International Journal of Modern Physics C

This paper uses the finite volume lattice Boltzmann method (FVLBM) to simulate the transient heat conduction from macro- to nano-scales corresponding to Kn = 0.01–10. This model is used for two dimensional (2D) transient hotspot modeling. The results of the diffusive regime are compared with those of the Fourier law as a model of continuum mechanics and an excellent agreement is found in this regime. After the validation of model for the case of Kn = 0.01, it has been used for high-Knudsen number simulations and a test case with Kn = 10 is studied. By increasing the Knudsen number from 0.01 up to 10, the transition from totally diffusive to totally ballistic behavior has been discussed and the wave-feature of heat transport through the solid material has been investigated.

We propose accurate explicit numerical schemes based on the lattice Boltzmann (LB) method for multi-dimensional diffusion equations. In LB schemes, the velocity models D2Q9 and D2Q13 are used for two-dimensional equations and D3Q19 and D3Q25 for three-dimensional equations. We introduce free parameters that characterize the weight of the equilibrium distribution functions to reduce numerical errors. Consistency analysis through the fourth-order Chapman–Ensgok expansion of the distribution functions gives an approximate diffusion equation with error terms up to fourth-order. The relaxation parameter and weight parameters are determined so that second-order error terms are eliminated in the approximate equation. Stability analysis shows that we can find a relaxation parameter so that each of the presented schemes is stable for given diffusion coefficients and discretizing parameters. Numerical experiments for the isotropic and anisotropic benchmark problems show that the presented schemes derived from the velocity models D2Q13 and D3Q25 are useful for numerical simulations of practical problems governed by two- and three-dimensional diffusion equations, respectively. In particular, schemes in which the value of the relaxation parameter is set to be 1 demonstrate a fourth-order accuracy under the stability condition.

In this paper, we present a pseudo-random bit generator (PRBG) based on two lag time series of the logistic map using positive and negative values in the bifurcation parameter. In order to hidden the map used to build the pseudo-random series we have used a delay in the generation of time series. These new series when they are mapped x_n against x_n+1 present a cloud of points unrelated to the logistic map. Finally, the pseudo-random sequences have been tested with the suite of NIST giving satisfactory results for use in stream ciphers.

Majority of epidemics eradication programs work in preventive responsive way. The lack of exact information about epidemiological status of individuals makes responsive actions less efficient. Here, we demonstrate that additional tests can significantly increase the efficiency of "blind" treatment (vaccination or culling). Eradication strategy consisting of "blind" treatment in very limited local neighborhood supplemented by extra tests in a little bit larger neighborhood is able to prevent invasion of even highly infectious diseases and to achieve this at a cost lower than for the "blind" strategy. The effectiveness of the extended strategy depends on such parameters as the test efficiency and test cost.

In this paper, the lattice Boltzmann (LB) method is used in order to simulate non-Newtonian blood flows in deformable vessels. Casson's rheological model is adopted and a local correction to the relaxation time is implemented in order to modify the viscosity. The hyperelastic, hardening and anisotropic behavior of a flexible arterial wall is discussed and a closed-form solution is used to predict the deformed configuration of the vessel. A partitioned staggered-explicit strategy to couple the LB method and such analytical prediction is proposed.

A dynamical model with continuous opinion is proposed to study how the speech order and the topology of directed social network affect the opinion formation of free speech. In the model, agents express their opinions one by one with random order (RO) or probability order (PO), other agents paying attentions to the speaking agent, receive provider's opinion, update their opinions and then express their new opinions in their turns. It is proved that with the same agent j repeats its opinion more, other agents who pay their attentions to j and include j's opinion in their confidence level at initial time, will continue approaching j's opinion. Simulation results reveal that on directed scale-free network: (1) the model for PO forms fewer opinion clusters, larger maximum cluster (MC), smaller standard deviation (SD), and needs less waiting time to reach a middle level of consensus than RO; (2) as the parameter of scale-free degree distribution decreases or the confidence level increases, the results often get better for both speech orders; (3) the differences between PO and RO get smaller as the size of network decreases.

In the consensus formation dynamics, the effect of leaders and interventions have been widely studied for it has many applications such as in politics and commerce. However, the problem is how to know if it is necessary for one to make an intervention. In this paper, we theoretically propose a method for predicting the tendency and final state of collective opinion. By giving each agent a conviction c_i which measures the ability to insist on his opinion, we present an opinion formation model in which agents with high convictions naturally show up properties of the opinion leaders. Results reveal that, although each agent initially gets an opinion evenly distributed in the range [-1, 1], the collective opinion of the steady-state may deviate to the positive or negative direction because of the initial bias of the leaders' opinions. We further get the correlation coefficient of the linear relationship between the collective opinion and the initial bias according to both the experimental and theoretical analysis. Thus, we could predict the final state at the very beginning of the dynamic only if we get the opinions of a small portion of the population. The prediction would afford us more time and opportunities to make reactions and interventions.

This paper discusses the suitability of the Large Eddy Simulation (LES) turbulence modeling for the accurate simulation of the shock train phenomena in a convergent-divergent nozzle. To this aim, we selected an experimentally tested geometry and performed LES simulation for the same geometry. The structure and pressure recovery inside the shock train in the nozzle captured by LES model are compared with the experimental data, analytical expressions and numerical solutions obtained using various alternative turbulence models, including k–ε RNG, k–ω SST, and Reynolds stress model (RSM). Comparing with the experimental data, we observed that the LES solution not only predicts the "locations of the first shock" precisely, but also its results are quite accurate before and after the shock train. After validating the LES solution, we investigate the effects of the inlet total pressure on the shock train starting point and length. The effects of changes in the back pressure, nozzle inlet angle (NIA) and wall temperature on the behavior of the shock train are investigated by details.

In this paper, two-phase fluid mixture flow in rectangular two-inlet cavity is studied using lattice Boltzmann method (LBM). To simulate two-phase fluids with large viscosity difference, the pseudo-potential model is improved. The improved model is verified for surface tension through Laplace's law and shown much better performance in simulating fluids with large viscosity difference than pseudo-potential model. The multiple-relaxation-time (MRT) scheme is used to enhance numerical stability. Then the two-phase fluid mixture flow with same and different viscosity in two-inlet cavity is simulated by present lattice Boltzmann (LB) model, pseudo-potential LB model and volume-of-fluid (VOF) method, respectively. The comparison of these numerical results shows that LB model is more suitable for such kind of flow than VOF method, since it can reflect repulsive forces and transitional region of two-phase fluids in dynamic process. Moreover, it also shows that present LB model has better dynamic stability than pseudo-potential model. Furthermore, simulations of the two-phase fluid mixture flow with different fluid viscosities, inlet velocities, inlet heights and outlet positions using present LB model are presented, exhibiting their effect to contact area of fluids.

To alleviate traffic congestion, a variety of route guidance strategies have been proposed for intelligent transportation systems. A number of strategies are introduced and investigated on a symmetric two-route traffic network over the past decade. To evaluate the strategies in a more general scenario, this paper conducts eight prevalent strategies on an asymmetric two-route traffic network with different slowdown behaviors on alternative routes. The results show that only mean velocity feedback strategy (MVFS) is able to equalize travel time, i.e. approximate user optimality (UO); while the others fail due to incapability of establishing relations between the feedback parameters and travel time. The paper helps better understand these strategies, and suggests MVFS if the authority intends to achieve user optimality.