In a chemical material network, a small fault is easy to spread and cause serious consequences, which is the embodiment of a complex network cascading fault. In order to ensure the safety and stability of chemical production, it is necessary to study the cascading fault propagation of a chemical material network. Firstly, the chemical material network model is constructed, and the SR algorithm is used to identify the important nodes in the network, which is the basis for selecting attack nodes. Secondly, the fault propagation strength is defined by the fault propagation probability and material hazard degree. The

In order to better characterize the accident propagation mechanism in chemical industry park (CIP), a method combining mixed degree decomposition (MDD) algorithm with accident propagation probability is proposed to measure the accident propagation ability of nodes in the accident chain network of CIP in this paper. First, the accident chain network model of CIP is established by using complex network theory and the nodes in the network model are layered according to the accident propagation ability based on the MDD algorithm. Second, the accident propagation probability value of each node in the network is defined and calculated according to the characteristic factors of the node itself. Finally, the result of MDD algorithm is combined with the accident propagation probability value by using Euclidean distance formula, the nodes with strong accident propagation ability in the accident chain network of CIP are determined. The case analysis shows that the method has higher discrimination, can effectively measure the accident propagation ability of nodes in the accident chain network of CIP, and better identify the nodes with strong propagation ability.

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With the rapid development of process industry, the heat exchanger network is becoming larger and more complicated. The heat exchanger network will inevitably be subject to internal and external interference, resulting in cascading failures, which reduces the controllability of the heat exchanger network and affects normal operation. A controllability robustness analysis method is proposed based on the complex network theory, to enhance the ability of the heat exchanger network to operate normally under external interference. First, combined with the interference transfer law of the heat exchanger network, a weighted directed complex network model of the heat exchanger network is constructed. Then, based on the controllability robustness analysis method of the minimum driver node, the controllability robustness of the heat exchanger network under four different attack modes is analyzed and compared. The comparative analysis of examples proves that the method takes into account the global controllability, accurately determines the attack modes and attack targets that have a greater impact on the controllability robustness of the heat exchanger network, reduces the computational complexity, and provides theoretical basis for improving the controllability robustness of the heat exchanger network and maintaining the normal operation of the heat exchanger network.