Space-Time Correlations and Dynamic Coupling in Turbulent Flows

He, Guowei; Jin, Guodong; Yang, Yue

doi:10.1146/annurev-fluid-010816-060309

Cited by 149 publications

(103 citation statements)

References 127 publications

(135 reference statements)

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“…These spectra are particularly useful in studies of multi-scale coupling in space and time [1,2]. However, obtaining full space-time energy spectra from experimental measurements remains challenging [3] because only a subset of the spatial and temporal signals of the velocity fluctuations is experimentally available.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of space-time energy spectra in turbulent channel flows

Geng

Yao

et al. 2017

Phys. Rev. Fluids

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An energy spectrum is preliminarily characterized by its mean and standard deviation. In this study, we derive exact expressions for the means and bandwidths of space-time energy spectra at fixed frequencies. The mean wave numbers are used to determine the phase velocities that bridge from temporal spectra to space-time spectra. The bandwidths are used to measure the well-known spectral broadening. We show that phase velocities alone are insufficient to determine the bandwidths of energy spectra. As a result, the cross-spectral method predicts narrower bandwidths of energy spectra. Therefore, in addition to phase velocities, amplitudes are used to rescale the space-time energy spectra, leading to the correct bandwidths. Existing data from direct numerical simulations of turbulent channel flows validate the rescaling approach.

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Section: Introductionmentioning

confidence: 99%

Characteristics of space-time energy spectra in turbulent channel flows

Geng

Yao

et al. 2017

Phys. Rev. Fluids

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“…As mentioned before, the settling velocities obtained from different approaches are expected to have some differences due to the complex physics after the tumbling stage of two particles. This may need more accurate modeling of the turbulence effects in the fluid‐particle interaction within localized areas . In contrast, the conventional SPH yields very poor results compared to the DLM/FDM solutions.…”

Section: Numerical Investigations On Particle Sedimentationmentioning

confidence: 99%

“…This may need more accurate modeling of the turbulence effects in the fluid-particle interaction within localized areas. 81 In contrast, the conventional SPH yields very poor results compared to the DLM/FDM solutions. To intuitively show the differences between the conventional and modified SPH results, the velocity distributions in the fluid obtained using the conventional SPH, modified…”

Section: Double-particle Sedimentationmentioning

confidence: 99%

Meshfree modeling of a fluid‐particle two‐phase flow with an improved SPH method

Zhang

Walayat

Chang

et al. 2018

Numerical Meth Engineering

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Summary Fluid‐particle two‐phase flows are very complex and quite challenging to numerically simulate due to the complex and constantly moving fluid‐particle interface. Recent developments in meshfree and particle methods provide alternatives in modeling fluid flows with moving boundaries. In this paper, a modified smoothed particle hydrodynamics (SPH) method is developed to simulate particle sedimentation (two‐dimensional) in Newtonian fluids. The modified SPH includes an enhanced particle approximation scheme, an effective solid boundary treatment algorithm, the artificial stress model, and a turbulence model. By decoupling a field variable and its derivatives in a finite particle method, a decoupled finite particle method is presented, which balances accuracy, efficiency, and stability in SPH simulations without the necessity of solving redundant and challenging corrective matrix equations. A coupled dynamic solid boundary treatment is developed to improve the accuracy near the fixed and moving solid boundaries. The artificial stress term is added into the SPH equations of motion to remove the possible tensile instability phenomenon. The large eddy simulation model is incorporated into the SPH to describe the turbulence effects at high Reynolds numbers. Four different particle sedimentation tests are conducted using the modified SPH along with the finite element fictitious boundary method. It is demonstrated that the improved SPH method can achieve much better results than the conventional SPH while showing a good comparison with the results from the finite element fictitious boundary method and from other sources.

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“…However, most models only provide the statistical characteristics of turbulence. For example, 1-point statistical results such as mean velocity profile (Clauser, 1956), turbulence intensity (Marusic & Kunkel, 2003), power spectra (Perry et al, 1986), and Eulerian time correlation (Comte-Bellot & Corrsin, 1971) and multipoint statistical results such as space correlations, space-time correlations (He et al, 2017;He & Zhang, 2006), and structure functions (Davidson & Krogstad, 2014;De Silva et al, 2015;Kolmogorov, 1941aKolmogorov, , 1941b can be predicted by the existing models. A model for the prediction of flow field is very rare.…”

Section: Introductionmentioning

confidence: 99%

A Predictive Model for the Streamwise Velocity in the Near‐Neutral Atmospheric Surface Layer

Han

Liu

et al. 2019

JGR Atmospheres

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For the reconstruction of the streamwise velocity field in the high‐Reynolds‐number (Reτ ≈ Ο(106)) near‐neutral atmospheric surface layer (ASL), a predictive model was proposed in our work. In our model, the streamwise velocity time series at each height are predicted by the superposition of mean velocity, small‐scale turbulent signals, and large‐scale turbulent signals. All the parameters used by our model have clear physical meaning. In addition, the parameters can be directly determined by the experiment that is easy to be achieved in the ASL. The model can predict the streamwise velocity between 0.9 and 30 m in the near‐neutral ASL based only on single‐point‐measured large‐scale streamwise velocity signal. For example, mean velocity, turbulence intensity, and power spectrum of streamwise velocity can be predicted by the new model. Furthermore, the streamwise velocity time series predicted by the new model have a good correlation with the directly measured results, especially for large‐scale structures. It indicates that our model can be used to reconstruct the streamwise velocity field in the logarithmic region of the near‐neutral ASL, and our model is an important complement to the Marusic‐Mathis‐Hutchins model.

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Space-Time Correlations and Dynamic Coupling in Turbulent Flows

Cited by 149 publications

References 127 publications

Characteristics of space-time energy spectra in turbulent channel flows

Characteristics of space-time energy spectra in turbulent channel flows

Meshfree modeling of a fluid‐particle two‐phase flow with an improved SPH method

A Predictive Model for the Streamwise Velocity in the Near‐Neutral Atmospheric Surface Layer

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