International Journal of Modern Physics C

Computational studies have been widely applied for the thermal evaluation of the nanomaterial thermal feature in different industrial and scientific issues. The squeezed flow and heat transfer features for Al₂O₃-water nanofluid among analogous plates are investigated using the GOHAM and its validity is verified by comparison with existing numerical results. Novel aspects of Brownian motion and thermal force were accounted in the simulation of nanomaterial flow within parallel plate. Analytical investigation has been done for diverse governing factors namely: the squeeze, chemical reaction factors and Eckert number. The obtained outcomes show that $|C_f|$ has direct relationship with absolute values of squeeze factor. Nu increases for large Eckert number and absolute values of squeeze number.

Community structure is a common characteristic of complex networks and community detection is an important methodology to reveal the structure of real-world networks. In recent years, many algorithms have been proposed to detect the high-quality communities in real-world networks. However, these algorithms have shortcomings of performing calculation on the whole network or defining objective function and the number of commonties in advance, which affects the performance and complexity of community detection algorithms. In this paper, a novel algorithm has been proposed to detect communities in networks by belonging intensity analysis of intermediate nodes, named BIAS, which is inspired from the interactive behavior in human communication networks. More specifically, intermediate nodes are middlemen between different groups in social networks. BIAS algorithm defines belonging intensity using local interactions and metrics between nodes, and the belonging intensity of intermediate node in different communities is analyzed to distinguish which community the intermediate node belongs to. The experiments of our algorithm with other state-of-the-art algorithms on synthetic networks and real-world networks have shown that BIAS algorithm has better accuracy and can significantly improve the quality of community detection without prior information.

The method introduced in this paper is based on the finite element method. As an application for this efficient numerical method, we employ it in solving the system of ordinary differential equations which describes the thin-film flow and heat transfer with the effect of thermal radiation, magnetic field and slip velocity. The effect of the parameters which govern the proposed problem is discussed. From this theoretical and numerical study, it is observed that the slip velocity parameter tends to decrease the fluid velocity, whereas both the magnetic parameter and the radiation parameter can enhance the temperature distribution.

Coarse-graining of complex networks is a hot topic in network science. Coarse-grained networks are required to preserve the topological information or dynamic properties of the original network. Some effective coarse-graining methods have been proposed, while an urgent problem is how to obtain coarse-grained network with optimal scale. In this paper, we propose an extraction algorithm (EA) for optimal coarse-grained networks. Numerical simulation for EA on four kinds of networks and performing Kuramoto model on optimal coarse-grained networks, we find our algorithm can effectively obtain the optimal coarse-grained network.

Because of interdependence between different network layers, interdependent networks are more fragile than single-layer networks, and large-scale iterative paralysis occurs easily. How to seek nodes whose removal can effectively dismantle networks has attracted great research attention. In this paper, a novel optimal dismantling strategy Maximum Entropy Centrality (EC) and overlapping betweenness (OB) based on residual theory (ECOB) is proposed. In the ECOB, the residual theory is used to detect the highest influence nodes according to the quality of the residual networks. In addition, to make sorting more accurate, EC and OB parameters are both considered in the node selection mechanism. Simulation shows that the ECOB strategy performs much better than existing methods both in artificial interdependent networks and real-world interdependent networks. This is thanks to the introduced ECOB node selection algorithm with proper parameter criterions.

This paper deals with numerical study of flow field in a channel bend in presence of a lateral intake using three-dimensional numerical model SSIIM2. The effects of bend on the structure of the flow around the intake are investigated and compared with the experimental data. The tests are carried out in a U-shaped channel bend with a lateral intake. The intake is located at the outer bank of an 180^∘ bend at position 115^∘ with 45^∘ diversion angle and the experimental data can be used to calibrate and validate numerical models. The results show that both the center-region and outer-bank cross-stream circulations are observed in the experiments while only the former is captured by the numerical model due to the limitations of the turbulence model. In the curved channel after the intake, both experimental and numerical results show another type of bi-cellular circulations in which clockwise center-region circulations and counterclockwise circulations near the inner bank and the free surface (inner-bank circulations) are captured. The study shows that the numerical model very satisfactorily predicts streamlines, velocity field and flow pattern in the channel and in vicinity of the intake. Investigation of flow pattern around lateral intake in channel bends shows that contrary to the case of flow diversion in straight channels, the width of the dividing stream surface near water surface level is greater than that of near bed level. Finally, the effects of position and diversion angle of the lateral intake, discharge ratio and upstream Froude number on the flow pattern are investigated.

The energy markets, as important parts of global financial markets, have been regarded as complex nonlinear systems. The researches on the return volatility of energy futures are of great significance for grasping the law of operations and measuring the risks of markets. This paper introduces two novel volatility statistics — volatility two-component range intensity (VTRI) and cumulative volatility two-component range intensity (CVTRI) into energy futures markets to investigate the volatility dynamics of eight important energy futures. These two statistics combine the volatility shortest passage time (or volatility duration) with the volatility maximum change intensity and the volatility cumulative change intensity. Then, some statistical properties including probability distribution and tail power-law distribution of VTRI series and CVTRI series for eight energy futures are studied by some statistical analyses methods. Moreover, various nonlinear analytical methods are used to explore some nonlinear behaviors including correlation behavior, similarity behavior and multifractal property of VTRI series and CVTRI series.

This theoretical work explores the effect of the magnetic field on the liquid thin film flow of a non-Newtonian Powell–Eyring fluid. The thermocapillarity phenomenon in association with the effect of slip velocity is studied. In our research, we cannot ignore the important role of the numerical shooting method which employed to get the solution for our problem. This method helped us to sketch both the dimensionless velocity and the dimensionless temperature for several parameters. Furthermore, the authentication on the correctness and effectiveness for our method is checked by performing a comparison between this problem in the absence of some parameters and the previously published work, which confirms the robustness for the shooting method. Finally, an overview of the effect of the emerging parameters on the velocity and temperature profiles as well as the local skin-friction coefficient and the local Nusselt number is done.

The essence of parameter estimation for fractional-order chaotic systems is a multi-dimensional parameter optimization problem, which is of great significance for implementing fractional-order chaos control and synchronization. Aiming at the parameter estimation problem of fractional-order chaotic systems, an improved algorithm based on bird swarm algorithm is proposed. The proposed algorithm further studies the social behavior of the original bird swarm algorithm and optimizes the foraging behavior in the original bird swarm algorithm. This method is applied to parameter estimation of fractional-order chaotic systems. Fractional-order unified chaotic system and fractional-order Lorenz system are selected as two examples for parameter estimation systems. Numerical simulation shows that the algorithm has better convergence accuracy, convergence speed and universality than bird swarm algorithm, artificial bee colony algorithm, particle swarm optimization and genetic algorithm.

In this paper, we analyze equal width wave equation using multi-quadric quasi-interpolation (MQQI) scheme. The traveling wave solutions called solitary waves: Single solitary wave motion, interaction of two and three solitary waves and evolution of solitons have been investigated computationally. Several comparisons are made to demonstrate the effectiveness of the proposed method. Error norms are used to observe the accuracy and efficiency of this scheme.

This research is aimed at presenting the two-dimensional steady fluid flow, represented by Williamson constitutive model past a nonlinear exponential stretching sheet theoretically. The system of ODEs describing the physical problem is successfully solved numerically with the help of the homotopy perturbation method (HPM). Special attention is given to study the convergence analysis of the proposed method. The influences of the physical governing parameters acting on the fluid velocity and the fluid temperature are explained with the help of the figures and tables. Further, the presented numerical method is employed to calculate both the rate of heat transfer and the drag force for the Williamson fluid flow. In particular, it is observed that both the Eckert number and the dimensionless convective parameter have the effect of enhancing the temperature of the stretching surface, while the inverse was noted for the dimensionless mixed convection parameter. Finally, the comparison with previous numerical investigations of other authors at some special cases which is reported here proves that the results obtained via homotopy perturbation method are accurate and the numerical method is reliable.

Traditional link prediction indices focus on the degree of the common neighbor and consider that the common neighbor with large degree contributes less to the similarity of two unconnected endpoints. Therefore, some of the local information-based methods only restrain the common neighbor with large degree for avoiding the influence dissipation. We find, however, if the large degree common neighbor connects with two unconnected endpoints through multiple paths simultaneously, these paths actually serve as transmission influences instead of dissipation. We regard these paths as the tie connection strength (TCS) of the common neighbor, and larger TCS can promote two unconnected endpoints to link with each other. Meanwhile, we notice that the similarity of node-pairs also relates to the network topology structure. Thus, in order to study the influences of TCS and the network structure on similarity, we introduce a free parameter and propose a novel link prediction method based on the TCS of the common neighbor. The experiment results on 12 real networks suggest that the proposed TCS index can improve the accuracy of link prediction.

To depict the effect of low-visibility foggy weather upon traffic flow on a highway with slopes, this paper proposes an extended car-following model taking into consideration the drivers’ misjudgment of the following distance and their active reduction of the velocity. By linear stability analysis, the neutral stability curves are obtained. It is shown that under all the three road conditions: uphill, flat road and downhill, drivers’ misjudgment of the following distance will change the stable regions, while having little effect on the sizes of the stable regions. Correspondingly, drivers’ active reduction of the velocity will increase the stability. The numerical simulations agree well with the analytical results. It indicates that drivers’ misjudgment contributes to a higher velocity. Meanwhile, their active reduction of the velocity helps mitigate the influences of small perturbation. Furthermore, drivers’ misjudgment of the following distance has the greatest effect on downhill and the smallest effect on uphill, so does drivers’ active reduction of the velocity.

In this work, we study a continuous opinion dynamics model considering 3-agent interactions and group pressure. Agents interact in a fully-connected population, and two parameters govern the dynamics: the agents’ convictions $\lambda$ that are homogeneous in the population, and the group pressure $p$. Stochastic parameters also drive the interactions. Our analytical and numerical results indicate that the model undergoes symmetry-breaking transitions at distinct critical points ${\lambda }_c$ for any value of $p<p^{\ast }=2/3$, i.e. the transition can be suppressed for sufficiently high group pressure. Such transition separates two phases: for any $\lambda \le {\lambda }_c$, the order parameter $O$ is identically null ($O=0$, a symmetric, absorbing phase), while for $\lambda >{\lambda }_c$, we have $O>0$, i.e. a symmetry-broken phase (ferromagnetic). The numerical simulations also reveal that the increase of group pressure leads to a wider distribution of opinions, decreasing the extremism in the population.

Behavior of swirling flow in a cylindrical container with top rotating lid has been investigated under the influence of a strong axial magnetic field. The flow is assumed to be axisymmetric for the parameters considered in the study. The flow domain consists of a cylindrical cavity with a top rotating lid packed with viscous incompressible electrically conducting fluid, e.g. liquid metal. A steady magnetic field acts perpendicular to the bottom wall of the cavity. When the top rotating lid rotates an Ekman boundary layer develops in vicinity to the top rotating lid. However, the presence of a Hartmann boundary layer not only restrains the vortex breakdown but also shifts its position to some extent. All the walls of the cavity are assumed to be electrically insulated.

The heterogeneous distribution of immunization probability has been proven to suppress the recurrent epidemic outbreaks effectively, but the reason for this interesting phenomenon is still unclear. To solve this problem, the effects of immunization probability on the maximal infected density and the average infected density are investigated, and it’s found that large immunization probability will depress the maximal infected density sharply. Moreover, it’s proved that small immunization probability is of great importance, which could not only reduce the cost of immunization at low risk but also decrease the outbreak risk of the next year by making the average infected density larger in the current year. Besides, a generalized immunization strategy is presented, which makes the immunization strategy easy to carry out and meanwhile keeps the maximal and the average infected density almost as good as those in the original dynamic immunization strategy. Moreover, the control effects in eight real networks are also investigated, which proves the usefulness of the modified dynamic immunization strategy. Our work proves the usefulness of the heterogeneous distribution of immunization probability and may present theoretical guidance for the government and the public to control the recurrent epidemic outbreaks.

Information dissemination groups, especially those disseminating the same kind of information such as advertising, product promotion, etc., compete with each other when their information spread on social networks. Most of the existing methods analyze the dissemination mechanism mainly upon the information itself without considering human characteristics, e.g. relation networks, cooperation/defection, etc. In this paper, we introduce a framework of social evolutionary game (SEG) to investigate the influence of human behaviors in competitive information dissemination. Coordination game is applied to represent human behaviors in the competition of asynchronous information diffusion. We perform a series of simulations through a specific game model to analyze the mechanism and factors of information diffusion, and show that when the benefits of competitive information is around 1.2 times of the original one, it can compensate the loss of reputation caused by the change of strategy. Furthermore, through experiments on a dataset of two films on Sina Weibo, we described the mechanism of competition evolution over real data of social network, and validated the effectiveness of our model.

The unsigned graphs containing positive links only, have been analyzed fruitfully. However, the physical relations behind complex networks are dissimilar. We often encounter the signed networks that have both positive and negative links as well. It is very important to study the characteristics of complex networks and predict individual attitudes by analyzing the attitudes of individuals and their neighbors, which can divide individuals into different clusters or communities. To detect the clusters in signed networks, first, a modularity function for signed networks is proposed on the basis of the combination of positive and negative part. Then, a new graph clustering algorithm for signed graphs has also been proposed based on CNM algorithm, which has high efficiency. Finally, the algorithm has been applied on both artificial and the real networks. The results show that the proposed method has been able to achieve near-perfect solution, which is suitable for multiple types real networks.

Based on simulation, the influence of the doors’ opening degree (DOD) on crowd evacuation is investigated in this paper. First of all, an evacuation model, which has one exit with two doors, is established by utilizing the software Pathfinder. Then, based on the obtained model, some evacuation scenarios are considered. The simulation results indicate, when the DOD is within 115^∘–135^∘, the time saving rate is more than 13%, and the maximum time saving rate is achieved when the DOD is 125^∘. Furthermore, there is a linear relationship between the mean square error and the number of the evacuees. For a small number of evacuees, the total evacuation time is mainly influenced by the distributions of the evacuees, however, as the number of the evacuees increases, it is mainly influenced by the number of the evacuees. Moreover, when the DOD is 125^∘, the mean flow rate per unit width (MFRPUW) decreases along with the increasing of exit’s width, however, it increases along with the increasing of exit’s width while the DOD is 180^∘. Compared with the 180^∘ DOD, the 125^∘ DOD can always achieve a higher MFRPUW, and the narrower the exit is, the higher MFRPUW the 125^∘ DOD achieves.

With the increase of emergencies in large public places, emergency evacuation research has become an important and urgent issue. This paper first proposes a tree hierarchical evacuation network. According to the hierarchical path selection strategy, the evacuation routes are obtained and sorted by the length of route. This hierarchical path selection strategy is more realistic than using the straight line distance. An evacuation model based on hierarchical directed evacuation network is presented in this paper, and a hierarchical directed artificial fish swarm algorithm is proposed to solve the evacuation problem. The model simulates the movements of pedestrians by means of preying, swarming, following and waiting behaviors of artificial fish swarm algorithm. During the evacuation process, the effects of congestion, retrograde and blocking time on evacuation speed and route selection are considered. The simulation results show that the proposed model and algorithm can effectively improve the evacuation efficiency in a stadium, and provide scientific and reasonable path guidance.

In the context of urban rail evacuation analysis, little work addresses the mechanism of passenger propagation between urban rail and bus systems. This paper attempts to quantify the propagation mechanism to make evacuation scheduling reasonable and effective. First, it provides a set of methods for characterizing the law of passenger propagation in the region affected by a rail station failure, based on the theory of interdependent networks. An interdependent public transport network between the rail transit and buses in the affected region is constructed using the methods of Space L and Space P. In the network, the initial capacities are modeled, the redistribution rules of passengers and the status identification rules of stations are established, and the propagation results are characterized. Second, using the passenger propagation impact of a faulty rail station, an emergency bus-scheduling model is set up, aimed at minimizing the operating costs of emergency buses and maximizing the benefits for passengers. A genetic algorithm is devised to solve the scheduling model. Finally, an example is put forward to verify the feasibility of the designed methods. The example shows that the methods provide theoretical support and a decision aid for passenger evacuation strategies at faulty urban rail stations.

The response function is the important information for the precise interpretation of experimental data and also for characterizing the developing nuclear instruments. Measurement of the response function normally requires a number of mono-energetic gamma-ray sources, a long acquisition time and an appropriate experimental setup. The Monte Carlo method, as an alternative to response function measurement, has widely been used and recommended. In this study, a computational model of an HPGe detector has been developed by using the MCNP5 code. To validate the simulated model, the simulations from mono-energetic sources have been compared to the corresponding measured data. Any deviation from the measurement could be attributed to the unmodeled details of the detector crystal, so they needed adjustment. Moreover, an analysis has been undertaken on the dependency of detection efficiency on the dead layer thickness of the germanium crystal. Having developed a computational model of the crystal, a set of correction factors was extracted to take into account the gamma-ray self-absorption within the source volume. The simulated model of the HPGe detector in this study can be used to calculate the detection efficiency when the samples are not of the standard geometry which require self-absorption considerations.

A new program created in C/C$++$ language generates automatically the analytic expression of grand potential and prints it in Latex2e format and in textual data. Another code created in Mathematica language can translate the textual data into a mathematical expression and help any interested to evaluate the thermodynamic quantities in analytic or numeric forms.