Fire safety in high-rise talent apartments, which is vital for safeguarding strategic human resources, was investigated to enhance evacuation resilience. A coupled fire-evacuation model was established using PyroSim and Pathfinder. This study analyzed multi-factor management strategies, including occupant vertical distribution, evacuation speed, evacuation priority settings, panic psychology, and guide intervention. Additionally, an Artificial Neural Network (ANN) model was developed using simulation data obtained under non-panic conditions to predict evacuation time and explore intelligent algorithms. Results show that the evacuation stairwells are the primary bottlenecks. Panic psychology significantly reduces evacuation efficiency, with severe panic increasing total evacuation time by up to 71.1%. The combined strategy CS4, integrating Pyramidal Vertical Distribution (VD7) and Organized Segmented Speed Control (ES6), reduced evacuation time by 17.42%. Guide intervention effectively mitigates the negative impact of panic. The ANN model achieved a coefficient of determination (R²) of 0.8695, confirming its predictive capability. Visibility was identified as the key parameter determining the Available Safe Egress Time (ASET). This study demonstrates that an integrated “hard–soft combination” strategy, complemented by intelligent modeling, offers an effective approach to building a resilient evacuation system for high-rise talent apartments.

Rapid urbanization in China has overwhelmed traditional drainage systems, resulting in frequent flooding and water pollution in densely populated urban areas. This study focuses on the East Lake core area of Wuhan, proposing a deep tunnel drainage system to improve sewage storage and conveyance capacity. A pilot-scale pipe model was employed to determine the critical non-silting velocity for full-pipe sewage flow. Based on projected dry-season inflows and intercepted combined sewer discharges, the design capacities for pumping stations and pretreatment facilities were defined. A three-dimensional gas–liquid two-phase numerical model was used to simulate inflow shaft hydraulics at Erlangmiao, Luobuzui, and Wudong pretreatment stations. Simulation results confirm that all shafts meet energy dissipation and ventilation requirements, with uniform flow and velocity distributions that could be obtained by a vortex-type shaft. The system not only mitigates regional environmental challenges but also shows significant social, environmental, and economic benefits. Overall project design, applied methodology, simulation study, and outcomes could provide a valuable reference to deep tunnel drainage design and research.