Abstract

The snow particles entrained in the wake of the snowplow (i.e. snow cloud) and the subsequent snow accumulation on the warning lights appear as the most pronounced visibility problems behind the snowplow truck. Computational fluid dynamics (CFD) methods are employed with detailed 2D and 3D models of the snowplow trucks (1) to evaluate the performance of the add-on devices (airfoils) available in the market which improve the rear visibility of truck by the public; (2) to gain more insight over the snow cloud pattern. Considering the low density of snow particles and high drag coefficient, they are assumed to follow air flow and their effect on the flow pattern is neglected. The effect of airfoil on the snow accumulation behind the truck is quantified by pressure and shear stress distribution. The airfoil selected based on the numerical studies is implemented on the back of the truck and tested in the field. The results confirmed the rear visibility performance increase by the airfoil over the base configuration. Three dimensional velocity and pressure measurements at twelve different locations on the rear surface of the truck are performed to validate the computational model. The calibration and design of the instruments used for the field test are done with extensive wind tunnel experiments. The error analysis is performed and the computational predictions are compared with the with field test results.