Combined with failure propagation model, the importance evaluation and critical node identification of five functional nodes of combat system are presented

To address node heterogeneity, complex functional dependences, and the limited ability of traditional metrics to capture system-level failure impacts in combat networks, this paper proposes a node-importance evaluation and critical-node identification method that couples failure propagation modeling with flow-blockage theory. We first construct a directed heterogeneous network with five functional node types and explicitly define their resource interfaces and dependency paths. An improved threshold-based propagation mechanism and a composite influence function integrating propagation probability, neighbor overlap, and the KHC topological index are then introduced, and a propagation-efficiency coupled identification algorithm is developed using the max-flow/min-cut principle to quantify traffic degradation under failures. Simulations across multiple failure scenarios and network topologies show that the proposed method significantly outperforms conventional centrality measures in identifying system-level high-loss nodes, yielding more actionable, task-chain–focused results with strong adaptability and robustness. These findings provide theoretical and algorithmic support for combat-network vulnerability assessment, resilient command-system design, and suppression-path planning.