The Characteristics of Wind-Blown Snow Hazards and an In-Situ Wind Tunnel Experiment Study on Snow Disaster Prevention along Railway

Abstract Snow drift disasters pose a serious threat to the safe operation of railway engineering. Current research on the characteristics of railway snow drift disasters and the role of snow fences in their prevention often relies on indoor wind tunnel experiments, which overlook the influence of factors such as temperature, humidity, and climate on snow particle transport. To realistically reproduce the forces acting on snow particles and their movement patterns, this study, based on field monitoring results, employed a mobile wind tunnel simulation device and applied similarity criteria to conduct scaled outdoor wind tunnel tests on-site. The study examined the impact of the distance between snow fences and the railway subgrade on snow accumulation distribution. It also analyzed how different fence-subgrade distances affect wind fields and surface shear velocity around the subgrade. Furthermore, numerical simulations were used to investigate the influence of snow fence porosity, the distance between snow fences and the cutting slope, and fence height on wind and snow field distributions near the subgrade. Optimal design parameters for snow fences were proposed accordingly. The results show that outdoor in-situ wind tunnel experiments can realistically replicate field engineering environments (including appropriate temperature and humidity), allowing for more scientific testing of the geometry, snow particle saltation processes, particle trajectories, time scales, and deposition patterns during snow drift disasters affecting the subgrade. For railway sections prone to snow drift disasters, snow fences with 50% porosity, a height of 3 meters, and placed 50 meters from the cutting slope provide optimal protection. These findings offer theoretical support for the prevention and control of snow drift disasters and for the safety-oriented design of railway subgrade engineering in high-risk areas.