Numerical Investigation of the Deposition Characteristics of Snow on the Bogie of a High-Speed Train

To investigate the deposition distribution of snow particles in the bogie surfaces of a high-speed train,a snow particle deposition model,based on the critical capture velocity and the critical shear velocity,was elaborated.Simulations based on the unsteady Reynolds-Averaged Navier-Stokes(RANS)approach coupled with Discrete Phase Model(DPM)were used to analyze the motion of snow particles.The results show that the cross beam of the bogie frame,the anti-snake damper,the intermediate brake clamps in the rear wheels,the traction rod and the anti-rolling torsion bar are prone to accumulate snow.The accumulation mass relating to the vertical surface in the rear region,horizontal surface in the front region and the corner area of the bogie is high.The average snow accumulation mass for each component ordered from high to low is as follow:traction rod,frame,bolster,brake clamp 2,anti-rolling torsion bar,brake clamp 1,transverse damper,axle box 2,axle box 1,air spring,anti-snake damper,tread cleaning device.The snow accumulation mass on the front components of the bogie is more significant than that relating to the rear components.Particularly,the average snow accumulation mass of rear brake clamp 2 and axle box 2 is about twice as high as that of the front brake clamp 1 and axle box 1.

Wind tunnel experiments on natural snow drift

Previous wind tunnel experiments on snow drift usually used artificial snow as a substitute of natural snow, which can not fully reflect the motion characteristics of snow drift in natural environments. In this paper we conducted a series of experiments in wind tunnel to investigate the motion of natural snow (fresh snow and old snow), which was collected out-door without destroying the surface structure. The results indicated that the threshold velocity of fresh snow is less than that of old snow, and that the mass flux rates of the two kinds of snow exponentially decrease with height whereas the snow transport rate increases exponentially with wind velocity. Based on the PIV measuring of the velocities of snow particles over two kinds of terrains (flat ground and roadbed), we found that the particle velocity obeys a Gaussian distribution for flat ground, top surface and leeward slope of the roadbed. However, for the windward slope of roadbed the particle velocity distribution displays poor correlation with a Gaussian function due to the acceleration of snow particles when saltating across the slop. Statistical analysis showed that impacting and liftoff velocities of snow particles also obey Gaussian distributions.

Scales of snow depth variability in high elevation rangeland sagebrush

In high elevation semi-arid rangelands, sage- brush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush （Artemisia tridentata Nutt.） at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions （0.05 to 25 m） and extents （2 to 1000 m）. Finer scale data were collected specifically for this study to examine the correlation between snow depth; sagebrush microtopogra- phy, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Vario- grams were used to identify the spatial structure and the Moran＇s I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.