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Lee, Seung Jun
Risk Assessment and Risk-Informed Application
Research Interests
  • Probabilistic Safety Assessment, Digital I&C System Reliability, Human Reliability Analysis


Abnormality Diagnosis Model for Nuclear Power Plants Using Two-Stage Gated Recurrent Units

DC Field Value Language Kim, Jae Min ko Lee, Gyumin ko Lee, Changyong ko Lee, Seung Jun ko 2020-02-13T08:41:17Z - 2020-02-07 ko 2020 ko
dc.identifier.issn 1738-5733 ko
dc.identifier.uri -
dc.description.abstract A nuclear power plant is a large complex system with tens of thousands of components. To ensure plant safety, the early and accurate diagnosis of abnormal situations is an important factor. To prevent misdiagnosis, operating procedures provide the anticipated symptoms of abnormal situations. While the more severe emergency situations total less than ten cases and can be diagnosed by dozens of key plant parameters, abnormal situations on the other hand include hundreds of cases and a multitude of parameters that should be considered for diagnosis. The tasks required of operators to select the appropriate operating procedure by monitoring large amounts of information within a limited amount of time can burden operators. This paper aims to develop a system that can, in a short time and with high accuracy, select the appropriate operating procedure and sub-procedure in an abnormal situation. Correspondingly, the proposed model has two levels of prediction to determine the procedure level and the detailed cause of an event. Simulations were conducted to evaluate the developed model, with results demonstrating high levels of performance. The model is expected to reduce the workload of operators in abnormal situations by providing the appropriate procedure to ultimately improve plant safety. ko
dc.language 영어 ko
dc.publisher KOREAN NUCLEAR SOC, ko
dc.title Abnormality Diagnosis Model for Nuclear Power Plants Using Two-Stage Gated Recurrent Units ko
dc.type ARTICLE ko
dc.type.rims ART ko
dc.identifier.doi 10.1016/ ko
dc.identifier.url ko
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