Identification of lagrangian coherent structures in the turbulent boundary layer

Pan, Chong; Wang, Jinjun; Cao, Zhang

doi:10.1007/s11433-009-0033-1

Cited by 50 publications

(30 citation statements)

References 19 publications

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“…Also, an empirical, and arguable subjective, threshold is inherently needed for defining the boundaries of CS. A recent method identifies Lagrangian coherent structures (LCS) (Shadden et al 2006), which seems to be more 'objective' than Eulerian-based schemes, but requires substantially higher temporal resolution (Pan et al 2009). …”

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confidence: 99%

Velocity–vorticity correlation structure in turbulent channel flow

et al. 2014

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A new statistical coherent structure (CS), the velocity-vorticity correlation structure (VVCS), using the two-point cross-correlation coefficient R ij of velocity and vorticity components, u i and ω j (i, j = 1, 2, 3), is proposed as a useful descriptor of CS. For turbulent channel flow with the wall-normal direction y, a VVCS study consists of using u i at a fixed reference location y r , and using |R ij (y r ; x, y, z)| R 0 to define a topologically invariant high-correlation region, called VVCS ij . The method is applied to direct numerical simulation (DNS) data, and it is shown that the VVCS ij qualitatively and quantitatively captures all known geometrical features of near-wall CS, including spanwise spacing, streamwise length and inclination angle of the quasi-streamwise vortices and streaks. A distinct feature of the VVCS is that its geometry continuously varies with y r . A topological change of VVCS 11 from quadrupole (for smaller y r ) to dipole (for larger y r ) occurs at y + r = 110, giving a geometrical interpretation of the multilayer nature of wall-bounded turbulent shear flows. In conclusion, the VVCS provides a new robust method to quantify CS in wall-bounded flows, and is particularly suitable for extracting statistical geometrical measures using two-point simultaneous data from hotwire, particle image velocimetry/laser Doppler anemometry measurements or DNS/large eddy simulation data.

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confidence: 99%

Velocity–vorticity correlation structure in turbulent channel flow

et al. 2014

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“…Using numerical simulation, I obtained new results not previously reported and found basic patterns for collective behaviors. Therefore, this study has value in searching for the connection of dynamics between few and many bodies [31,32]. We expect more valuable achievements in the future.…”

Section: Discussionmentioning

confidence: 85%

Collective behavior of coupled map lattices with different scales of local coupling

Shi

2011

Chin. Sci. Bull.

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In this paper, I present a numerical study on the collective behavior of one-dimensional coupled map lattices with the nearest coupling to different scales for the whole system. Using the maximum Lyapunov exponent as a tool for subsystem and return mapping, I observed several basic patterns of collective behavior and investigated the contrasts between the different scales. To study the mechanism, the system under entirely random perturbations was investigated using the Monte Carlo method and the contrast with the deterministic approach is given. The results show that the response to a random input is complicated and involves the correlation of different signals and taking into consideration the dynamic properties of the system itself. subsystem, maximum Lyapunov exponent, different scale, return map, random perturbation Citation:Shi W J. Collective behavior of coupled map lattices with different scales of local coupling.Space-time chaos has been studied for many years and is still a major topic of research. Using coupled map lattices (CMLs) as a basic model for studying space-time chaos has received increased attention for some time [1]. Previous research on this model has mainly been applied to global dynamics, while little consideration of the dynamics has been given to different scales of the system as the lattices were assumed to be coarse grained. However, if the system has some collective behavior, the dynamics for different scales of the system should be considered. On the other hand, the relationship between few and many bodied systems continues to attract great interest. A similar pertinent question is whether I can also treat the dynamics of the CML with a deterministic approach and add random perturbations? An interesting paper [2] gives a positive answer to this for a special case, although random noise is artificially added. From the research presented in this paper, it is clear that the question is a difficult one. Furthermore, recent works related to nontrivial collective behavior has attracted wide attention. In particular, using Lyapunov modes gives a very new and profound comprehension of collective spatiotemporal chaotic behaviors [3]. In this paper, I aim to carry out a numerical study of collective behaviors for various local scales of the whole system (the scale here is the length of a subsystem). Common and extensively studied models (CML) are employed.

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“…It is found that the convection motions gradually reach the mean velocity away from the wall, which is similar to the tendency shown in Pan et al's work. [45] Alamo and Jiménez [27] proposed an approximate formula in which the convection velocity is regarded as the average of the mean velocity profile with 104703-5 a weight function. Because the conditional-averaged convection velocity is calculated based on the real swirling motions in the flow, it has more realistic significance than the convection velocity calculated from the correlation.…”

Section: Space Time Correlationmentioning

confidence: 99%

Convection and correlation of coherent structure in turbulent boundary layer using tomographic particle image velocimetry

Wang¹,

Guan²,

Jiang³

2014

Chinese Phys. B

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The present experimental work focuses on a new model for space-time correlation and the scale-dependencies of convection velocity and sweep velocity in turbulent boundary layer over a flat wall. A turbulent boundary layer flow at Re θ = 2460 is measured by tomographic particle image velocimetry (tomographic PIV). It is demonstrated that arch, cane, and hairpin vortices are dominant in the logarithmic layer. Hairpins and hairpin packets are responsible for the elongated low-momentum zones observed in the instantaneous flow field. The conditionally-averaged coherent structures systemically illustrate the key roles of hairpin vortice in the turbulence dynamic events, such as ejection and sweep events and energy transport. The space-time correlations of instantaneous streamwise fluctuation velocity are calculated and confirm the new elliptic model for the space-time correlation instead of Taylor hypothesis. The convection velocities derived from the space-time correlation and conditionally-averaged method both suggest the scaling with the local mean velocity in the logarithmic layer. Convection velocity result based on Fourier decomposition (FD) shows stronger scale-dependency in the spanwise direction than in streamwise direction. Compared with FD, the proper orthogonal decomposition (POD) has a distinct distribution of convection velocity for the large-and small-scales which are separated in light of their contributions of turbulent kinetic energy.

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Identification of lagrangian coherent structures in the turbulent boundary layer

Cited by 50 publications

References 19 publications

Velocity–vorticity correlation structure in turbulent channel flow

Velocity–vorticity correlation structure in turbulent channel flow

Collective behavior of coupled map lattices with different scales of local coupling

Convection and correlation of coherent structure in turbulent boundary layer using tomographic particle image velocimetry

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