Urban flooding disasters are increasingly prevalent because of global climate change and urbanization. University campuses, as independent functional zones, exhibit complex rainfall–runoff dynamics. This study focuses on the China University of Geosciences, using data from two extremely heavy rainfall events and on-site waterlogging investigations in Wuhan in 2020 and 2021. A stormwater management model was employed to simulate campus catchment runoff and pipe network performance under rainstorm scenarios of various return periods, illustrating the spatial and temporal evolution of waterlogging on the campus. The simulation results indicate that the discharge at the main outlets aligned with rainfall patterns but exhibited a delayed response. During an overload period exceeding one hour, the ratios of overflow nodes and overloaded conduits reached 72.22% and 57.94%, respectively. Ponding was concentrated mainly in the southwest region of the campus, with the maximum ponding depth reaching 0.5 m. Future flood mitigation measures, such as enhancing permeable surfaces, upgrading pipeline infrastructure, and promoting rainwater reuse, could support the development of a “sponge campus” layout to alleviate flood pressure and enhance campus sustainability and resilience.

Underground rail transit transfer stations are large-scale, complex structures with high-passenger flows, making them more vulnerable to fires and rescue challenges than other stations. Taking Zhongnan Road Metro Transfer Station in Wuhan as a project example, this study simulates two typical fire scenarios—flammable package ignition and equipment short circuits—using PyroSim to analyze changes in smoke movement, temperature, visibility, and CO concentration within the station. The required safety egress time (T_RSET) was determined according to the critical threshold. Then, the critical evacuation phase time (t_move’) at each key evacuation node was calculated by working backward from T_RSET. The threshold control of the open/close time nodes of the evacuation passages in the Pathfinder calculation was realized based on this time parameter. Based on the improved optimization algorithm method, personnel evacuation simulations are conducted to analyze evacuation characteristics, efficiency, and safety levels. Results show that the combustion characteristics of the fire source significantly affect the efficiency of passenger evacuation. The evacuation fails in Scenario 1 (flammable package) but succeeds in Scenario 2 (short circuit of an elevator circuit). Safety ratings for exits A–F are Level 1 (Good), Staircase 1 is Level 2 (Qualified), Staircases 2 and 3 are Level 3 (At Risk), and Staircase 4 is Level 4 (Poor). Finally, suggestions for improvement were proposed regarding size, quantity, and layout optimization of egress staircases.

The development and maturation of TBM (tunnel boring machine) technology have significantly improved the accuracy and richness of excavation data, driving advancements in intelligent tunneling research. However, challenges remain in managing data noise and parameter coupling, limiting the interpretability of traditional machine learning models regarding TBM parameter relationships. This study proposes a cutterhead rotation speed prediction model based on dimensional analysis. By utilizing boxplot methods and low-pass filtering techniques, excavation data were preprocessed to select appropriate operational and mechanical parameters. A dimensionless model was established and integrated with elastic net regression to quantify parameters. Using TBM cluster data from a water diversion tunnel project in Xinjiang, the accuracy and generalizability of the model were validated. Results indicate that the proposed model achieves high prediction accuracy, effectively capturing trends in cutterhead rotation speed while demonstrating strong generalizability.

Taking the Xianfeng Tunnel in Luzhai county, Guangxi province as the engineering background, this study aims to investigate the influence of different construction parameters on the stress and deformation of lining structures under creep effects, and also reveal the load-sharing ratios of composite lining structures under varying initial support stiffness conditions and the temporal evolution patterns and transfer mechanisms of surrounding rock pressure by using field monitoring and numerical simulation methods. The findings of this research are as follows: (1) Both monitoring data and simulation analyses demonstrate that the Cvisc constitutive model effectively describes the creep behavior of the surrounding rock in the engineering area; (2) Construction parameters have a significant impact on the stress of the primary lining, the earlier application of the secondary lining leading to greater structural stress; (3) With the increase of the elastic modulus of the primary lining, the load-sharing ratio of the secondary lining decreases, while the ultimate pressure borne by the secondary lining remains relatively stable; (4) Considering the time-dependent effects of creep behavior, when the secondary support is installed before the yield phase of initial structure, the pressure on each part of the lining structure is distributed according to the stiffness of each structure; subsequently, as the initial support enters the yield phase, the load it bears transferred to the secondary lining structure. These research findings can provide theoretical guidance for the design of support structures and construction parameters in soft rock tunnels.