Risk Identification and Chaotic Synchronization Control for Spent Fuel Road Transportation Based on Complex Network Evolution Models

To improve the safety of road transportation of Spent Nuclear Fuel (SNF), this paper proposes a novel approach for risk identification and chaotic synchronous control in SNF road transportation systems. Firstly, a dynamic risk evolution model for the road transportation of SNF is developed by analyzing the nonlinear interactions among vehicles, environmental conditions, and human factors using complex network analysis and nonlinear dynamics. Secondly, an enhanced K-shell decomposition method is applied to identify key risk nodes and assess the relative importance of different risk factors, providing a basis for targeted risk control. Finally, a chaotic synchronization control strategy based on Lyapunov stability is proposed to suppress risk divergence and restore system stability. Three targeted control schemes are evaluated by varying the control gain coefficients across the ‘Vehicle–Environment–Human’ dimensions. Simulation results indicate that the strategy prioritizing environmental and human risk control yields the fastest convergence, significantly outperforming vehicle-centric approaches. The results show that prioritizing both environmental and human-factor control is most effective for suppressing chaotic divergence. This provides a solid quantitative basis for the strategic shift from passive defense to active environmental warning, thereby significantly optimizing the dynamic risk management of the SNF transportation system.