Numerical simulation of a bubble rising in shear-thinning fluids

The motion of a single bubble rising freely in quiescent non-Newtonian viscous fluids was investigated experimentally and computationally. The non-Newtonian effects in the flow of viscous inelastic fluids are modeled by the Carreau theological model. An improved level set approach for computing the incompressible two-phase flow with deformable free interface is used. The control volume formulation with the SIMPLEC algorithm incorporated is used to solve the governing equations on a staggered Eulerian grid. The simulation results demonstrate that the algorithm is robust for shear-thinning liquids with large density (rho(1)/rho(g) up to 10(3)) and high viscosity (eta(1)/eta(g) up to 10(4)). The comparison of the experimental measurements of terminal bubble shape and velocity with the computational results is satisfactory. It is shown that the local change in viscosity around a bubble greatly depends on the bubble shape and the zero-shear viscosity of non-Newtonian shear-thinning liquids. The shear-rate distribution and velocity fields are used to elucidate the formation of a region of large viscosity at the rear of a bubble as a result of the rather stagnant flow behind the bubble. The numerical results provide the basis for further investigations, such as the numerical simulation of viscoelastic fluids. (C) 2010 Elsevier B.V. All rights reserved.

Range-based attacks on links in random scale-free networks

Range and load play key roles in the problem of attacks on links in random scale-free (RSF) networks. In this paper we obtain the approximate relation between range and load in RSF networks by the generating function theory, and then give an estimation about the impact of attacks on the efficiency of the network. The results show that short-range attacks are more destructive for RSF networks, and are confirmed numerically.

Knotlike chi disclinations in the cholesteric liquid crystals

We investigate the topological properties of N(N >= 1) disclination lines in cholesteric liquid crystals. The topological structure of N disclination lines is obtained with the Hopf index and Brouwer degree. Furthermore, the knotted x disclination loops is proposed with the Hopf invariant. And we consider the stability of such configuration based on the higher order interaction. At last, the evolution of the disclinations is discussed.

Efficiency Dynamics on Two Coupled Small-World Networks

We investigate the effect of clusters in complex networks on efficiency dynamics by studying a simple efficiency model in two coupled small-world networks. It is shown that the critical network randomness corresponding to transition from a stagnant phase to a growing one decreases to zero as the connection strength of clusters increases. It is also shown for fixed randomness that the state of clusters transits from a stagnant phase to a growing one as the connection strength of clusters increases. This work can be useful for understanding the critical transition appearing in many dynamic processes on the cluster networks.

EFFICIENCY DYNAMICS ON SCALE-FREE NETWORKS WITH COMMUNITIES

The simple efficiency model is developed on scale-free networks with communities to study the effect of the communities in complex networks on efficiency dynamics. For some parameters, we found that the state of system will transit from a stagnant phase to a growing phase as the strength of community decreases.

Promotion of cooperation in the form C0C1D classified by 'degree grads' in a scale-free network

In this paper, we revisit the issue of the public goods game (PGG) on a heterogeneous graph. By introducing a new effective topology parameter, 'degree grads' phi, we clearly classify the agents into three kinds, namely, C-0, C-1, and D. The mechanism for the heterogeneous topology promoting cooperation is discussed in detail from the perspective of C0C1D, which reflects the fact that the unreasoning imitation behaviour of C-1 agents, who are 'cheated' by the well-paid C-0 agents inhabiting special positions, stabilizes the formation of the cooperation community. The analytical and simulation results for certain parameters are found to coincide well with each other. The C0C1D case provides a picture of the actual behaviours in real society and thus is potentially of interest.

The effect of human rhythm on packet delivery

In communication networks such as the Internet, the relationship between packet generation rate and time is similar to a rectangle wavefunction due to the rhythm of humans. Thus, we investigate the traffic dynamics on a network with a rectangle wavepacket generation rate. It is found that the critical delivering capacity parameter beta(c) (which separates the congested phase and the free phase) decreases significantly with the duty cycle r of the rectangle wave for package generation. And, in the congested phase, more collective generation of packets (smaller r) is helpful for decreasing the packet aggregation rate. Moreover, it is found that the congested phase can be divided into two regions, i.e., region1 and region2, where the distributions of queue lengths are nonlinear and linear, respectively. Also, the linear expression for the distribution of queue lengths in region2 is obtained analytically. Our work reveals an obvious effect of the rectangle wave on the traffic dynamics and the queue length distribution in the system, which is of essential interest and may provide insights into the designing of work-rest schedules and routing strategies.

Quantifying the kinetic paths of flexible biomolecular recognition

Biomolecular recognition often involves large conformational changes, sometimes even local unfolding. The identification of kinetic pathways has become a central issue in understanding the nature of binding. A new approach is proposed here to study the dynamics of this binding-folding process through the establishment of a path-integral framework on the underlying energy landscape. The dominant kinetic paths of binding and folding can be determined and quantified. The significant coupling between the binding and folding of biomolecules often exists in many important cellular processes. In this case, the corresponding kinetic paths of binding are shown to be intimately correlated with those of folding and the dynamics becomes quite cooperative. This implies that binding and folding happen concurrently. When the coupling between binding and folding is weak (strong), the kinetic process usually starts with significant folding (binding) first, with the binding (folding) later proceeding to the end. The kinetic rate can be obtained through the contributions from the dominant paths. The rate is shown to have a bell-shaped dependence on temperature in the concentration-saturated regime consistent with experiment. The changes of the kinetics that occur upon changing the parameters of the underlying binding-folding energy landscape are studied.

The role of Li-O bonds in calculations of nonlinear optical coefficients of LiXO3-type complex crystals

The second-order nonlinear optical (NLO) tenser coefficients of LiXO3 (X = I; Nb or Ta) type complex crystals have been calculated using the chemical bond theory of complex crystals. Contributions of each type of bond to the total second-order NLO coefficient d(ij) and the linear susceptibility X are quantitatively determined. All tensor values thus calculated are in good agreement with experimental data. The Li-O bonds are found to be an important group in the contributions to the total NLO tenser coefficient, especially for those in LiNbO3 and LiTaO3. The importance of Li-O bonds depends on the environment of Li atom in these crystals.

笼形水簇和溶解甲烷之间平均力势能的约束型分子动力学计算及其在天然气水合物成核研究中的意义

That the dodecahedral water cluster (DWC) can adsorb dissolved methane molecules, an important phenomenon related to the hydrate nucleation study, has been observed through molecular dynamics simulations, but it has not been explained satisfactorily [Guang-Jun Guo; Yi-Gang Zhang; Hua Liu. J. Phys. Chem. C, 2007, 111, 2595]. In order to explain this phenomenon by using the potential of mean force (PMF) between the DWC and the dissolved methane, we perform several series of constrained molecular dynamics simulations in the methane-water system. The distance between the center of DWC and the methane molecule is constrained from 5 Å to 18 Å by adding 0.2 Å every time. For each fixed distance, we perform 20 independent simulations to improve the statistical precision. We first get the constraint force between the DWC and the dissolved methane in each simulation and then calculate the PMF by integrating these forces. Subsequently, the radial distribution function (RDF) is obtained from the PMF through an equation of statistical mechanics. The results show that the RDF has a sharp peak at about 6.2 Å, successfully explaining why the DWC adsorbs dissolved methane molecules. The preferential binding coefficient is a positive value (=2.05±0.5), indicates that the DWC tends to adsorb dissolved methane rather than water molecules in methane aqueous solutions. The curve of PMF for the DWC encaging a methane almost coincides that for the empty DWC, meaning that it is the DWC rather than the encaged methane who could adsorb dissolved methane molecules. By comparing the curves of PMF for different directions of the DWC relative to the dissolved methane, we find that it is the cage face rather than the cage edge or vertex that plays an essential role when the DWC adsorbing dissolved methane. This research sheds light on the driving force for the methane adsorption, and it is helpful in understanding the nucleation process of methane hydrate.

HHT在电磁信号处理中的应用

In modem signal Processing，non－linear，non－Gaussian and non－stable signals are usually the analyzed and Processed objects，especially non－stable signals. The convention always to analyze and Process non－stable signals are： short time Fourier transform，Wigner－Ville distribution，wavelet Transform and so on. But the above three algorithms are all based on Fourier Transform，so they all have the shortcoming of Fourier Analysis and cannot get rid of the localization of it. Hilbert－Huang Transform is a new non－stable signal processing technology，proposed by N. E. Huang in 1998. It is composed of Empirical Mode Decomposition (referred to as EMD) and Hilbert Spectral Analysis (referred to as HSA). After EMD Processing，any non－stable signal will be decomposed to a series of data sequences with different scales. Each sequence is called an Intrinsic Mode Function (referred to as IMF). And then the energy distribution plots of the original non－stable signal can be found by summing all the Hilbert spectrums of each IMF. In essence，this algorithm makes the non－stable signals become stable and decomposes the fluctuations and tendencies of different scales by degrees and at last describes the frequency components with instantaneous frequency and energy instead of the total frequency and energy in Fourier Spectral Analysis. In this case，the shortcoming of using many fake harmonic waves to describe non－linear and non－stable signals in Fourier Transform can be avoided. This Paper researches in the following parts： Firstly，This paper introduce the history and development of HHT，subsequently the characters and main issues of HHT. This paper briefly introduced the basic realization principles and algorithms of Hilbert－Huang transformation and confirms its validity by simulations. Secondly, This paper discuss on some shortcoming of HHT. By using FFT interpolation, we solve the problem of IMF instability and instantaneous frequency undulate which are caused by the insufficiency of sampling rate. As to the bound effect caused by the limitation of envelop algorithm of HHT, we use the wave characteristic matching method, and have good result. Thirdly, This paper do some deeply research on the application of HHT in electromagnetism signals processing. Based on the analysis of actual data examples, we discussed its application in electromagnetism signals processing and noise suppression. Using empirical mode decomposition method and multi-scale filter characteristics can effectively analyze the noise distribution of electromagnetism signal and suppress interference processing and information interpretability. It has been founded that selecting electromagnetism signal sessions using Hilbert time-frequency energy spectrum is helpful to improve signal quality and enhance the quality of data.

f-x-y域去除随机噪音方法研究

The seismic survey is the most effective prospecting geophysical method during exploration and development of oil/gas. The structure and the lithology of the geological body become increasingly complex now. So it must assure that the seismic section own upper resolution if we need accurately describe the targets. High signal/noise ratio is the precondition of high-resolution. For the sake of improving signal/noise ratio, we put forward four methods for eliminating random noise on the basis of detailed analysis of the technique for noise elimination using prediction filtering in f-x-y domain. The four methods are put forward for settling different problems, which are in the technique for noise elimination using prediction filtering in f-x-y domain. For weak noise and large filters, the response of the noise to the filter is little. For strong noise and short filters, the response of the noise to the filter is important. For the response of the noise, the predicting operators are inaccurate. The inaccurate operators result in incorrect results. So we put forward the method using prediction filtering by inversion in f-x-y domain. The method makes the assumption that the seismic signal comprises predictable proportion and unpredictable proportion. The transcendental information about predicting operator is introduced in the function. The method eliminates the response of the noise to filtering operator, and assures that the filtering operators are accurate. The filtering results are effectively improved by the method. When the dip of the stratum is very complex, we generally divide the data into rectangular patches in order to obtain the predicting operators using prediction filtering in f-x-y domain. These patches usually need to have significant overlap in order to get a good result. The overlap causes that the data is repeatedly used. It effectively increases the size of the data. The computational cost increases with the size of the data. The computational efficiency is depressed. The predicting operators, which are obtained by general prediction filtering in f-x-y domain, can not describe the change of the dip when the dip of the stratum is very complex. It causes that the filtering results are aliased. And each patch is an independent problem. In order to settle these problems, we put forward the method for eliminating noise using space varying prediction filtering in f-x-y domain. The predicting operators accordingly change with space varying in this method. Therefore it eliminates the false event in the result. The transcendental information about predicting operator is introduced into the function. To obtain the predicting operators of each patch is no longer independent problem, but related problem. Thus it avoids that the data is repeatedly used, and improves computational efficiency. The random noise that is eliminated by prediction filtering in f-x-y domain is Gaussian noise. The general method can't effectively eliminate non-Gaussian noise. The prediction filtering method using lp norm (especially p=l) can effectively eliminate non-Gaussian noise in f-x-y domain. The method is described in this paper. Considering the dip of stratum can be accurately obtained, we put forward the method for eliminating noise using prediction filtering under the restriction of the dip in f-x-y domain. The method can effectively increase computational efficiency and improve the result. Through calculating in the theoretic model and applying it to the field data, it is proved that the four methods in this paper can effectively solve these different problems in the general method. Their practicability is very better. And the effect is very obvious.

Mean Field Theory for Sigmoid Belief Networks

We develop a mean field theory for sigmoid belief networks based on ideas from statistical mechanics. Our mean field theory provides a tractable approximation to the true probability distribution in these networks; it also yields a lower bound on the likelihood of evidence. We demonstrate the utility of this framework on a benchmark problem in statistical pattern recognition -- the classification of handwritten digits.

Generalized Low-Rank Approximations

We study the frequent problem of approximating a target matrix with a matrix of lower rank. We provide a simple and efficient (EM) algorithm for solving {\\em weighted} low rank approximation problems, which, unlike simple matrix factorization problems, do not admit a closed form solution in general. We analyze, in addition, the nature of locally optimal solutions that arise in this context, demonstrate the utility of accommodating the weights in reconstructing the underlying low rank representation, and extend the formulation to non-Gaussian noise models such as classification (collaborative filtering).

The mixing of bubbles in two-dimensional bidisperse foams under extensional shear

Cox, S.J. (2006) The mixing of bubbles in two-dimensional bidisperse foams under extensional shear. Journal of Non-Newtonian Fluid Mechanics . 137:39-45.