arXiv subjects

Yongxiang Huang

Publications and source records attributed to Yongxiang Huang.

27 records · Page 2Linked to original sources

arXiv2019

Turbulent lithosphere deformation in the Tibetan Plateau

In this work, we show that the Tibetan Plateau deformation demonstrates a turbulence-like statistics, e.g., spatial invariance cross continuous scales. A dual-power-law behavior is evident to show the existence of two possible conversation laws for the enstrophy-like cascade on the range $500\lesssim r\lesssim 2,000\,\si{km}$ and kinetic-energy-like cascade on the range $50\lesssim r\lesssim 500\,\si{km}$. The measured second-order structure-function scaling exponents $ζ(2)$ are similar with the counterpart of the Fourier scaling exponents observed in the atmosphere, where in the latter case the earth rotation is relevant. The turbulent statistics observed here for nearly zero Reynolds number flow is favor to be interpreted by the geostrophic turbulence theory. Moreover, the intermittency correction is recognized with an intensity to be close to the one of the hydrodynamic turbulence of high Reynolds number turbulent flows, implying a universal scaling feature of very different turbulent flows. Our results not only shed new light on the debate regarding the mechanism of the Tibetan Plateau deformation, but also lead to new challenge for the geodynamic modelling using Newton or non-Newtonian model that the observed turbulence-like features have to be taken into account.

physics.flu-dyn↗

arXiv2018

Spatial statistics of atmospheric particulate matter in China

In this paper, the spatial dynamics of the atmospheric particulate matters (resp. PM$_{10}$ and PM$_{2.5}$) are studied using turbulence methodologies. It is found experimentally that the spatial correlation function $ρ(r)$ shows a log-law on the mesoscale range, i.e., $50\le r\le 500\,{km}$, with an experimental scaling exponent $β=0.45$. The spatial structure function shows a power-law behavior on the mesoscale range $90\le r\le 500\,{km}$. The experimental scaling exponent $ζ(q)$ is convex, showing that the intermittent correction is relevant in characterizing the spatial dynamic of particulate matter. The measured singularity spectrum $f(α)$ also shows its multifractal nature. Experimentally, the particulate matter is more intermittent than the passive scalar, which could be partially due to the \red{mesoscale movements} of the atmosphere, and also due to local sources, such as local industry activities.

physics.ao-ph↗

arXiv2018

Lagrangian Statistics and Intermittency in Gulf of Mexico

Due to the nonlinear interaction between different flow patterns, for instance, ocean current, meso-scale eddies, waves, etc, the movement of ocean is extremely complex, where a multiscale statistics is then relevant. In this work, a high time-resolution velocity with a time step 15 minutes obtained by the Lagrangian drifter deployed in the Gulf of Mexico (GoM) from July 2012 to October 2012 is considered. The measured Lagrangian velocity correlation function shows a strong daily cycle due to the diurnal tidal cycle. The estimated Fourier power spectrum $E(f)$ implies a dual-power-law behavior which is separated by the daily cycle. The corresponding scaling exponents are close to $-1.75$ and $-2.75$ respectively for the time scale larger (resp. $0.1\le f\le 0.4\,{day^{-1}}$) and smaller (resp. $2\le f\le 8\,{day^{-1}}$) than 1 day. A Hilbert-based approach is then applied to this data set to identify the possible multifractal property of the cascade process. The results show an intermittent dynamics for the time scale larger than 1 day, while a less intermittent dynamics for the time scale smaller than 1 day. It is speculated that the energy is partially injected via the diurnal tidal movement and then transferred to larger and small scales through a complex cascade process, which needs more studies in the near future.

physics.ao-ph↗

arXiv2018

Taylor dispersion in two-dimensional bacterial turbulence

In this work, single particle dispersion was analyzed for a bacterial turbulence by retrieving the virtual Lagrangian trajectory via numerical integration of the Lagrangian equation. High-order displacement functions were calculated for cases with and without mean velocity effect. Two-regime power-law behavior for short and long time evolutions were identified experimentally, which were separated by the Lagrangian integral time. For the case with the mean velocity effect, the experimental Hurst numbers were determined to be $0.94$ and $0.97$ for short and long times evolutions, respectively. For the case without the mean velocity effect, the values were $0.88$ and $0.58$. Moreover, very weak intermittency correction was detected. All measured Hurst number were above $1/2$, the value of the normal diffusion, which verifies the super-diffusion behavior of living fluid. This behavior increases the efficiency of bacteria to obtain food.

physics.flu-dyn↗

arXiv2018

Intrinsic flow structure and multifractality in two-dimensional bacterial turbulence

The active interaction between the bacteria and fluid generates turbulent structures even at zero Reynolds number. Velocity of such a flow obtained experimentally has been quantitatively investigated based on streamline segment analysis. There is a clear transition at about $16$ times of the organism body length separating two different scale regimes, which may be attributed to the different influence of the viscous effect. Surprisingly the scaling extracted from the streamline segment indicates the existence of scale similarity even at the zero Reynolds number limit. Moreover the multifractal feature can be quantitatively described via a lognormal formula with the Hurst number $H=0.76$ and the intermittency parameter $μ=0.20$, which is coincidentally in agreement with the three-dimensional hydrodynamic turbulence result. The direction of cascade is measured via the filter-space technique. An inverse energy cascade is confirmed. For the enstrophy, a forward cascade is observed when $r/R\le 3$, and an inverse one is observed when $r/R>3$. Additionally, the lognormal statistics is verified for the coarse-grained energy dissipation and enstrophy, which supports the lognormal formula to fit the measured scaling exponent.

physics.flu-dyn↗

arXiv2018

Extremal-point density of scaling processes from fractal Brownian motion to turbulence in one dimension

In recent years several local extrema based methodologies have been proposed to investigate either the nonlinear or the nonstationary time series for scaling analysis. In the present work we study systematically the distribution of the local extrema for both synthesized scaling processes and turbulent velocity data from experiments. The results show that for the fractional Brownian motion (fBm) without intermittency correction the measured extremal point density (EPD) agrees well with a theoretical prediction. For a multifractal random walk (MRW) with the lognormal statistics, the measured EPD is independent with the intermittency parameter $μ$, suggesting that the intermittency correction does not change the distribution of extremal points, but change the amplitude. By introducing a coarse-grained operator, the power-law behavior of these scaling processes is then revealed via the measured EPD for different scales. For fBm the scaling exponent $ξ(H)$ is found to be $ξ(H)=H$, where $H$ is Hurst number, while for MRW $ξ(H)$ shows a linear relation with the intermittency parameter $μ$. Such EPD approach is further applied to the turbulent velocity data obtained from a wind tunnel flow experiment with the Taylor scale $λ$ based Reynolds number $Re_λ= 720$, and a turbulent boundary layer with the momentum thickness $θ$ based Reynolds number $Re_θ= 810$. A scaling exponent $ξ\simeq 0.37$ is retrieved for the former case. For the latter one, the measured EPD shows clearly four regimes, which agree well with the four regimes of the turbulent boundary layer structures.

cond-mat.stat-mech↗

arXiv2018

Improving High Resolution Histology Image Classification with Deep Spatial Fusion Network

Histology imaging is an essential diagnosis method to finalize the grade and stage of cancer of different tissues, especially for breast cancer diagnosis. Specialists often disagree on the final diagnosis on biopsy tissue due to the complex morphological variety. Although convolutional neural networks (CNN) have advantages in extracting discriminative features in image classification, directly training a CNN on high resolution histology images is computationally infeasible currently. Besides, inconsistent discriminative features often distribute over the whole histology image, which incurs challenges in patch-based CNN classification method. In this paper, we propose a novel architecture for automatic classification of high resolution histology images. First, an adapted residual network is employed to explore hierarchical features without attenuation. Second, we develop a robust deep fusion network to utilize the spatial relationship between patches and learn to correct the prediction bias generated from inconsistent discriminative feature distribution. The proposed method is evaluated using 10-fold cross-validation on 400 high resolution breast histology images with balanced labels and reports 95% accuracy on 4-class classification and 98.5% accuracy, 99.6% AUC on 2-class classification (carcinoma and non-carcinoma), which substantially outperforms previous methods and close to pathologist performance.

cs.CV↗

arXiv2016

Intermittency measurement in two dimensional bacterial turbulence

In this paper, an experimental velocity database of a bacterial collective motion , e.g., \textit{B. subtilis}, in turbulent phase with volume filling fraction $84\%$ provided by Professor Goldstein at the Cambridge University UK, was analyzed to emphasize the scaling behavior of this active turbulence system. This was accomplished by performing a Hilbert-based methodology analysis to retrieve the scaling property without the $β-$limitation. A dual-power-law behavior separated by the viscosity scale $\ell_ν$ was observed for the $q$th-order Hilbert moment $\mathcal{L}_q(k)$. This dual-power-law belongs to an inverse-cascade since the scaling range is above the injection scale $R$, e.g., the bacterial body length. The measured scaling exponents $ζ(q)$ of both the small-scale \red{(resp. $k>k_ν$) and large-scale (resp. $k<k_ν$)} motions are convex, showing the multifractality. A lognormal formula was put forward to characterize the multifractal intensity. The measured intermittency parameters are $μ_S=0.26$ and $μ_L=0.17$ respectively for the small- and large-scale motions. It implies that the former cascade is more intermittent than the latter one, which is also confirmed by the corresponding singularity spectrum $f(α)$ vs $α$. Comparison with the conventional two-dimensional Ekman-Navier-Stokes equation, a continuum model indicates that the origin of the multifractality could be a result of some additional nonlinear interaction terms, which deservers a more careful investigation.

physics.flu-dyn↗

arXiv2013

Lagrangian single particle turbulent statistics through the Hilbert-Huang Transform

The Hilbert-Huang transform is applied to analyze single particle Lagrangian velocity data from numerical simulations of hydrodynamic turbulence. The velocity trajectory is described in terms of a set of intrinsic mode functions, C_{i}(t), and of their instantaneous frequency, ω_{i}(t). On the basis of this decomposition we define the ω-conditioned statistical moments of the C_{i} modes, named q-order Hilbert Spectra (HS). We show that such new quantities have enhanced scaling properties as compared to traditional Fourier transform- or correlation-based (Structure Functions) statistical indicators, thus providing better insights into the turbulent energy transfer process. We present a clear empirical evidence that the energy-like quantity, i.e. the second-order HS, displays a linear scaling in time in the inertial range, as expected from dimensional analysis and never observed before. We also measure high order moment scaling exponents in a direct way, without resorting the Extended Self Similarity (ESS) procedure. This leads to a new estimate of the Lagrangian structure functions exponents which are consistent with the multifractal prediction in the Lagrangian frame as proposed in [Biferale et al., Phys. Rev. Lett. vol. 93, 064502 (2004)].

physics.flu-dyn↗