Showing papers in "International Journal of Modern Physics C in 2012"

Modeling of particle size segregation: calibration using the discrete particle method

Abstract: Over the last 25 years a lot of work has been undertaken on constructing continuum models for segregation of particles of different sizes. We focus on one model that is designed to predict segregation and remixing of two differently sized particle species. This model contains two dimensionless parameters, which in general depend on both the flow and particle properties. One of the weaknesses of the model is that these dependencies are not predicted; these have to be determined by either experiments or simulations. We present steady-state simulations using the discrete particle method (DPM) for bi-disperse systems with different size ratios. The aim is to determine one parameter in the continuum model, i.e., the segregation Peclet number (ratio of the segregation velocity to diffusion) as a function of the particle size ratio. Reasonable agreement is found; but, also measurable discrepancies are reported; mainly, in the simulations a thick pure phase of large particles is formed at the top of the flow. In the DPM contact model, tangential dissipation was required to obtain strong segregation and steady states. Additionally, it was found that the Peclet number increases linearly with the size ratio for low values, but saturates to a value of approximately 7.35.

Statistical Properties and Multifractal Behaviors of Market Returns by Ising Dynamic Systems

Abstract: An interacting-agent model of speculative activity explaining price formation in financial markets is considered in the present paper, which based on the stochastic Ising model and the mean field theory. The model describes the interaction strength among the agents as well as an external field, and the corresponding random logarithmic price return process is investigated. According to the empirical research of the model, the time series formed by this Ising model exhibits the bursting typical of volatility clustering, the fat-tail phenomenon, the power-law distribution tails and the long-time memory. The statistical properties of the returns of Hushen 300 Index, Shanghai Stock Exchange (SSE) Composite Index and Shenzhen Stock Exchange (SZSE) Component Index are also studied for comparison between the real time series and the simulated ones. Further, the multifractal detrended fluctuation analysis is applied to investigate the time series returns simulated by Ising model have the distribution multifractality as well as the correlation multifractality.

Prediction of effective permeability in porous media based on spontaneous imbibition effect

Abstract: Permeability is an important parameter for characterizing the transport properties (e.g. heat and mass transfer) of porous media. It is one of the crucial issues that the permeability of porous media is exactly and quickly decided in many fields such as reservoir engineering, groundwater engineering and composite material modeling. Spontaneous imbibition is a fundamental and ubiquitous natural phenomenon extensively existing in a variety of processes. In this paper, the relationships between the height and weight of imbibition versus the time are derived based on Darcy's law, and a simple method for predicting effective permeability of porous media using spontaneous imbibition effect is proposed, including expressions for permeabilities of artificial and natural porous media. The validity of the proposed models is analysed and tested by experimental data.

Towards a statistical physics of human mobility

Abstract: In this paper, we extend some ideas of statistical physics to describe the properties of human mobility. From a physical point of view, we consider the statistical empirical laws of private cars mobility, taking advantage of a GPS database which contains a sampling of the individual trajectories of 2% of the whole vehicle population in an Italian region. Our aim is to discover possible "universal laws" that can be related to the dynamical cognitive features of individuals. Analyzing the empirical trip length distribution we study if the travel time can be used as universal cost function in a mesoscopic model of mobility. We discuss the implications of the elapsed times distribution between successive trips that shows an underlying Benford's law, and we study the rank distribution of the average visitation frequency to understand how people organize their daily agenda. We also propose simple stochastic models to suggest possible explanations of the empirical observations and we compare our results with analogous results on statistical properties of human mobility presented in the literature.

Age-related preferential selection can promote cooperation in the prisoner's dilemma game

Abstract: In this paper, we introduce an age-related preferential selection mechanism into the prisoner's dilemma game. Under this mechanism, players can select a source of strategy imitation from their neighbors in a biased way proportional to their ages. Tuned by a selection parameter α, the impact of aging on the evolution of cooperation can be very different. The numerical results show that the cooperation will be effectively promoted by adjusting the value of α. By examining the evolution process and spatial patterns for different values of α, it is found that larger α will effectively promote the formation of large scale of cooperator clusters. In addition, the impact of noise K on the spreading process of cooperation strategy is studied. We find that small K can make cooperation monotonously increase with α, while large K guarantees the optimal existence of cooperation for an intermediate α.

Improved efficient routing strategy on scale-free networks

Abstract: Since the betweenness of nodes in complex networks can theoretically represent the traffic load of nodes under the currently used routing strategy, we propose an improved efficient (IE) routing strategy to enhance to the network traffic capacity based on the betweenness centrality. Any node with the highest betweenness is susceptible to traffic congestion. An efficient way to improve the network traffic capacity is to redistribute the heavy traffic load from these central nodes to non-central nodes, so in this paper, we firstly give a path cost function by considering the sum of node betweenness with a tunable parameter β along the actual path. Then, by minimizing the path cost, our IE routing strategy achieved obvious improvement on the network transport efficiency. Simulations on scale-free Barabasi–Albert (BA) networks confirmed the effectiveness of our strategy, when compared with the efficient routing (ER) and the shortest path (SP) routing.

Complex network analysis of literary and scientific texts

Abstract: We present results from our quantitative study of statistical and network properties of literary and scientific texts written in two languages: English and Polish. We show that Polish texts are described by the Zipf law with the scaling exponent smaller than the one for the English language. We also show that the scientific texts are typically characterized by the rank-frequency plots with relatively short range of power-law behavior as compared to the literary texts. We then transform the texts into their word-adjacency network representations and find another difference between the languages. For the majority of the literary texts in both languages, the corresponding networks revealed the scale-free structure, while this was not always the case for the scientific texts. However, all the network representations of texts were hierarchical. We do not observe any qualitative and quantitative difference between the languages. However, if we look at other network statistics like the clustering coefficient and the average shortest path length, the English texts occur to possess more clustered structure than do the Polish ones. This result was attributed to differences in grammar of both languages, which was also indicated in the Zipf plots. All the texts, however, show network structure that differs from any of the Watts–Strogatz, the Barabasi–Albert, and the Erdos–Renyi architectures.

A comprehensive dft study of zinc oxide in different phases

Abstract: A density functional study for structural and electronic properties of Zinc Oxide (ZnO), in wurtzite, rock salt and zinc-blende phases has been performed using full potential-linearized augmented plane wave/linearized augmented plane wave plus local ideal orbital (FP-LAPW/L(APW+lo) approach as realized in WIEN2k code. To approximate exchange correlation energy and corresponding potential, a special GGA parameterized by Wu–Cohen has been implemented. Our results of lattice constants, bulk moduli as well as for internal parameter with GGA-WC are found to be more reliable. This study reveals that value of internal parameter decreases with increasing volume whereas computed electronic band structure confirms the direct band gap behavior of ZnO in B4 and B3 phases while indirect band gap behavior in B1 phase. Moreover, two fold degeneracy at the maxima of valence band for B4 and B1 phases whereas three fold for B3 is observed. A detailed comparison with experimental and other first principles studies is also made.

Mrt rectangular lattice boltzmann method

Abstract: A multiple-relaxation-time (MRT) collision operator is introduced into the author's rectangular lattice Boltzmann method for simulating fluid flows. The model retains both the advantages and the standard procedure of using a constant transformation matrix in the conventional MRT scheme on a square lattice, leading to easy implementation in the algorithm. This allows flow problems characterized by dominant feature in one direction to be solved more efficiently. Two numerical tests have been carried out and shown that the proposed model is able to capture complex flow characteristics and generate an accurate solution if an appropriate lattice ratio is used. The model is found to be more stable compared to the original rectangular lattice Boltzmann method using the single relaxation time.

A novel lattice traffic flow model and its solitary density waves

Abstract: A novel lattice traffic flow model with a slope effect is proposed Neutral stability condition is obtained by the use of the linear stability theory The standard KdV equation is derived in the meta-stable region and soliton solution is obtained near the neutral stability line The solitary waves are reproduced through the numerical simulations Results show that the solitary density wave appears in upward form when the average density is less than critical density, otherwise it exhibits downward form

Practical synchronization of nonautonomous systems with uncertain parameter mismatch via a single state feedback control

Abstract: Robust practical synchronization of general second-order nonautonomous systems with uncertain parameter mismatch is investigated by using a single state feedback control. Some simple general algebraic criteria are derived based on practical stability theory of nonautonomous dynamical system. A distinctive feature of this work is that the parameter mismatch not only exists in system parameters, but also in the external excitation ones. More reasonably, the values of parameter mismatch can be uncertain. Besides, a single state feedback control including an approximate differentiation filter only needs to know information about one state, which provides an advantage over the use of full-state model-based observers. It is shown that the approaches developed here further extend the ideas and techniques presented in recent literature. As a direct application of the new theoretical results, the obtained results are applied to a typical horizontal platform system and the representative forced Duffing–Van der Pol oscillator. Subsequently, numerical simulations demonstrate the effectiveness of the criteria and the robustness of the control technique.

An efficient bandwidth allocation strategy for scale-free networks

Abstract: Traffic capacity is critical for various networks and strongly depends on the distribution of link's bandwidth resources. In this paper, we propose a betweenness-based bandwidth allocation strategy in which the bandwidth of each link lij is allocated proportionally to the product (1 + Bi)α(1 + Bj)α, where α is a tunable parameter, and Bi and Bj are the betweenness of node i and node j, respectively. The optimal value of α is achieved by extensive simulations and slightly increases with the network size. Our new bandwidth allocation strategy achieves the highest traffic capacity when compared with the average bandwidth allocation strategy and the previously proposed degree-based bandwidth allocation strategy. Our work will be beneficial for network service providers to improve the traffic capacity by efficiently allocating or reallocating the overall finite link's bandwidth resources of networks such as the Internet, urban transport networks and airway networks.

Using variable speed limits to eliminate wide moving jams: a study based on three-phase traffic theory

Abstract: One frequently observed congested traffic flow pattern is wide moving jam (WMJ), in which the average vehicle speed is very low and the density is very high. In some recent studies, variable speed limits (VSL) were proposed as effective measures to eliminate or abate the influence of jam waves. However, in most of these studies, the stochastic features of driving behaviors and the resulting uncertainty of traffic flow dynamics were not fully considered. In this paper, we use cellular automaton (CA) model-based simulations to test the performances of different VSL control strategies and apply the three-phase traffic theory to further analyze the obtained results. Based on the simulation results, we got two novel findings. Firstly, we observed seven, instead of the previously assumed six, states of traffic flow in the evolution process of WMJ, when VSL were applied. Secondly and more importantly, we found that inappropriate speed limit may induce new WMJ and exaggerate congestions in two ways: one way corresponds to an F → J transition and the other corresponds to an F → S → J transition. Based on these findings, the appropriate lower bound of VSL was finally discussed in this paper.

A design of pseudo-random bit generator based on single chaotic system

Abstract: Pseudo-random bit sequence have a wide range of applications in the field of cryptography and communications. For the good chaotic dynamical properties of chaotic systems sequence such as randomness and initial sensitivity, chaotic systems have a strong advantage in generating the pseudo-random bit sequence. However, in practical use, the dynamical properties of chaotic systems will be degraded because of the limited calculation accuracy and it even could cause a variety of security issues. To improve the security, in full analyses of the pseudo-random bit generator proposed in our former paper, we point out some problems in our former design and redesign a better pseudo-random bit generator base on it. At the same time, we make some relevant theoretical and experimental analyses on it. The experiments show that the design proposed in this paper has good statistical properties and security features.

Neural network aided evaluation of landslide susceptibility in southern italy

Abstract: Landslide hazard mapping is often performed through the identification and analysis of hillslope instability factors. In heuristic approaches, these factors are rated by the attribution of scores based on the assumed role played by each of them in controlling the development of a sliding process. The objective of this research is to forecast landslide susceptibility through the application of Artificial Neural Networks. In particular, given the availability of past events data, we mainly focused on the Calabria region (Italy). Vectors of eight hillslope factors (features) were considered for each considered event in this area (lithology, permeability, slope angle, vegetation cover in terms of type and density, land use, yearly rainfall and yearly temperature range). We collected 106 vectors and each one was labeled with its landslide susceptibility, which is assumed to be the output variable. Subsequently a set of these labeled vectors (examples) was used to train an artificial neural network belonging to the category of Multi-Layer Perceptron (MLP) to evaluate landslide susceptibility. Then the neural network predictions were verified on the vectors not used in the training (validation set), i.e. in previously unseen locations. The comparison between the expected output and the artificial neural network output showed satisfactory results, reporting a prediction discrepancy of less than 4.3%. This is an encouraging preliminary approach towards a systematic introduction of artificial neural network in landslide hazard assessment and mapping in the considered area.

Optimized scale-free networks against cascading failures

Abstract: According to the dynamical characteristics of the local redistribution of the load on a removal node, by the reconnection of the neighboring edge of the most vulnerable node, we propose an effective method to improve the network robustness against cascading failures. Under two constraints, i.e. keeping the degree of each node unchanged and fixing the total protective cost of a network, we investigate the efficiency of the swap method on scale-free networks and analyze the correlation between the optimized network and the Pearson correlation coefficient. We numerically show that effective swapping of the small part of connections can dramatically improve the network robust level against cascading failures and find that the optimized networks obtained by the swap method exhibit an extremely disassortative degree–degree correlation, that is, the disassortativity decreases the robustness of the optimized network against cascading failures. While the extent of the disassortative mixing is decided by the parameters in the cascading model. In addition, we also compare the average path length and the diameter of the optimized and the original networks.

Tax Evasion Dynamics and Zaklan Model on Opinion-Dependent Network

Abstract: Within the context of agent-based Monte-Carlo simulations, we study the problem of the fluctuations of tax evasion in a community of honest citizens and tax evaders by using the version of the nonequilibrium Zaklan model proposed by Lima (2010). The studied evolutionary dynamics of tax evasion are driven by a non-equilibrium majority-vote model of M. J. Oliveira, with the objective to attempt to control the fluctuations of the tax evasion in the observed community in which citizens are localized on the nodes of the Stauffer–Hohnisch–Pittnauer networks.

Methods to compute pressure and wall tension in fluids containing hard particles

Abstract: Colloidal systems are often modeled as fluids of hard particles (possibly with an additional soft attraction, e.g. caused by polymers also contained in the suspension). In simulations of such systems, the virial theorem cannot be straightforwardly applied to obtain the components of the pressure tensor. In systems confined by walls, it is hence also not straightforward to extract the excess energy due to the wall (the “wall tension”) from the pressure tensor anisotropy. A comparative evaluation of several methods to circumvent this problem is presented, using as examples fluids of hard spheres and the Asakura–Oosawa model of colloid-polymer mixtures with a size ratio q = 0.15 (for which the effect of the polymers can be integrated out to yield an effective attractive potential between the colloids). Factors limiting the accuracy of the various methods are carefully discussed, and controlling these factors very good mutual agreement between the various methods is found.

Lyapunov exponents and modulated phases of an ising model on cayley tree of arbitrary order

Abstract: Different types of the lattice spin systems with the competing interactions have rich and interesting phase diagrams. In this study a system with competing nearest-neighbor interaction J1, prolonged next-nearest-neighbor interaction Jp and ternary prolonged interaction Jtp is considered on a Cayley tree of arbitrary order k. To perform this study, an iterative scheme is developed for the corresponding Hamiltonian model. At finite temperatures several interesting properties are presented for typical values of α = T/J1, β = −Jp/J1 and γ = -Jtp/J1. This study recovers as particular cases, previous work by Vannimenus1 with γ = 0 for k = 2 and Ganikhodjaev et al.2 in the presence J1, Jp, Jtp with k = 2. The variation of the wavevector q with temperature in the modulated phase and the Lyapunov exponent associated with the trajectory of our iterative system are studied in detail.

Finding community structure in spatial maritime shipping networks

Abstract: This study explores the community structure in spatial maritime shipping networks. As compared with air transportation networks and urban road networks, ports in spatial maritime shipping networks have smaller connections due to the physical confinement. A new divisive algorithm is proposed for detecting community structure in spatial maritime shipping networks. At each iteration for modularity optimization, the length of each edge is successively updated, instead of edge removal used in the conventional divisive method. Finally, numerical experiments based on the global maritime shipping network are carried out to account for the properties of community structure in spatial maritime shipping networks.

A review of high performance computing foundations for scientists

Abstract: The increase of existing computational capabilities has made simulation emerge as a third discipline of Science, lying midway between experimental and purely theoretical branches [G. Makov, C. Gattinoni and A. D. Vita, Model. Simul. Mater. Sci. Eng.17, 084008 (2009); C. J. Cramer, Essentials of Computational Chemistry: Theories and Models, 2nd edn. (John Wiley & Sons, Chichester, 2002)]. Simulation enables the evaluation of quantities which otherwise would not be accessible, helps to improve experiments and provides new insights on systems which are analyzed [T. C. Germann, K. Kadau and S. Swaminarayan, Concurrency Comput. Pract. Exp.21, 2143 (2009); M. A. L. Marques, X. Lopez, D. Varsano, A. Castro and A. Rubio, Phys. Rev. Lett.90, 258101 (2003); D. E. Shaw, P. Maragakis, K. Lindorff-Larsen, S. Piana, R. O. Dror, M. P. Eastwood, J. A. Bank, J. M. Jumper, J. K. Salmon, Y. Shan and W. Wriggers, Science330, 341 (2010); D. Marx, Chem. Phys. Chem.7, 1848 (2006)]. Knowing the fundamentals of computation can be very useful for scientists, for it can help them to improve the performance of their theoretical models and simulations. This review includes some technical essentials that can be useful to this end, and it is devised as a complement for researchers whose education is focused on scientific issues and not on technological respects. In this document, we attempt to discuss the fundamentals of high performance computing (HPC) [G. Hager and G. Wellein, Introduction to High Performance Computing for Scientists and Engineers, 1st edn. (CRC Press, Taylor & Francis Group, 2011)] in a way which is easy to understand without much previous background. We sketch the way standard computers and supercomputers work, as well as discuss distributed computing and discuss essential aspects to take into account when running scientific calculations in computers.

Matrix approach of an encryption system based on cellular automata and its numerical implementation

Abstract: The main components of an encryption system based on rule 90 cellular automata, i.e., two indexed families of permutations and a pseudo-random bit generator are implemented in a very flexible way through a convenient matrix approach.

A runge–kutta–fehlberg code for the complex plane: comparing with similar codes by applying to polytropic models

Abstract: In this paper, we modify the Runge–Kutta–Fehlberg code of fourth and fifth order with the purpose of solving initial value problems established on ordinary differential equations involving complex-valued functions of one complex variable, which are allowed to have high complexity in their definition, when integration along prescribed complex paths is required. Such initial value problems arise in certain astrophysical issues, like the polytropic models, applied to polytropic stars, and the general-relativistic polytropic models, applied to neutron stars. Comparison with similar codes is made by applying to these models.

Characterizing english poetic style using complex networks

Abstract: Complex networks have been proven useful in characterizing written texts. Here, we use networks to probe if there exist a similarity within, and difference across, era as reflected within the poem's structure. In literary history, boundary lines are set to distinguish the change in writing styles through time. We obtain the network parameters and motif frequencies of 845 poems published from 1522 to 1931 and relate this to the writing of the Elizabethan, 17th Century, Augustan, Romantic and Victorian eras. Analysis of the different network parameters shows a significant difference of the Augustan era (1667–1780) with the rest. The network parameters and the convex hull and centroids of the motif frequencies reflect the adjectival sequence pattern of the poems of the Augustan era.

An improved cluster dynamics model for hydrogen retention in tungsten

Abstract: An improved cluster dynamics model has been developed for studying the behaviors of hydrogen retention in tungsten under hydrogen ions irradiation. In addition to different types of objects, adopting up-to-date parameters and complex reaction processes, we newly introduce ion-induced and natural defects into our model. This improved model programmed in IRadMat2 could describe very well the depth distributions and the amounts of hydrogen retained in tungsten under different radiation conditions. The calculated results agree with the experimental ones much better than the previous model, especially for the depth-distribution of D retained in W, which imply that this model is applicable to the evolution of defects especially for low energy high flux ions irradiated on plasma-facing materials.

REVERSIBLE CELLULAR AUTOMATA WITH PENTA-CYCLIC RULE AND ECCs

Abstract: The reversibility problem for linear cellular automata with null boundary defined by a rule matrix in the form of a pentadiagonal matrix was studied over the binary field ℤ2 by Martin del Rey et al. [Appl. Math. Comput.217, 8360 (2011)]. Recently, the reversibility problem of 1D Cellular automata with periodic boundary has been extended to ternary fields and further to finite primitive fields ℤp by Cinkir et al. [J. Stat. Phys.143, 807 (2011)]. In this work, we restudy some of the work done in Cinkir et al. [J. Stat. Phys.143, 807 (2011)] by using a different approach which is based on the theory of error correcting codes. While we reestablish some of the theorems already presented in Cinkir et al. [J. Stat. Phys.143, 807 (2011)], we further extend the results to more general cases. Also, a conjecture that is left open in Cinkir et al. [J. Stat. Phys.143, 807 (2011)] is also solved here. We conclude by presenting an application to Error Correcting Codes (ECCs) where reversibility of cellular automata is crucial.

Complex network for a crisis contagion on an interbank system

Abstract: The main focus of this research is the contagion of a financial crisis on an interbank debt network. In order to simulate the crisis propagation a weighted community complex network based on growth strategy has been created. The contagion is described by a new way of disease propagation perspective based on the concept of a financial virus. The model reproduces the existence of TBTF banks and shows the impact that an initial TBTF bank crash produces in the interbank network depending on the magnitude of the initial crash and on the resistance that the network offers against the contagion propagation.

On 1d Reversible Cellular Automata with Reflective Boundary Over the Prime Field of Order p

Abstract: In this paper, we study one dimensional finite linear cellular automata with reflective boundary condition by using matrix algebra built on the field ℤp. We present an algorithm for determining the reversibility of this family of cellular automata. We also answer the reversibility question for some special subfamilies. Finally, we present some examples of this family of cellular automata under the reflective boundary condition.

Klein Tunneling in the Presence of Random Impurities

Abstract: In this paper, we study Klein tunneling in random media. To this purpose, we simulate the propagation of a relativistic Gaussian wave packet through a disordered medium with randomly distributed potential barriers (impurities). The simulations, based on a relativistic quantum lattice Boltzmann (QLB) method, permit to compute the transmission coefficient across the sample, thereby providing an estimate for the conductivity (or permeability) as a function of impurity concentration and strength of the potentials. It is found that the conductivity loss due to impurities is significantly higher for wave packets of massive particles, as compared to massless ones. A general expression for the loss of conductivity as a function of the impurity percentage is presented and successfully compared with the Kozeny–Carman law for disordered media in classical fluid-dynamics.

Visibility graphs from experimental three-phase flow for characterizing dynamic flow behavior

Abstract: We systematically carried out oil–gas–water three-phase flow experiments for measuring the time series of flow signals. We first investigate flow pattern behaviors from the energy and frequency point of view and find that different flow patterns exhibit different flow behaviors. In order to quantitatively characterize dynamic behaviors underlying different oil–gas–water three-phase flow patterns, we infer and analyze visibility graphs (complex networks) from signals measured under different flow conditions. The results indicate that the combination parameters of network degree are sensitive to the transition among different flow patterns, which can be used to distinguish different flow patterns and quantitatively characterize nonlinear dynamics of the three-phase flow. In this regard, visibility graph can be a useful tool for characterizing the nonlinear dynamic behaviors underlying different oil–gas–water three-phase flow patterns.