Numerical study of flow over a bluff body with drag reduction devices
2nd International Conference on Fluid Dynamics & Aerodynamics
October 19-20, 2017 | Rome, Italy

Adam Abikan, Yiling Lu and Zhiyin Yang

University of Derby, UK

Posters & Accepted Abstracts: J Appl Mech Eng

Abstract:

The aerodynamics performance of heavy vehicles is relatively poor compared against other ground vehicles due to their un-streamlined body shapes which cause massive flow separation. This phenomenon is more pronounced for heavy trucks which usually have a boxy shape with many sharp edges, leading to higher aerodynamics drag. Hence aerodynamic drag reduction is very important and has been one of the major concerns of heavy trucks since it is directly related to fuel consumption with approximately 4% fuel savings by a 20% aerodynamic drag reduction at an operating speed of 105 km/h for a tractor-trailer weighing 36 tons. The aerodynamic drag distribution for a truck is usually split as: the front face of a tractor generates a drag of 25%, the gap between the tractor and trailer generates a 20% drag with the rear of the trailer generating another 25% drag, and the rest 30% of the total drag is due to the underside of the truck. The focus of our study is on the aerodynamic drag reduction in the rear of a truck and this paper presents a numerical investigation of flow over bluff body with drag reduction devices since the flow field behind a heavy truck and a bluff body is very similar. The numerical model was validated first by comparing the predictions against the experimental data. Figure 1 shows the comparison between the predicted axial mean velocity profile and the experimental data in the wake region and a reasonably good agreement is obtained, with the general feature and trend well captured by the prediction although the reverse flow is over-predicted. Figure 2 presents the comparison between the predicted normal Reynolds stress in the axial direction against the experimental data and the agreement is reasonable, especially the double peak feature is well predicted although the predicted peak locations are slightly lower. Those are just preliminary results and more refined results with detailed analysis will be presented in the paper, in particular the results with drag devices will be presented and analyzed to demonstrate the effectiveness of those devices.