Understanding the mechanisms of snow adhesion to surfaces and its subsequent shedding provides means to search for active and passive methods to mitigate the issues caused by snow accumulation on surfaces. Here, a novel setup is presented to measure the adhesion strength of snow to various surfaces without altering its properties (i.e., liquid water content (LWC) and/or density) during the measurements and to study snow shedding mechanisms. In this setup, a sensor is utilized to ensure constant temperature and liquid water content of snow on test substrates, unlike inclined or centrifugal snow adhesion testing. A snow gun consisting of an internal mixing chamber and ball valves for adjusting air and water flow is designed to form snow with controlled LWC inside a walk-in freezing room with controlled temperatures. We report that snow adheres to surfaces strongly when the LWC is around 20%. We also show that on smooth (i.e., RMS roughness of less than 7.17 μm) and very rough (i.e., RMS roughness of greater than 308.33 μm) surfaces, snow experiences minimal contact with the surface, resulting in low adhesion strength of snow. At the intermediate surface roughness (i.e., RMS of 50 μm with a surface temperature of 0 °C, the contact area between the snow and the surface increases, leading to increased adhesion strength of snow to the substrate. It is also found that an increase in the polar surface energy significantly increases the adhesion strength of wet snow while adhesion strength decreases with an increase in dispersive surface energy. Finally, we show that during shedding, snow experiences complete sliding, compression, or a combination of the two behaviors depending on surface temperature and LWC of the snow. The results of this study suggest pathways for designing surfaces that might reduce snow adhesion strength and facilitate its shedding.

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.

With the rapid development of artificial intelligence, the autonomous vehicles (AV) have attracted considerable attention in the automotive industry. However, different factors negatively impact the adoption of the AVs, delaying their successful commercialization. Accretion of atmospheric icing, especially wet snow, on AV sensors causes blockage on their lenses, making them prone to lose their sight, in turn, increasing potential chances of accidents. In this study, two different designs are proposed in order to prevent snow accretion on the lenses of AVs via air flow across the lens surface. In both designs, lenses made of plain glass and superhydrophobic coated glass surfaces are tested. While some researchers have shown promise of water repellency on superhydrophobic surfaces, more snow accretion is observed on the superhydrophobic surfaces, when compared to the plain glass lenses. In the experiments, snow is formed using a novel snow gun inside a walk-in cold room connected to a wind tunnel that can reach wind speeds of up to 40 mph. It is observed that the air flow over the lens significantly reduces the accretion of snow on the lens and could maintain the lens clean for up to 20 mph wind velocities. However, at LWC values of approximately 28%, the stickiness of the snowflakes increases, enhancing snow accretion on the lenses and translating to significant loss of sight. The high stickiness of the snowflakes along with high wind speeds leads to increased blockage of the AV lenses.

Damages due to a fault activity can be divided into dynamic rupture and quasi-static rupture. In some special projects like roads, channels, and pipelines, engineers have to design and construct them on the faults inescapably. In addition to seismic design, the effects of fault rupture crossing the structures must be considered in the design process. In this paper, four different computer models of a granular alluvium with and without tunnel were made by a three-dimensional finite-difference software. A normal fault offset with three different cross angles was applied to the bottom of the models at the next step. Then, the shear bands propagation and ground deformations were calculated. The results show that the effects of tunnel existence on the ground deformations and shear band propagation depend on the cross angle.