Simulating atmospheric boundary layer for trucks

The application of an atmospheric boundary layer to evaluate truck aerodynamics in CFD

As part of a MSc graduation project at DAF Trucks NV an atmospheric boundary layer is applied in CFD to evaluate the effects on truck aerodynamics. The atmospheric boundary layer is one of the major differences between the flow conditions at real driving situations versus wind tunnel and CFD test situations. In the boundary layer, which is usually a few hundred meters thick, the wind velocity profile near the ground can be considered logarithmic, similar to the regular boundary layer theory. As a result of the wind velocity profile the truck faces a varying air speed over height, as well as the yaw angle. Another aspect of importance is the turbulence level in the flow, which in realistic road conditions is usually larger than in wind tunnel experiments and CFD simulations.

Numerical simulations are done using  STAR-CCM+® performing steady-state RANS simulations with the K-Omega SST and K-Epsilon turbulence models. The atmospheric boundary layer is simulated within an empty domain, i.e. without a truck, in order to monitor the profile development through the domain in longitudinal direction. The development of the velocity profile appears to be very sensitive to the boundary conditions, the mesh settings and the turbulence models and parameters such as turbulence length scale and intensity. In order to avoid this development, a specific combination of boundary conditions and mesh settings is applied for one particular atmospheric boundary layer without alternating the settings in the turbulence models.  As a result, the specified atmospheric boundary layer at the input is equal to the air profile at the location where the truck will be positioned.

The presentation will elaborate on the numerical aspects of this study.

DAF Trucks NV
Niek van Dijk
Session Time Slot(s): 
06/03/2017 - 2:00pm-06/03/2017 - 2:25pm
Convention Hall 1C
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Session Track: 

Session Tracks (STAR Global Conference 2017)