Fan Yajun, Xia Chao, Ge Diandian, Yang Zhigang. Experimental investigation of the unsteady wake of the square-back Ahmed model[J]. Journal of Experiments in Fluid Mechanics, 2019, 33(6): 84-89. DOI: 10.11729/syltlx20190112
Citation: Fan Yajun, Xia Chao, Ge Diandian, Yang Zhigang. Experimental investigation of the unsteady wake of the square-back Ahmed model[J]. Journal of Experiments in Fluid Mechanics, 2019, 33(6): 84-89. DOI: 10.11729/syltlx20190112

Experimental investigation of the unsteady wake of the square-back Ahmed model

  • The square-back Ahmed model is a simplified commercial vehicle body model. The flow separates at the tail to form a recirculation region, leading to the negative pressure on the back and large aerodynamic drag. The unsteady wake of the 1/4-scale square back Ahmed model were finely measured and statistically analyzed via the wind tunnel test. The experimental Reynolds number was 9.2×104. The results of the back pressure measurement, particle image velocimetry (PIV) and hot-wire measurement show that the unsteady wake pattern of the square back Ahmed model basically consists of three flow characteristics: the bi-stable behavior (random asymmetry between the left and right vortex structures), vortex shedding in the horizontal and vertical direction, and pumping of the recirculation region periodically. Among them, the bi-stable phenomenon plays a dominant role in the wake. It shows the alternating occurrence of two stable states (the transition probability is 0.149). Each stable state can maintain a long time scale (the average duration is about 6 s), and its spectral characteristics satisfy the -2 power law distribution; the corresponding frequency of the periodic pumping oscillation is SrH=0.07; and the vortex shedding frequencies corresponding to the oscillations in the horizontal direction and the vertical direction are SrH=0.13 and SrH=0.17, respectively. The interaction among these structures exists, and thus the unsteady wake of the square back Ahmed model presents complex three-dimensional features.
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