Wall-modeling for large-eddy simulation of flows around an axisymmetric body using the diffuse-interface immersed boundary method

A novel method is proposed to combine the wall-modeled large-eddy simulation(LES) with the diffuse-interface direct-forcing immersed boundary(IB) method.The new developments in this method include:(i) the momentum equation is integrated along the wall-normal direction to link the tangential component of the effective body force for the IB method to the wall shear stress predicted by the wall model;(ii) a set of Lagrangian points near the wall are introduced to compute the normal component of the effective body force for the IB method by reconstructing the normal component of the velocity. This novel method will be a classical direct-forcing IB method if the grid is fine enough to resolve the flow near the wall. The method is used to simulate the flows around the DARPA SUBOFF model. The results obtained are well comparable to the measured experimental data and wall-resolved LES results.

Wall-resolved large-eddy simulation of turbulent channel flows with rough walls

Turbulent flows over rough surfaces widely exist in nature and industry.Investigating its mechanism is of theoretical and practical significance.In this work we simulate the turbulent channel flow with rough walls using large-eddy simulation with rough elements resolved using the curvilinear immersed boundary method and compare the results obtained in this work with those in the paper by Yuan and Piomelli(J.Fluid Mech.,vol.760,pp.R1,2014),where the volume of fluid method was employed for modeling rough elements.The mean streamwise velocity profiles predicted by the two methods agree well with each other.Differences in Reynolds stresses and dispersive stresses are observed,which are attributed to the different approaches in dealing with the complex geometry of the rough surface.

Effects of the Reynolds number on a scale-similarity model of Lagrangian velocity correlations in isotropic turbulent flows

A scale-similarity model of a two-point two-time Lagrangian velocity correlation(LVC) was originally developed for the relative dispersion of tracer particles in isotropic turbulent flows(HE, G. W., JIN, G. D., and ZHAO, X. Scale-similarity model for Lagrangian velocity correlations in isotropic and stationary turbulence. Physical Review E, 80, 066313(2009)). The model can be expressed as a two-point Eulerian space correlation and the dispersion velocity V. The dispersion velocity denotes the rate at which one moving particle departs from another fixed particle. This paper numerically validates the robustness of the scale-similarity model at high Taylor micro-scale Reynolds numbers up to 373, which are much higher than the original values(R_λ = 66, 102). The effect of the Reynolds number on the dispersion velocity in the scale-similarity model is carefully investigated. The results show that the scale-similarity model is more accurate at higher Reynolds numbers because the two-point Lagrangian velocity correlations with different initial spatial separations collapse into a universal form compared with a combination of the initial separation and the temporal separation via the dispersion velocity.Moreover, the dispersion velocity V normalized by the Kolmogorov velocity V_η ≡ η/τ_η in which η and τ_η are the Kolmogorov space and time scales, respectively, scales with the Reynolds number R_λ as V/V_η ∝ R_λ^(1.39) obtained from the numerical data.

Lattice Boltzmann simulations of high-order statistics in isotropic turbulent flows

The lattice Boltzmann method （LBM） is coupled with the multiple-relaxation- time （MRT） collision model and the three-dimensional 19-discrete-velocity （D3Q19） model to resolve intermittent behaviors on small scales in isotropic turbulent flows. The high- order scaling exponents of the velocity structure functions, the probability distribution functions of Lagrangian accelerations, and the local energy dissipation rates are investi- gated. The self-similarity of the space-time velocity structure functions is explored using the extended self-similarity （ESS） method, which was originally developed for velocity spatial structure functions. The scaling exponents of spatial structure functions at up to ten orders are consistent with the experimental measurements and theoretical results, implying that the LBM can accurately resolve the intermittent behaviors. This valida~ tion provides a solid basis for using the LBM to study more complex processes that are sensitive to small scales in turbulent flows, such as the relative dispersion of pollutants and mesoscale structures of preferential concentration of heavy particles suspended in turbulent flows.

Response of turbulent enstrophy to sudden implementation of spanwise wall oscillation in channel flow

The response of turbulent enstrophy to a sudden implementation of spanwise wall oscillation（SWO） is studied in a turbulent channel flow via direct numerical simulation. In the beginning of the application of SWO, a significant correlation is formed between ω′yand ω′z. A transient growth of turbulent enstrophy occurs, which directly enhances turbulent dissipation and drifts the turbulent flow towards a new lower-drag condition. Afterwards, the terms related to the stretching of vorticity（ωx, ω′y, and ωz）,the inclination of ω′yby ？w/？y, the turn of z by ？v′/？z, and the horizontal shear of z by ？w′/？x are suppressed due to the presence of SWO, leading to attenuation of the turbulent enstrophy.

Template-guided frequency attention and adaptive cross-entropy loss for UAV visual tracking

This paper addresses the problem of visual object tracking for Unmanned Aerial Vehicles(UAVs).Most Siamese trackers are used to regard object tracking as classification and regression problems.However,it is difficult for these trackers to accurately classify in the face of similar objects,background clutters and other common challenges in UAV scenes.So,a reliable classifier is the key to improving UAV tracking performance.In this paper,a simple yet efficient tracker following the basic architecture of the Siamese neural network is proposed,which improves the classification ability from three stages.First,the frequency channel attention module is introduced to enhance the target features via frequency domain learning.Second,a template-guided attention module is designed to promote information exchange between the template branch and the search branch,which can get reliable classification response maps.Third,adaptive cross-entropy loss is proposed to make the tracker focus on hard samples that contribute more to the training process,solving the data imbalance between positive and negative samples.To evaluate the performance of the proposed tracker,comprehensive experiments are conducted on two challenging aerial datasets,including UAV123 and UAVDT.Experimental results demonstrate that the proposed tracker achieves favorable tracking performances in aerial benchmarks beyond 41 frames/s.We conducted experiments in real UAV scenes to further verify the efficiency of our tracker in the real world.

Numerical implementation and evaluation of resolvent-based estimation for space-time energy spectra in turbulent channel flows

Resolvent operator has been increasingly used to investigate turbulent flows and develop control strategies.Recently,Towne et al.(J Fluid Mech 883:A17,2020)proposed a resolvent-based estimation(RBE)method for predicting turbulent statistics in a channel flow.In this paper,we utilize the RBE method to predict the root-mean-square(RMS)and space-time energy spectra of streamwise velocity fluctuation,where the input is the space-time energy spectra at a reference horizontal plane located in the logarithmic layer and the output is the space-time energy spectra in the buffer layer.The explicit formulas for the RBE method are given in detail for numerical implementation.The results show the capability of the RBE method in the prediction of the convection velocity and bandwidth of the space-time energy spectra.Furthermore,we make a systematic evaluation of the performance of the RBE method by varying the input configurations,including the wall-normal location of the reference plane,the inclusion or exclusion of the pressure as an input variable,the implementation approach of the pressure boundary condition,and the choice of the window function.It is found that the results of both RMS velocity and space-time energy spectra obtained from the RBE method are sensitive to the location of the reference plane.However,the pressure boundary conditions and inclusion of pressure as an input do not cause significant change in the RMS velocity and space-time energy spectra.Although it does not influence the prediction of the RMS velocity,a window function is found crucial in the RBE method for the prediction of the space-time energy spectra.