International Journal of Modern Physics C

The fluid flow over three staggered square cylinders at two symmetrical arrangements has been numerically investigated in this study. The numerical calculations are carried out for several values of the Reynolds number (Re) ranging from 1 to 180. The results are presented in the form of vorticity contours and temporal histories of drag and lift coefficients. Furthermore, the physical parameters, namely, the average drag and lift coefficients and Strouhal number are presented as a function of Re. Two different states of flow are found in this work by systematically varying Re: steady and unsteady states. The transition to unsteady state regime is exhibited via Hopf bifurcation first in the second configuration followed consequently by the first one with critical Reynolds number of Re${}_{\mathrm{\text{c}}}=22.37$ and Re${}_{\mathrm{\text{c}}}=22.45$, respectively. It is observed that the bifurcation point of the steady regime to the unsteady one is very much influenced by the change in the geometry of the obstacle. The unsteady periodic wake is characterized by the Strouhal number, which varies with the Reynolds number and the obstacle geometry. Hence, the values of vortex shedding frequencies are estimated for both the considered configurations. Computations obtained also reveal that the spacing in the wake leads to reducing the pressure and enhancing the fluid flow velocity for both arrangements by monotonically strengthening the Reynolds number value. Furthermore, the drag and lift coefficients are determined, which allowed determining; the best configuration in terms of both lift and drag. It is observed that the drag force is dependent on the obstacle geometry and strengthens while lowering the Reynolds number. On the other hand, an opposite trend of the lift drag evolutions is observed for both configurations and considerably affected by the arrangements shape.

The growth and development of COVID-19 transmission have significantly attracted the attention of many societies, particularly Iran, that have been struggling with this contagious, infectious disease since late February 2020. In this study, the known “Susceptible-Infectious-Recovered (SIR)” and some other mathematical approaches were used to investigate the dynamics of the COVID-19 epidemic to provide a suitable assessment of the COVID-19 virus epidemic in Iran. The epidemic curve and SIR model parameters were obtained with the use of Iran’s official data. The recovered people were considered alongside the official number of confirmed victims as the reliable long-time statistical data. The results offer important predictions of the COVID-19 virus epidemic such as the realistic number of victims, infection rate, peak time and other characteristics. Besides, the effectiveness of infection and immunization rates to the number of infected people and epidemic end time are reported. Finally, different suggestions for decreasing victims are offered.

In every country except China, COVID-19 first infection cases were imported by travelers, which are either people coming back to their own country or visiting foreigners (international or external tourists). In a global and regional phenomenological analysis of COVID-19 spread, we assume that tourism inflow is a trigger mechanism of worldwide dissemination at the pandemic onset days. Taking into account all countries, a convenient common-time origin timeline was employed as if the beginning of the epidemic would have occurred simultaneously in every country. We obtained very good statistical Pearson and Spearman correlations between accumulated infected cases by country and a positive power of the product $TP$, where $T$ is the tourism inflow before the pandemic and $P$ is the country population.

In this paper, we propose a cellular automaton model to simulate traffic flow controlled by a series of traffic lights. The synchronized traffic light and the green wave light strategies were investigated. The spatiotemporal diagrams, energy dissipation, and CO₂ emission of the system were presented. Our simulations are conducted to clarify the difference between both strategies and their effects on the traffic flow and the CO₂ emission. We found that the traffic flow depends mainly on the strategy used for managing the traffic lights as well as on the parameters of the traffic lights, namely the cycle length, the number of traffic lights and the length of the system. The fundamental diagram has barely the same characteristics for both methods and it depends on the combination of the parameters of the system. We find that the green wave is more convenient for the management of a series of traffic lights than the synchronized control strategy in terms of throughput, especially for large-sized systems. Unlike in terms of CO₂ emission and energy dissipation, both control strategies outperform each other depending on the density regions and the parameters of the system. Finally, we investigate the effect of both cycles (i.e. red and green) for the synchronized control method on the CO₂ emission. It is found that the green cycle generates often a series of acceleration events that increase CO₂ emission.

The study of community structure is of great significance when analyzing the structural and functional characteristics of networks. Attractor is a fast community detection method with the advantage of high accuracy for complex networks. However, in the connected nodes interaction model proposed by the Attractor algorithm, there is a problem with slow convergence during the distance updating process. To solve this problem, we propose an improved Attractor algorithm based on the change trend of the distances between connected nodes. We have generally found that distances between connected nodes exhibit a consistent trend. The dynamic distance trend is determined by setting a window of evaluation. The convergence of the Attractor algorithm is accelerated by the consistent change trend. Experiments on datasets for real-world networks and synthetic networks have shown that our proposed algorithm not only maintains high-quality communities, but also reduces the calculation time significantly and greatly improves the speed of the algorithm.

Current continuation describes the computational study concerning with the unsteady flow of Eyring–Powell magneto nanoliquid over a bidirectionally deformable surface. Transference of activation energy is used in the improvement of binary chemical reaction. Nonlinear significance of thermal radiation is also incorporated in the energy equation. Investigation has been carried out through convective Nield’s boundary restrictions. Firstly, useful combination of variables has been implemented to alter the governing PDEs into ODEs. Later on, Keller-Box approach has been adopted to obtain the numerical solution of the physical problem. Physical interpretations of obtained results are also described for temperature and mass concentration distributions through various graphs. Rate of heat transportation has been explained through tabular data for acceptable ranges of involved engineering parameters. It is detected that escalating amount of Brownian constraint provides a constant temperature distribution. It is also inspected through present investigation that escalating amounts of activation energy factor, thermophoresis parameter, radiation parameter, Biot number and temperature ratio parameter improve the concentration field. Moreover, the amount of heat transport has considerably improved by increasing the amounts of temperature controlling indices and Biot number. Convergence analysis and error estimations of the numerical solution are also presented through various mesh refinement levels of the computational domain. Finally, comparison benchmarks with the restricted cases have been presented for the validation of the results obtained through the present parametric investigation.

Originally, we would like to use traffic modeling for car-following model to recover the individual difference of driving behavior corresponding to honk effect under V2X environment. Traffic stability is related to the individual difference resulting from the honk effect, which states that the individual difference of honk effect plays a different significant impact on the traffic stability. Furthermore, the slowly varying behaviors are closely consistent with the individual difference corresponding to the honk effect for long waves. Numerical simulation indicates that the individual difference of driving behavior plays a different role on traffic flow dynamics under honk environment in car-following model.

Link prediction based on node similarity has become one of the most effective prediction methods for complex network. When calculating the similarity between two unconnected endpoints in link prediction, most scholars evaluate the influence of endpoint based on the node degree. However, this method ignores the difference in contribution of neighbor (NC) nodes for endpoint. Through abundant investigations and analyses, the paper quantifies the NC nodes to endpoint, and conceives NC Index to evaluate the endpoint influence accurately. Extensive experiments on 12 real datasets indicate that our proposed algorithm can increase the accuracy of link prediction significantly and show an obvious advantage over traditional algorithms.

The generalized windmill graphs are good models for many real-world networks. In this paper, we obtain analytic expressions for the eigenvalues of the adjacency matrices and of the Laplacian matrices of the generalized windmill graphs. Using this information, we study some structural and dynamical properties of these graphs. To the end, we investigate the metro networks of four France cities and propose our suggestions for the planning of public transport networks.

Link prediction has been widely applied in social network analysis. Existing studies on link prediction assume the network to be undirected, while most realistic social networks are directed. In this paper, we design a simple but effective method of link prediction in directed social networks based on common interest and local community. The proposed method quantifies the contributions of neighbors with analysis on the information exchange process among nodes. It captures both the essential motivation of link formation and the effect of local community in social networks. We validate the effectiveness of our method with comparative experiments on nine realistic networks. Empirical studies show that the proposed method is able to achieve better prediction performance under three standard evaluation metrics, with great robustness on the size of training set.

In this study, the incentive is defined based on feedback mechanism promoting propagation, and a novel model of behavior propagation is proposed based on feedback mechanism to investigate behavior propagation. In this model, the incentive includes the distance among individuals and the set of state and the influence of node is decided by the incentive and node degree, which explore the propagation effect under different network. The experimental results show the incentive and the propagation have positive correlation, and the propagating effect is determined by the network attribute. At the same time, the greater the degree of the node, the more obvious the incentive effect. Incentive results of nodes will continuously decline until they suffer second incentive.

The extortion strategy can let its surplus exceed its opponents by a fixed percentage, hence the influence of extortion strategy in a population games has drawn wide attention. In this paper, we study the evolution of extortion strategy with unconditional cooperation and unconditional defection strategies in the Kagome lattice with abundant triangles. Our investigation shows that the extortion strategy can act as catalysts to promote the evolution of cooperation in the networked Prisoner’s Dilemma game. Moreover, proper strength of extortion slope can improve the living environment of the cooperators, thus they enhance cooperation level in the network. Moreover, proper strength of extortion can not only enhance the cooperation level, but also delay the extinction of cooperation. The underlying overlapping triangles help individuals form cooperation cliques that play crucial roles for the evolution of cooperation in those lattices.

In some research involving opinion formation, there are some details that have not been studied deeply, just as the role of a person’s self-confidence in opinion dynamics. This small but important detail needs to be cleared up. Hence, in this paper, we want to discuss the self-confidence in opinion dynamics with regard to some common linear and nonlinear models: DeGroot, Friedkin–Johnsen, Deffuant–Weisbuch and Hegselmann–Krause (HK) model. We unfold that (1) A person’s self-confidence assumption has an important impact on the consensus condition in DeGroot model; (2) The relationship between the self-confidence on the initial opinion and the current opinion follows a Kuznets curve in Friedkin–Johnsen model; (3) A person’s self-confidence has a close relationship with the convergence parameter in Deffuant–Weisbuch model, which has little impact on the number of opinion clusters at the stable stage; and (4) A person’s self-confidence varies with time at first and then stays at a certain level finally in the HK model, while the person’s self-confidence does not change with time in above three models.

In this paper, the flapping dynamics and wake flow characteristics in the nonlinear hysteresis region are investigated experimentally by immersing a cantilevered flexible plate in uniform airflow. The experimental results show that the flapping mode of a cantilevered flexible plate in hysteresis region will be transited from periodical traveling wave mode to limited cantilever-like mode with the variation of Reynolds number. The flapping mode will greatly influence the kinetic parameters of a flexible plate and also wake flow characteristics. The comparison of Strouhal number values between flapping flexible plate and animals further indicates that the fluid dynamics between passive flapping and active swimming is similar to the obtained optimal propulsive efficiency. Flow visualization reveals that the Karman vortex street appears, vanishes and coherent structures of turbulent flow arise behind the stable flexible plate with increasing Reynolds number. Meanwhile, the measurements of pressure distribution in wake flow provide a good physical understanding of the energy-saving mechanism and the optimal arrangement in fish school. Moreover, the fast Fourier transform (FFT) spectra of fluctuating velocity indicate that the characteristics of wake flow are closely related to the flapping mode of flexible plate. The wake flow will come into strong harmonic excitation state when flapping mode transits into a limited cantilever-like mode.

By comparing with symplectic different methods, the quadratic element is an approximately symplectic method which can keep high accuracy approximate of symplectic structure for Hamiltonian chaos, and it is also energy conservative when there have chaos phenomenon. We use the quadratic finite element method to solve the H$ê$non–Heiles system, and this method was never used before. Combining with Poincar$ê$ section, when we increase the energy of the systems, KAM tori are broken and the motion from regular to chaotic. Without chaos, three kinds of methods to calculate the Poincar$ê$ section point numbers are the same, and the numbers are different with chaos. In long-term calculation, the finite element method can better keep dynamic characteristics of conservative system with chaotic motion.

A space-time collocation method (STCM) using asymptotically-constant basis functions is proposed and applied to the quantum Hamiltonian constraint for a loop-quantized treatment of the Schwarzschild interior. Canonically, these descriptions take the form of a partial difference equation (PDE). The space-time collocation approach presents a computationally efficient, convergent, and easily parallelizable method for solving this class of equations, which is the main novelty of this study. Results of the numerical simulations will demonstrate the benefit from a parallel computing approach; and show general flexibility of the framework to handle arbitrarily-sized domains. Computed solutions will be compared, when applicable, to a solution computed in the conventional method via iteratively stepping through a predefined grid of discrete values, computing the solution via a recursive relationship.