Abstract
Wet snow accumulation on bridge cables and its shedding due to external phenomena such as rise in temperature, wind, and gravity is a serious threat to the safety of cars and pedestrians crossing the bridge. Commonly the accumulated snow on bridge cables is removed by external means such as mechanical removal or heat treatment which are expensive, time-consuming, and high-risk processes and are conducted based on little or no information available regarding the actual size and shape of the accumulated snow. In addition, cleaning of cables using the mechanical methods can potentially lead to erosion of cable materials when applied over years, resulting in enhanced surface roughness and potentially increased wet snow/ice accumulation during future precipitation events, and sometimes might require replacement of cable stays, which is an extremely costly and complicated task. Optimizing the number of mechanical cleaning procedures such as chain release through predicting the shape and thickness of the accumulated snow on the cable stays reduces the cost, time, and risk associated with the process. In this study, wet snow accumulation on torsionally rigid inclined cylinders of high-density polyethylene (HDPE) has been studied experimentally and numerically. A 2-D numerical model has been developed utilizing weather data to predict the thickness and the shape of the accumulated wet snow on inclined cylindrical surfaces. Outdoor experiments were also conducted to measure the density and thickness of accumulated snow, while monitoring the weather data real time. Overall, snow density was found to be linearly increasing with an increase in wind velocity, during snow precipitation. The maximum thickness and shape of the accumulated snow on cables obtained from the numerical model were found to be in good agreement with the outdoor experimental data. This work aims to provide a mean for prediction of snow accumulation on surfaces for optimizing the efficiency of the costly and high-risk snow removal procedures.
Highlights
Atmospheric icing is referred to various processes in which water droplets in atmosphere freeze and adhere to surfaces potentially posing severe risks to the security of man-made structures [1, 2]
Ice and wet snow accumulation on structures such as power transmission lines, bridge cables, wind turbine blades, and aircraft wings can reduce efficiency, cause detrimental environmental consequences, enhance safety hazards, and increase operational costs [3,4,5,6,7]. e cost of damages of wet snow accretion could be in the order of 100 million US dollars per storm [8]. erefore, significant ice loads form due to particles in the air colliding with surfaces with different geometries. ese particles can be liquid, solid, or a mixture of water and ice
We conducted outdoor experiments to measure the density of the accumulated snow on plates and used the measured density values to simulate the accumulation of wet snow on inclined torsionally rigid cables. en, we compared the simulation results with measured accumulated snow thicknesses and shapes on the cables
Summary
Atmospheric icing is referred to various processes in which water droplets in atmosphere freeze and adhere to surfaces potentially posing severe risks to the security of man-made structures [1, 2]. Freezing rain is a type of precipitation icing, and it forms when crystals of snow melt before hitting the surface [11]. Development of coatings to prevent ice/snow accumulation and, in case of any formation, reduce their adhesion strength to surfaces has received considerable attention [3, 4, 10, 15]. There is a weak adhesion force between the surface and the snow blocks at subfreezing temperatures due to low liquid water content of snowflakes, meaning that the snow accumulation only occurs at low wind speeds (V ≤ 2 m/s) [16]. We developed a model that takes into account the orientation of the cable in determining the effective wind impact speed to obtain realtime thickness, location, and shape of wet snow accumulation on torsionally rigid inclined cylinders. We developed and conducted extensive outdoor experiments to understand impact of snow precipitation parameters on its density and to verify the shape and thickness of accumulated snow on surfaces, obtained from the numerical studies
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