ABSTRACT
In order to solve the problem of laboratory safety, a quantitative assessment method of laboratory poisoning accident risk evolution was proposed based on complex network theory and risk uncertainty. According to the laboratory operation process, the complex network evolution model of the poisoning accident scene was constructed to judge the clustering of nodes. In view of the randomness and fuzziness of risk transfer, edge weights are introduced to represent the uncertainty. The expression of the maximum possibility of the risk transmission path is given, and the accident's shortest path is obtained by the Dijkstra algorithm. The results show that the clustering coefficient of the complex network of laboratory poisoning accidents is 0.120, and the node aggregation degree is low but the evolution is strong, which has the characteristics of the small-world network. The risk transmission path that directly affects laboratory equipment and facilities as the initial event has the greatest influence on poisoning accidents. However, all the initial events can lead to poisoning accidents after a few steps of transmission, which verifies the feasibility of this method in the semi-quantitative risk assessment of complex process systems.
