Fractured rock masses are extremely common in geological engineering. In order to improve the stability of surrounding rock under dynamic conditions, new grouting materials and their reinforcement characteristics were studied. In this paper, split Hopkinson pressure bar (SHPB) tests were employed to analyze the dynamic mechanical and failure characteristics of grouted fractured rock with nano-grouting material (nano-grouted fractured rock). Simultaneously, high-speed camera tests were utilized to examine the macroscopic dynamic deformation and failure processes. The following was found: (1) Under a relatively low impact air pressure of 0.1 MPa, the mechanical properties of nano-grouted fractured rock are considerably better than those of traditional cement-based grouted rock. However, when the impact air pressure is increased to 0.3 MPa, the superiority of nano-grouting material diminishes, the possible cause of which is explained from the microscopic point of view. This means the nano-grouting material is more suitable for low-engineering-disturbance conditions (e.g., shield construction). (2) Both for the nano- and superfine cement grouting material, the impact fractures initially emerge at the two ends of the original grouted fracture and form a pair of parallel lines. (3) In comparison with 0.1 MPa, the impact pressure of 0.3 MPa leads to more severe damage to the rock specimen. These findings contribute to a deeper understanding of the behavior of nano-grouted fractured rock under dynamic loading and provide valuable insights for relevant engineering applications in the field of rock mechanics and grouting technology.

Based on the lining structure of an operational tunnel, the AHP and Fuzzy mathematical models were used to determine the weight of the evaluation index and solve the membership matrix. The weighted-average Fuzzy comprehensive function was used to combine the two, and the Fuzzy–AHP evaluation model was built and programmed. According to the self-developed Fuzzy–AHP evaluation-programmed model, a visualized structure safety evaluation system for operational tunnels was developed by using MATLAB. The system’s functional design, program development, and computational visualized interface were implemented, and key codes were provided. The system can be divided into four modules: data management, fuzzy computation, predictive analysis and key disease indexes to focus on. In addition, the system can easily edit and modify the evaluation function, which includes not only the Fuzzy evaluation but also other types of evaluation functions applicable to other practical engineering projects, improving the applicability of the system. After that, the system was applied to the structure safety evaluation of a mountain tunnel, which provided the evaluation results and key indexes to focus on in the tunnel. Finally, the rationality of the system design was verified by constructing the corresponding BP–RBF combined neural network. This study provides a reference for the establishment of an intelligent structure safety warning system for operational tunnels.