Yajun Fan

The sensitivity of the drag to the rear design of a flat-back body is investigated under different body attitudes defined by the pitch (-1.5o, 0o, +1.5o) and yaw (up the 15o). The rear design consists of taper angles at the top and bottom trailing edge varying from 0o (no taper) to 12.5o. Compared to the fixed optimal rear design that minimizes drag at the wind-aligned body attitude, the rear design adaptation to the change of attitude produces a noticeable drag reduction up to 3% and 5% when the pitch is varied within a yaw range smaller than 3o. It is shown that this drag reduction is related to the vertical wake steady instability interfering with the rear design. For yaw larger than 3o and up to 12o, an almost constant drag reduction of 2% is found and shown to be a compromise between a beneficial pressure recovery on the flat base and a detrimental pressure drag on the tapers. At larger yaw and independently to the pitch, there is no compromise anymore such that any taper angle different from 0o produces a drag increase leading eventually to the squareback rear design as the optimal design. Overall, the study emphasizes the potential of adaptive control of the top and bottom trailing edge tapers to arbitrary body attitude even at small yaw when the pitch is varied.

We propose a novel reduced-order model and examine its applicability to the complex three-dimensional turbulent wake of a generic square-backed bluff body called the Ahmed body at Reynolds number Re_H =U_∞H/ν =9.2×10⁴ (where U_∞ is free-stream velocity, H the height of the body and ν viscosity). Training datasets are obtained by large eddy simulation (LES). The model reduction method consists of two components, a VGG-based hierarchical autoencoder (H-VGG-AE) and a temporal convolutional neural network (TCN). The first step is to map the high-dimensional flow attributes into low-dimensional features, namely latent modes, which are employed as the input for the second step. The TCN is then trained to predict the low-dimensional features in a time series. We compare this method with a TCN based on proper orthogonal decomposition (POD), which utilizes time coefficients as the input in the second part. It turns out that the H-VGG-AE has a lower reconstruction error than POD when the number of latent modes is relatively small in the first part. As the number of latent modes increases, POD exceeds in the performance of model reduction. However, the H-VGG-AE-based TCN is still more effective in terms of spatio-temporal predictions because it has a lower prediction error and costs much less time.

The flow around a seal-vibrissa-shaped cylinder (SVSC) is numerically investigated using the large eddy simulation framework at a Reynolds number of 20 000. Compared with a circular cylinder (CC), the wake of the SVSC presents more stable three-dimensional separation, a longer vortex formation length, and a weaker vortex strength. The mean drag and fluctuation of the lift coefficient are 59.5% and 87.7% lower than those of the CC, respectively. Three-dimensional spectral proper orthogonal decomposition (SPOD) is used to investigate the turbulent flow around these two types of cylinders in terms of the spatial modes, mode energy, mode coefficients, and reconstructed flow by a reduced-order modeling. Four typical vortex shedding patterns are first extracted by SPOD for the SVSC, producing crescent-, twist-, branch-, and knot-shaped vortices. A concept model is proposed for the wake dynamics of the SVSC, allowing the formation and transformation of these modes to be elucidated. Detailed analysis of the impact of the flow pattern on the associated forces indicates that the dominant out-phase vortex shedding at the upper and lower saddle planes makes a significant contribution to the reduction in lift fluctuations.

The wake dynamics of a rectangular flat-backed bluff body is studied using both the wind tunnel experiment and Improved Delayed Detached Eddy Simulation (IDDES) at Re = 9.2 × 10⁴. Both approaches are systematically investigated in order to provide a quantitative comparison. The wake barycenter deficit and base pressure gradient dynamics are first investigated to characterize the wake states. Second, the known global dynamics such as long-term bi-stability, vortex shedding, and wake pumping are analyzed using proper orthogonal decomposition. It is found that the wake dynamics is globally well captured by the IDDES, but with a more intense activity due to the absence of the fore-body separations observed in the experiment. The coupling of these global dynamics is explored by utilizing low-order modeling in cross planes and elaborating the evolution of the three-dimensional (3D) instantaneous wake flow from IDDES. The shedding of a large-scale hairpin vortex from the horizontal shear layer is closely associated with the pumping motion during wake switchings or switching attempts. A concept model is proposed for 3D bi-stable wake topology, which attempts to elucidate both asymmetric and symmetric wake configurations.