The events at the Fukushima Daiichi Nuclear Power Station in March 2011 point out, among other matters, that concurrent accidents at multiple units of a site can occur in reality. Although site risk has been deterministically considered to some extent in nuclear power plant siting and design, potential occurrence of multi-unit accident sequences at a site was not investigated in sufficient detail thus far in the nuclear power community. Therefore, there is considerable worldwide interest and research effort directed toward multi-unit site risk assessment, especially in the countries with high-density nuclear-power-plant sites such as Korea. As the technique of probabilistic safety assessment (PSA) has been successfully applied to evaluate the risk associated with operation of nuclear power plants in the past several decades, the PSA having primarily focused on single-unit risks is now being extended to the multi-unit PSA. In this paper we first characterize the site risk with explicit consideration of the risk associated with spent fuel pools as well as the reactor risks. The status of multi-unit risk assessment is discussed next, followed by a description of the emerging issues relevant to the multi-unit risk evaluation from a practical standpoint.

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.

Advances in multi-unit nuclear power plant probabilistic risk assessment

The Fukushima Dai-ichi accident highlighted the importance of risks from multiple nuclear reactor unit accidents at a site. As a result, there has been considerable interest in Multi-Unit Probabilistic Risk Assessment (MUPRA) in the past few years. For considerations in nuclear safety, the MUPRA estimates measures of risk and identifies contributors to risk representing the entire site rather than the individual units in the site. In doing so, possible unit-to-unit interactions and dependencies should be modeled and accounted for in the MUPRA. In order to effectively account for these risks, six main commonality classifications—initiating events, shared connections, identical components, proximity dependencies, human dependencies, and organizational dependencies—may be used. This paper examines advances in MUPRA, offers formal definitions of multi-unit site risk measures and proposes quantitative approaches and data to account for unit-to-unit dependencies. Finally, a parametric approach for the multi-unit dependencies has been discussed and a simple example illustrates application of the proposed methodology.

Integrated risk assessment for multi-unit NPP sites—A comparison

Most of the nuclear power producing sites in the world houses multiple units. Such sites are faced with hazards generated from external events: earthquake, tsunami, flood, etc. and can threaten the safety of nuclear power plants. Further, risk from a multiple unit site and its impact on the public and environment was evident during the Fukushima nuclear disaster in March 2011. It is therefore important to evolve a methodology to systematically assess the risk from multi-unit site. For a single unit site, probabilistic risk assessment technique identifies the potential accident scenarios, their consequences, and estimates the core damage frequency that arise due to internal and external hazards. This challenging task becomes even more complex for a multiple unit site, especially when the external hazards that has the potential to generate one or more correlated hazards or a combination of non-correlated hazards are to be modelled. This paper presents an approach to evaluate risk for multiple NPP sites and also compare the risk for sites housing single, double and multiple nuclear plants.

Probabilistic safety assessment of multi-unit nuclear power plant sites – An integrated approach

Multi-unit safety assessment has gained global importance after the Fukushima disaster in 2011. Most of the nuclear sites in the world have more than one reactor and hence it is important to evolve a methodology to systematically assess the safety of the multi-unit site. In this paper, unique features to be addressed in multi-unit safety assessment are discussed and an integrated approach is developed to assess the risk contribution of multiple nuclear plants at the site. The paper highlights the importance of risks for multi-unit sites arising from shared system, common cause failures, failure correlations, cliff-edge effects, etc. from different hazards. Though the main emphasis on multi-unit safety is on external hazards, the proposed approach also includes risk from random internal events. The approach developed not only quantifies the frequency of multiple core damage for a multi-unit site but also evaluates site core damage frequency which is the frequency of at least single core damage per site per year.

ICONE19-43305 Development of Level 1 Seismic PSA Method for Multi-Unit Site

Internal events as well as external events as initiators that may entail potential consequence have to be considered when we discuss the comprehensive risk of Nuclear Power Plant (NPP). Two or more NPPs that are located at a multi-unit site or close to each other could fail simultaneously at seismic event as one of external events, depending on the degree of seismic ground motion and its impact to units of the site. The seismometers at the Kashiwazaki-Kariwa NPPs recorded different time-histories of ground motion due mainly to the folding structure beneath the free field rock surface and to the installation condition of the embedded buildings, when the Niigata-ken Chuetsu-oki earthquake in July, 2007, impacted on the Site significantly. This suggested the different input ground motions on all plants at the site. Then the method is being enhanced to be applicable even if different input ground motions to respective plants at the site may happen to be generated. The interface of seismic hazard evaluation method, structure, system and component (SSC) fragility evaluation method, and accident sequence evaluation method were carefully and systematically considered. The enhanced method was preliminary applied to a hypothetical site where a highly-aseismatic and a lesser-aseismatic designed plant were located, and the applicability of the developed method to LWRs was discussed, applying typical correlation factor to the analysis model. Some insights on accident sequences for both plants failure and for either plant failure ("plant failure" is defined as "serious damage to the reactor core" in this paper.) were obtained from the analysis results. The developed method is robust to delineate the risk profile of multiple NPPs close to each other, being impacted by a strong seismic motion.

Effect of Correlations of Component Failures and Cross-Connections of EDGs on Seismically Induced Core Damages of a Multi-Unit Site

Aiming at proposing effective applications of seismic probabilistic safety assessment (PSA) for design and risk management of nuclear facilities, we conducted a preliminary seismic PSA study for a multi-unit site to examine core damage frequency (CDF) and core damage sequences with consideration of the effect of correlations of component failures. In addition, we also examined the effectiveness of an accident management measure, namely, cross-connections of emergency diesel generators (EDGs) between adjacent units in this study. Twin BWR-5 units of the same design were hypothesized to be located at the same site in this study and the CDF as well as the accident sequences of this two-unit site were analyzed by using SECOM2, a system reliability analysis code for seismic PSA. The results showed that the calculated CDF was dependent on the assumptions on the correlations of component failures. When the rules for assigning correlation coefficients of component responses defined in the NUREG-1150 program were adopted, the CDF of a single unit, the CDF of this two-unit site (the frequency of core damages of at least one unit at this site) and the frequency of simultaneous core damages of both units increased by factors of about 1.3, 1.2 and 2.3, respectively. In addition, it might be possible that the simultaneous core damages of both units are caused by different accident sequence pairs as well as the same sequence pairs. When cross-connections of EDGs between two units were available, the CDF of a single unit, the CDF of this two-unit site as well as the frequency of simultaneous core damages of both units decreased. In addition, the CDF of this two-unit site was smaller than the CDF of a single unit site. These results show that cross-connections of EDGs might be beneficial for a multi-unit site if the rules for assigning correlation coefficients defined in NUREG-1150 program are reasonable.

An Illustrative Application of Multi-Unit Franchise Expansion in a Local Retail Market

Retail expansion in a local market offers many challenges, and given the sensitivity of survival to location mistakes, it is imperative to develop site models that incorporate realistic impediments to that expansion. Small independent businesses or local area franchisees facing limits on all forms of capital rarely can open additional units without delays. In this paper, we test the benefit of using Kaufmann, Donthu and Brooks' (2000) multi-unit site selection model that incorporates the reality of delays in the opening of new stores as well as the recognition that local retail chains can face competition from many hard to identify sources. We use data from the actual introduction of a small set of stores in a major United States metropolitan market to estimate the potential for improvement over a pure sequential expansion strategy. When compared to the sequential strategy actually used by the retailer, we estimate that performance could have been improved by 15.5% if a model that anticipated the delays in opening the stores and competition from secondary sources would have been used.