(A) model for quantification of resilience to recover from emergency situations in nuclear power plants

Abstract

therefore, it focuses on the condition that “things go right.” Human factors are consequently considered as resources necessary for system flexibility and resilience. There are several limitations of existing safety analysis measures, such as deterministic safety analysis and probabilistic safety analysis. For instance, the existing safety analysis measures focus on the failure of the system and try to eliminate the causes of failure. They also consider the failure of components and human error and assess these factors individually. Resilience can be defined as the intrinsic ability of a system to adjust to its functioning prior to, during, or following changes and disturbances, so that it can sustain required operation under both expected and unexpected conditions. Resilience engineering is a relatively new paradigm for safety management that focuses on how to cope with complexity under pressure or disturbance to achieve success, addressing the limitations of existing safety analysis measures. Resilience engineering focuses on the success of the system and aims to eliminate the latent factors that can be trigger a disaster. It involves an overall assessment, considering the hardware, operator, organizational, training, procedure, etc. Additionally, it assesses the integrated safety-influencing factors. Thus, resilience engineering provides a more integrated view for safety analysis. There is necessity to consider how NPPs, including human and organizational factors, cope with emergency situation in NPP on the perspectives of resilience. This study aimed to develop a model for quantification of resilience which shows quantitative relations between resilience and resilience components to recover from emergency situations in NPPs. To develop a model, the analysis of event data that occurred in Korea from the perspectives of Safety-I and Safety-II by applying the resilience factors was performed. And the analyzed results were applied by statistical method to perform the factor analysis to derive principal components, and the reliability analysis was performed to confirm the adequacy of the results. The concept of resilience was applied to define the degree of degradation and recovery in emergency situations, and the relationship with the previously analyzed components was confirmed by multivariate regression analysis. Through these statistical results, a model for quantification of resilience to recover from emergency situations was developed. The developed quantitative resilience model was also validated through a statistical method. And the developed model is applied for ‘stress test’ which was conducted to evaluate the coping capability to extreme natural disaster, which exceed design basis, for domestic NPPs after the Fukushima accident. The quantitative resilience values to cope with the extreme natural disaster were evaluated from this model. From the results, the value of required resilience, which the NPPs need to cope with emergency situations, was derived. And this study developed a guideline to evaluate and quantify each resilience component as a way to quantitatively evaluate the capability of nuclear power plants. From the guidelines which define values for each resilience component, we can apply this model and evaluate the NPP’s capability to recover the emergency situations quantitatively. The results provide a new method for safety assessment in NPPs, which can complement the conventional safety assessment. The proposed method is expected to be an index for evaluating the integrity of safety management in Korean NPPs.

The causes of the Fukushima nuclear power plant (NPP) accident have been identified as not only technical factors such as the structure, system, and equipment design, but also inadequate management of the human and organizational factors, which were the major contributors to exacerbating the beyond design basis accident. After the accident, the safety paradigm was changed to address the failure of equipment as well as effective factors for safety. The definition of safety is the state of being safe, which is the condition of being protected from harm or other non-desirable outcomes. From the concept of Safety-I, increasing safety means reducing the number of failures by precautionary measures such as rigid policies, more rules, and additional constraints. However, safety management and evaluation may not be applicable for highly complicated systems such as NPPs. The concept of Safety-II assumes that the performance variability provides the adaptations that are needed to respond to various situations