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Technical Paper

HPC-LES for Unsteady Aerodynamics of a Heavy Duty Truck in Wind Gust - 1st report: Validation and Unsteady Flow Structures

2010-04-12
2010-01-1010
Large eddy simulation based on high-performance computing technique was conducted to investigate the unsteady aerodynamic forces acting on a full-scale heavy duty truck subjected to sudden crosswind. The CFD results were applied to evaluate the effect of the unsteady external forces on a vehicle motion, as a first step toward a more reliable vehicle motion analysis. As the first report, the numerical method was validated on the DNW wind-tunnel data by comparing the time-averaged drag and lateral forces at various yawing angles up to 10 degrees. Then the method was applied to the case when the vehicle goes through the crosswind region. The time series of the aerodynamic forces were acquired and discussed through the visualization of instantaneous flow structures around the vehicle. It was observed that drastic undershooting and overshooting of the yawing moment acts on the vehicle during the rushing in and out process.
Technical Paper

Investigation of Increase in Aerodynamic Drag Caused by a Passing Vehicle

2018-04-03
2018-01-0719
On-road turbulences caused by sources such as atmospheric wind and other vehicles influence the flow field and increases the drag in a vehicle. In this study, we focused on a scenario involving a passing vehicle and investigated its effect on the physical mechanism of the drag increase in order to establish a technique for reducing this drag. Firstly, we conducted on-road measurements of two sedan-type vehicles passed by a truck. Their aerodynamic drag estimated from the base pressure measurements showed different increment when passed by the truck. This result raised the possibility of reducing the drag increase by a modification of the local geometry. Then, we conducted wind tunnel measurements of a simplified one-fifth scale vehicle model in quasi-steady state, in order to understand the flow mechanism of the drag increase systematically.
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