A Finite State Machine-Based Modeling Approach for Command and Logging in Nuclear Emergency Exercise

Nuclear accident emergency exercises serve as a critical safeguard for nuclear safety. However, conventional approaches relying on paper-based scripts and manual documentation suffer from inherent limitations, including rigid procedures, fragmented data, and insufficient real-time analytical capabilities. To address these challenges, this study proposes an intelligent dynamic recording and analysis framework for nuclear emergency exercises based on Finite State Machine (FSM) theory. By employing modular design, hierarchical state modeling, critical-node optimization, and serial-parallel structure, the framework enables intelligent guidance and real-time documentation throughout the entire emergency exercise process. Case studies demonstrate that the proposed model achieves dynamic process control, ensures logical completeness, and maintains robust real-time recording capabilities, effectively overcoming the issues of procedural inflexibility and data fragmentation in traditional exercises. This research provides an extensible and intelligent technical solution for nuclear emergency preparedness, offering significant practical value in optimizing response mechanisms for major nuclear accidents.