Nuclear Safety Assessment and Plant HMI Evolution Laboratory

원자력 안전성평가 및 HMI 혁신 연구실

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원자력 안전성평가 및 HMI 혁신 연구실

Nuclear Power Plant Safety Assessment
“How to assess the safety of a nuclear power plant?” “How safe is safe enough?”
We are performing the researches to answer the questions and to make nuclear power plants safer. The risk assessment of nuclear power plants is crucial in plant designing, licensing, and various decision makings. To assess the plant safety more accurately, we are solving the emerging issues such as reliability of safety-critical digital systems, human reliability in digitalized environment, cyber security, dynamic risk assessment, and multi-unit risk assessment.
Plant Human Machine Interface (HMI) Evolution
Human error is one of the major contributors in the nuclear power plant safety. Since a nuclear power plant is a large complex system with ten thousands of components, it is not easy to diagnose the current situation and to perform corrective actions quickly and accurately even for highly trained operators. To improve the plant safety by preventing human errors, we are developing an innovative plant HMI with high level automation systems using the artificial intelligence technology.

Major research field

Multi-unit PSA, Gen-IV reactor PSA, Cyber-attack risk assessment, Digital I&C reliability, Human reliability analysis, operator support systems

Desired field of research

Dynamic PSA, Passive system reliability evaluation, Autonomous operation

Research Keywords and Topics

Probabilistic safety assessment, Human reliability analysis, Risk-informed application, Digital I&C reliability evaluation, Operator support system development, Autonomous system development

Research Publications
MORE

1. RELIABILITY ENGINEERING AND SYSTEM SAFETY / Development of a multi-unit seismic conditional core damage probability model with uncertainty analysis / Heo, Yunyeong, Lee, Seung Jun / 2021-03
2. APPLIED SOFT COMPUTING / A Convolutional Neural Network Model for Abnormality Diagnosis in a Nuclear Power Plant / Lee, Gyumin, Lee, Changyong, Lee, Seung Jun / 2021-02
3. IEEE ACCESS / Bayesian Belief Network Model Quantification Using Distribution-Based Node Probability and Experienced Data Updates for Software Reliability Assessment / Lee, Seung Jun, Lee, Sang Hun, Chu, Tsong-Lun, Varuttamaseni, Athi, Yue, Meng, Li, Ming, Cho, Jaehyun, Kang, Hyun Gook / 2018-10

Patents

1. [KOR] Method of Guarantee for Software Failure / 이승준, 조재현, 신성민, 정원대, 양준언 / 2019-05
2. [KOR] Generating human error mode status distribution method according to the soft controller types and system thereof / 이승준, 김재환, 장승철 / 2013-03

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