International Journal of Modern Physics C

This paper analyses the characteristics of separating pedestrian flow in T-shaped passage. Pedestrians would wave and the crowed phenomenon may happen in the connection area of the main passage and branch passage. In order to reduce the pedestrian conflicts, guide sign is set to guide the pedestrians and subconscious strength is introduced to show the effect of guide sign. On this basis, simulation model of separating pedestrian flow in T-shaped passage based on guide sign considering unbalanced flow is established. On the platform of MATLAB software, separating pedestrian flow simulation with the effect of guide sign is realized. Simulations indicate that efficiency of pedestrians passing the passage is improved with the effect of guide sign, suitable position of guide sign is obtained, and compared with the separating pedestrian flow based on guide sign without considering unbalanced flow, the model considering unbalanced flow is better in describing pedestrian distribution.

Recently, various ways are investigated to augment heat transfer in different applications such as porous ceramic domain. Adding nanoparticles to fluid is the best operational way to increase the conduction of fluids. In this paper, migration of nanofluid inside a porous duct under the impact of magnetic force is scrutinized. LBM is applied to present comprehensive parametric analysis for various concentrations of nanofluid, Hartmann, Reynolds, and Darcy numbers. Outputs illustrate that Nu augments with improve of Lorentz forces. Augmenting Da significantly enhances the convective flow in our model.

In this paper, we develop an analytical framework and analyze the percolation properties of a random network by introducing statistical physics method. To adequately apply the statistical physics method on the research of a random network, we establish an exact mapping relation between a random network and Ising model. Based on the mapping relation and random cluster model (RCM), we obtain the partition function of the random network and use it to compute the size of the giant component and the critical value of the present probability. We extend this approach to investigate the size of remaining giant component and the critical phenomenon in the random network which is under a certain random attack. Numerical simulations show that our approach is accurate and effective.

In this study, a thermal Large Eddy Lattice Boltzmann Method (LBM–LES) is applied to Taylor–Couette flow simulations, allowing detailed analysis of local heat transport over a wide range of Taylor numbers, including resolved transient Taylor vortices.

The challenge in thermal management of electric motors is to control the temperature in the air gap between rotor and stator due to the gap’s small width and complex geometry, in which Taylor vortices strongly influence the heat transfer. This thin gap — here simplified by an annulus — is solved for the first time by a Thermal Lattice Boltzmann Method with a Smagorinsky sub-grid model. The influence of the rotational velocity of the inner cylinder with Taylor numbers from 36 to 511 — corresponding to a Reynolds number on the inner cylinder of up to 126000 — is numerically investigated.

The simulations are validated on the basis of the global Nusselt number, where we find good agreement with a published measurement series, an empirical correlation and Finite Volume simulations using the SST turbulence model. Special attention is paid on predicting the critical Taylor number, which is reproduced almost exactly by Direct Numerical Simulations (DNS) with LBM, whereas LBM–LES slightly overestimates and the SST model further overestimates the occurrence of Taylor vortices.

Gene expression and its regulation is a nonequilibrium stochastic process. Different molecules are involved in several biochemical steps in this process with low copies. It is observed that the stochasticity in biochemical processes is mainly due to the low copy number of the molecules present in the system. Several studies also show that the nonequilibrium biochemical processes require energy cost. But cellular system has developed itself through natural evolution by minimizing energy cost for optimum output. Here, we study the role of stochasticity qualitatively in a network of two genes using stochastic simulation method and approximately measure the energy consumption for the gene expression process. We find that the noise in gene expression process reduces the energy cost of protein synthesis. Therefore, we argued that the stochasticity in gene expression may be a choice of cellular system for protein synthesis with minimum energy cost.

Two-dimensional incompressible fluid flows around square cylinders at different arrangements have been numerically analyzed in the present work. The calculations are carried out for several values of Reynolds number (Re) ranging from 20 to 180. The results are presented in the form of vorticity contours and temporal histories of drag and lift coefficients. Besides, the physical parameters, namely, the average drag and lift coefficients and Strouhal number, are evaluated as a function of Re. Two different states of flow are predicted in the current investigation by systematically varying Re for steady and unsteady regimes. Vortex shedding is studied at different arrangements of the square cylinders allowing the investigation of three possible configurations. Special attention is paid to compute the drag and lift forces acting on the different obstacles, which allowed determining the optimal configuration in terms of both drags and lifts. The unsteady periodic wake is characterized by the Strouhal number, which varies with the Reynolds number and the obstacle geometry. The values of vortex shedding frequencies are consequently calculated in this study.

The community is the dominant structure that exhibits different features and multifold functions of complex networks from different levels; accordingly, multiresolution community detection is of critical importance in network science. In this paper, inspired by the ideas of the network flow, we propose an intensity-based community detection algorithm, i.e. ICDA, to detect multiresolution communities in weighted networks. First, the edge intensity is defined to quantify the relationship between each pair of connected nodes, and the vertices connected by the edges with higher intensities are denoted as core nodes, while the others are denoted as marginal nodes. Second, by applying the expansion strategy, the algorithm merges the closely connected core nodes as the initial communities and attaches marginal nodes to the nearest initial communities. To guarantee a higher internal density for the ultimate communities, the captured communities are further adjusted according to their densities. Experimental results of real and synthetic networks illustrate that our approach has higher performance and better accuracy. Meanwhile, a multiresolution investigation of some real networks shows that the algorithm can provide hierarchical details of complex networks with different thresholds.

The focus of this paper is on aligned fiber-reinforced composites, where fiber centers were randomly distributed in their cross-sections. The volume fractions of fibers were $V_f=30$% and $V_f=50$%. Samples were built with the help of the simulated annealing technique according to the chosen Radial Distribution Functions (RDFs). For each sample, the fields of local stresses and heat fluxes were simulated by finite element method. Then, homogenization by volume averaging was performed in order to investigate both the effective mechanical and thermal properties. The effect of RDF shape on elastic and thermal properties was quantified along with the influence of the probability of near neighbors of fibers on the physical properties. The more the fiber distributions deviate from Poisson’s Law, the higher the results compared to the lower bound of Hashin–Shtrikman.

A dilemma game is presented to study the crossing conflicts at unsignalized intersection. Each driver has two possible strategies: cooperation (driver who respects the right-hand priority rule) or defection (driver who crosses quickly or aggressively the intersection without any caution). A evolutionary dilemma game is played when two drivers (left and right drivers) attempt to cross simultaneously the intersection. In this game, the left driver has a trade-off between crossing the intersection safely and doing it quickly. In addition, each driver, within a distance $D_Z$ from the intersection, may be able to change his strategy, at time $t+1$, by imitating the driver in front of him and who got through the crossroad at time $t$. We study the outcomes of these behavior strategies and their impacts on the traffic capacity of the system. An analysis of these results shows that the strategies adopted by drivers at unsignalized intersection are intrinsically linked to the occurrence of collisions between left and right drivers and can have subconscious effects on their decisions making. The traffic flow capacity is computed using computer simulations for various values of the system parameters and we found that it is extremely dependent on the decisions of drivers crossing the intersection.

In this paper, we propose a new type of finite difference weighted essentially nonoscillatory (WENO) schemes to approximate the viscosity solutions of the Hamilton–Jacobi equations. The new scheme has three properties: (1) the scheme is fifth-order accurate in smooth regions while keep sharp discontinuous transitions with no spurious oscillations near discontinuities; (2) the linear weights can be any positive numbers with the symmetry requirement and that their sum equals one; (3) the scheme can avoid the clipping of extrema. Extensive numerical examples are provided to demonstrate the accuracy and the robustness of the proposed scheme.