CFD Investigation of Aerodynamic Drag Reduction for an Unloaded Timber Truck

Sammanfattning: The road transport industry is facing a strong need for fuel consumption reduction, driven by the necessity of decreasing polluting emissions, such as CO2 and NOX, as well as coping with strict regulations and increasing fuel costs. For road vehicles the aerodynamic drag constitutes a major source of energy consumption, and for this reason improving the aerodynamic performance of the vehicle is an established approach for reducing fuel consumption and greenhouse gases emissions. In this Thesis work, Computational Fluid Dynamics (CFD) investigations have been carried out in order to investigate and improve the aerodynamic performance of an unloaded timber truck. The work has been divided in two parts. In a first phase, a preliminary study was carried out on a simplified tractor-trailer model in order to establish a suitable computational grid and turbulence model. The hexcore-mesh showed a better performance over the tet- and poly-mesh types. Among the selected RANS turbulence models, the Realizable k − ε with Enhanced Wall Treatment (EWT) and y+ > 30 showed the highest reliability of results in comparison with experimental data and existing CFD investigations. In a second phase, the flow field around the baseline unloaded timber truck was analysed in order to highlight potential regions for drag reduction. The truck cabin-bulkhead gap, bunks, the exposed wheels and the stakes were found make key contribution to the drag build-up. The analysis confirmed the 5◦-yaw case to be the most representative for the wind-averaged drag coefficient. Geometry modifications were implemented in order to improve the aerodynamic performance in the selected areas, and subsequently combined into aero-kits in order to enhance the performance, analysed for the 5◦-yaw case. The combination of extended side skirts, bulkhead shield and collapsed stakes yielded a remarkable result of more than 30% decrease in the wind-averaged drag coefficient, achieved by reducing the flow separation on the cabin leeward A-pillar, and by shielding areas of high stagnation pressure from the side wind. Furthermore, a parallel study was conducted on the development of a procedure for the automatic post-processing of results. The outcome was a set of Python scripts to be used with Kitaware Paraview in order to automatically obtain figures of surface variables distributions, iso-surfaces, velocity profiles, drag build-up and total pressure contours. The procedure was finally extended to include the case comparison.