## 1 Introduction  
In recent years, several emerging issues have gradually come to light in the prolonged operation of high-speed railway tunnels. These problems included concerns such as water leakage, cracks, bottom expansion, and settlement [1; 2; 3]. These tunnel-related issues, exacerbated by the cumulative effects of prolonged train vibrations and aerodynamic loads, often led to the dislodgment of debris from the tunnel lining surface [4], as shown in Figure 1. This presents a significant safety risk to train operations, and such incidents have been reported globally. An illustrative incident occurred in June 1999 at the Fukuoka Tunnel in Japan, where a serious accident transpired. This incident involved debris striking a pantograph on the twelfth car of a train, damaging overhead wires and resulting in a 10 h stoppage of train operations [5]. Similar incidents were reported later that year in a tunnel on the Rebunhama high-speed railway in Hokkaido, Japan, leading to a train derailment. Instances of debris falling from the vault of the Pingshan tunnel in China in 2016 prompted speed restrictions for over two hours. In August 2017, concrete dislodgment from the vault at the upstream line of New Mijiahe Tunnel No. 1 on the Baoxi Line disrupted the operation of the upstream line [6]. Many scholars have employed deep learning and photogrammetric techniques for semi-autonomous inspection of concrete structures, confirming that surface defects in concrete cannot be overlooked [7]. Additionally, studies have utilized computer vision techniques integrated with deep learning models to analyze and predict the microscopic characteristics of concrete [8]. Regarding dynamic load monitoring, research has demonstrated that by combining sensor technology with advanced data processing algorithms, intelligent controllers can monitor the stress conditions of tunnels in real time, providing critical support for safety assessment and maintenance [9]. When a train is operating at high speed, the viscous effects of air, the propulsive force generated by the train, and the pressure differential between its front and rear sections compel the surrounding air to move in tandem with the train, leading to extreme wind environments [10; 11; 12; 13]. Particularly in tunnels, where airflow is restricted by the tunnel walls, the slipstream effect is more pronounced compared with open lines [14; 15; 16; 17]. Studies indicate that the slipstream effect can have adverse effects on trackside ballast, platform passengers, and staff [18; 19]. [PERSON] et al. [20] simulated high-speed trains passing through snow with different train lengths, observing that the downward airflow significantly affected the distribution and accumulation of snow. [PERSON] et al. [21] replicated the airflow generated during train operations through 1:1 wind tunnel tests, revealing noticeable displacement of bottom slag due to the passing train's airflow. [PERSON], et al. [22] studied slipstream variations when passenger and freight trains passed through underground stations. Their findings indicated that high-speed train passage can subject platform passengers to strong winds, causing discomfort and potential danger. Given this scenario, the slipstream effect can significantly alter the flight trajectory of falling debris from the lining, deviating it from freefall motion. With the increase in the operational mileage of high-speed railways, two trains crossing in a tunnel has become a common occurrence. Studies indicate that under trains-crossing conditions, the maximum Mach number in the tunnel can reach 0.6, leading to more complex flow phenomena and pressure fluctuations. The slipstream effect resulting from intersections is significantly more severe than that observed with a single train [23; 24; 25]. [PERSON] et al. [26] utilized the unsteady Reynolds-averaged Navier-Stokes (RANS) method to analyze and compare the three-dimensional slipstream effects of trains passing through  
Figure 1: A schematic diagram of crack propagation and falling debris under aerodynamic load.