Risk-informed approach to the safety improvement of the reactor protection system of the AGN-201K research reactor

Periodic safety reviews (PSRs) are conducted on operating nuclear power plants (NPPs) and have been mandated also for research reactors in Korea, in response to the Fukushima accident. One safety review tool, the probabilistic safety assessment (PSA), aims to identify weaknesses in the design and operation of the research reactor, and to evaluate and compare possible safety improvements. However, the PSA for research reactors is difficult due to scarce data availability. An important element in the analysis of research reactors is the reactor protection system (RPS), with its functionality and importance. In this view, we consider that of the AGN-201K, a zero-power reactor without forced decay heat removal systems, to demonstrate a risk-informed safety improvement study. By incorporating risk- and safety-significance importance measures, and sensitivity and uncertainty analyses, the proposed method identifies critical components in the RPS reliability model, systematically proposes potential safety improvements and ranks them to assist in the decision-making process. Keywords: Research reactor, Reactor protection system, Probabilistic safety assessment, Risk-informed design, Unavailability analysis, Sensitivity analysi

QRA Considering Multi-Vessel Failure Scenarios due to a Natural Disaster – Lessons from Fukushima

PresentationThe Fukushima accident is the largest nuclear power plant accident caused by a natural disaster, which shut off the cooling system. In this accident, an initiating event from a single unit was propagated to other units at the site. Prior to the Fukushima accident, scenarios for multi-unit failures had been screened out, so that only single unit failure scenarios were taken into account in the nuclear industry. Since that accident, the nuclear industry in South Korea is now more concerned with multi-unit Probabilistic Safety Assessment (PSA) and is attempting to develop a new methodology since there are generally more than four units on one site in the country The chemical and petrochemical industries have experienced a number of incidents/accidents related to multi-units such as vessels and tanks because many of these units are usually installed on a site. The chemical industry has a wide range of experience, but most scenarios have involved domino effects, while the study of multi-vessel accidents caused by natural disasters (i.e., earthquakes) is lacking. The purpose of this paper is to review past experiences in the chemical industry and adapt appropriate process safety applications using risk analysis related to multiple vessels (tanks) at a site. Several QRA approaches have been searched and employed to compare the risks of some chemical plant complexes in South Korea regarding multi-vessel (unit) failure scenarios due to natural disasters

Emerging I&C Technologies Under the Shifting Regulatory Environment in South Korea

The role of Probabilistic Safety Assessment (PSA) has been supplementary and Risk-Informed Applications (RIAs) based on the insight from PSA has also been utilized limitedly in the licensing process for Nuclear Power Plants (NPPs) in South Korea. However, as the technical significance of PSA is getting increased, PSA has become a mandatory part of Safety Analysis Reports and Periodic Safety Review. It is worthwhile to highlight the role of emerging Instrumentation and Control (I&C) technologies including human-machine interface (HMI) in developing more credible and realistic PSA models. Particularly, it is expected that the information technology (i.e. software) embedded in digital I&C can adjust over- and under conservatism in analyzing risk. In this study, authors proposed the cases which would be able to significantly reduce risk if advanced I&C supported by information technologies is applied. In regard, the several enabling techniques and their effects are proposed. In order to improve the commercial competitiveness of NPPs, the need of collaboration and synergetic outcome of I&C, HMI and PSA should be emphasized

Fault Detection by Signal Reconstruction in Nuclear Power Plants

In this work, the recently developed auto associative bilateral kernel regression (AABKR) method for on-line condition monitoring of systems, structures, and components (SSCs) during transient process operation of a nuclear power plant (NPP) is improved. The advancement enhances the capability of reconstructing abnormal signals to the values expected in normal conditions during both transient and steady-state process operations. The modification introduced to the method is based on the adoption of two new approaches using dynamic time warping (DTW) for the identification of the time position index (the position of the nearest vector within the historical data vectors to the current on-line query measurement) used by the weighted-distance algorithm that captures temporal dependences in the data. Applications are provided to a steady-state numerical process and a case study concerning sensor signals collected from a reactor coolant system (RCS) during start-up operation of a NPP. The results demonstrate the effectiveness of the proposed method for fault detection during steady-state and transient operations

Sensitivity Study on Availability of I&C Components Using Bayesian Network

The objective of this study is to find out the impact of instrumentation and control (I&C) components on the availability of I&C systems in terms of sensitivity analysis using Bayesian network. The analysis has been performed on I&C architecture of reactor protection system. The analysis results would be applied to develop I&C architecture which will meet the desire reliability features and save cost. RPS architecture unavailability P(x=0) and availability P(x=1) were estimated to 6.1276E-05 and 9.9994E-01 for failure (0) and perfect (1) states, respectively. The impact of I&C components on overall system risk has been studied in terms of risk achievement worth (RAW) and risk reduction worth (RRW). It is found that circuit breaker failure (TCB), bi-stable processor (BP), sensor transmitter (TR), and pressure transmitter (PT) have high impact on risk. The study concludes and recommends that circuit breaker bi-stable processor should be given more consideration while designing I&C architecture

cyber attack taxonomy for digital environment in nuclear power plants

With the development of digital instrumentation and control (I&C) devices, cyber security at nuclear power plants (NPPs) has become a hot issue. The Stuxnet, which destroyed Iran's uranium enrichment facility in 2010, suggests that NPPs could even lead to an accident involving the release of radioactive materials cyber-attacks.However, cyber security research on industrial control systems (ICSs) and supervisory control and data acquisition (SCADA) systems is relatively inadequate compared to information technology (IT) and further it is difficult to study cyber-attack taxonomy for NPPs considering the characteristics of ICSs. The advanced research of cyber-attack taxonomy does not reflect the architectural and inherent characteristics of NPPs and lacks a systematic countermeasure strategy.Therefore, it is necessary to more systematically check the consistency of operators and regulators related to cyber security, as in regulatory guide 5.71 (RG.5.71) and regulatory standard 015 (RS.015). For this reason, this paper attempts to suggest a template for cyber-attack taxonomy based on the characteristics of NPPs and exemplifies a specific cyber-attack case in the template. In addition, this paper proposes a systematic countermeasure strategy by matching the countermeasure with critical digital assets (CDAs). The cyber-attack cases investigated using the proposed cyber-attack taxonomy can be used as data for evaluation and validation of cyber security conformance for digital devices to be applied, and as effective prevention and mitigation for cyber-attacks of NPPs. Keywords: Cyber-attack taxonomy, Cyber security, Nuclear power plant, ICS, SCAD

Design process of the nanofluid injection mechanism in nuclear power plants

Nanofluids, which are engineered suspensions of nanoparticles in a solvent such as water, have been found to show enhanced coolant properties such as higher critical heat flux and surface wettability at modest concentrations, which is a useful characteristic in nuclear power plants (NPPs). This study attempted to provide an example of engineering applications in NPPs using nanofluid technology. From these motivations, the conceptual designs of the emergency core cooling systems (ECCSs) assisted by nanofluid injection mechanism were proposed after following a design framework to develop complex engineering systems. We focused on the analysis of functional requirements for integrating the conventional ECCSs and nanofluid injection mechanism without loss of performance and reliability. Three candidates of nanofluid-engineered ECCS proposed in previous researches were investigated by applying axiomatic design (AD) in the manner of reverse engineering and it enabled to identify the compatibility of functional requirements and potential design vulnerabilities. The methods to enhance such vulnerabilities were referred from TRIZ and concretized for the ECCS of the Korean nuclear power plant. The results show a method to decouple the ECCS designs with the installation of a separate nanofluids injection tank adjacent to the safety injection tanks such that a low pH environment for nanofluids can be maintained at atmospheric pressure which is favorable for their injection in passive manner

Study on Nuclear Accident Precursors Using AHP and BBN

Most of the nuclear accident reports used to indicate the implicit precursors which are not easily quantified as underlying factors. The current Probabilistic Safety Assessment (PSA) is capable of quantifying the importance of accident causes in limited scope. It was, therefore, difficult to achieve quantifiable decision-making for resource allocation. In this study, the methodology which facilitates quantifying these precursors and a case study were presented. First, four implicit precursors have been obtained by evaluating the causality and hierarchy structure of various accident factors. Eventually, it turned out that they represent the lack of knowledge. After four precursors are selected, subprecursors were investigated and their cause-consequence relationship was implemented by Bayesian Belief Network (BBN). To prioritize the precursors, the prior probability is initially estimated by expert judgment and updated upon observations. The pair-wise importance between precursors is calculated by Analytic Hierarchy Process (AHP) and the results are converted into node probability tables of the BBN model. Using this method, the sensitivity and the posterior probability of each precursor can be analyzed so that it enables making prioritization for the factors. We tried to prioritize the lessons learned from Fukushima accident to demonstrate the feasibility of the proposed methodology

Advancements in Probabilistic Safety Assessment of Nuclear Energy for Sustainability

Since the publication of the first comprehensive Probabilistic Safety Assessment (PSA) study—known as WASH-1400—in the US, PSA has developed into an effective and systematic method of identifying hazards, and evaluating and prioritizing the risks in nuclear facilities [...

Development of a radiological emergency evacuation model using agent-based modeling

In order to mitigate the damage caused by accidents in nuclear power plants (NPPs), evacuation strategies are usually managed on the basis of off-site effects such as the diffusion of radioactive materials and evacuee traffic simulations. However, the interactive behavior between evacuees and the accident environment has a significant effect on the consequential gap. Agent-based modeling (ABM) is a method that can control and observe such interactions by establishing agents (i.e., the evacuees) and patches (i.e., the accident environments). In this paper, a radiological emergency evacuation model is constructed to realistically check the effectiveness of an evacuation strategy using NetLogo, an ABM toolbox. Geographic layers such as radiation sources, roads, buildings, and shelters were downloaded from an official geographic information system (GIS) of Korea, and were modified into respective patches. The dispersion model adopted from the puff equation was also modified to fit the patches on the geographic layer. The evacuees were defined as vehicle agents and a traffic model was implemented by combining the shortest path search (determined by an A ∗ algorithm) and a traffic flow model incorporated in the Nagel-Schreckenberg cellular automata model. To evaluate the radiological harm to the evacuees due to the spread of radioactive materials, a simple exposure model was established to calculate the overlap fraction between the agents and the dispersion patches. This paper aims to demonstrate that the potential of ABM can handle disaster evacuation strategies more realistically than previous approaches