International Journal of Modern Physics C

The impact of various sizes and positions of the heater in a nanofluid-saturated porous lid-driven chamber with a uniform Lorentz force is studied numerically. In this investigation, three different lengths of heater with higher temperature at six different locations along the left sidewall of the cavity are considered. Lower temperature is maintained at the right sidewall. Further, lower and moving upper horizontal walls and the rest of left wall are supposed to be thermally insulated. Based on the finite volume method, the system of nondimensional governing equations is solved by SIMPLE algorithm. The results conclude that the average Nusselt number is reduced with the enhancement of Richardson and Hartmann numbers. When the heater length is reduced from bottom to top, the heat transfer rate is increased for all the considered Richardson, Darcy and Hartmann numbers. In the lower permeability of the porous medium, the effect of solid volume fraction of nanofluid is more vulnerable. In the case of nanofluid, the steady state is reached quickly than the pure fluid.

It is significant to assign reputation scores to users and identify spammers in the bipartite rating networks. In this paper, we propose an Iterative Group-based and Difference Ranking (IGDR) method, which is based on the original Iterative Group-based Ranking (IGR) method. The IGR method considers users grouping behaviors, but it ignores the characteristics of the individual ratings. It is discovered that individual rating characteristics could also contribute to the redistribution of reputation scores of users. The user with a smaller rating deviation will be given a higher reputation score. The proposed method outperforms IGR method ranging from 8% to 163% tested on three real datasets. It also can be applied to deal with big data in a short time.

Social media plays a crucial role in controlling the epidemic spreading by creating awareness. Epidemic spreading processes over the multiplex network where epidemic spreading in one layer and awareness spreading in another layer, are well suitable to study the spreading of infection in a small region. Using the Microscopic Markov chain approach (MMCA), the dynamical interplay between the spreading of epidemics over the physical contact layer and human awareness diffusion over the virtual contact layer over a multiplex network framework is analyzed. SEIR process for epidemic spreading and UAU process for awareness diffusion are assumed to study the spreading process of COVID-19. The basic-reproduction number $R_0$ is determined using the next generation matrix approach. The stability of disease-free equilibrium (DFE) and endemic equilibrium (EE) is analyzed. Using Pontryagins Minimum Principle, optimal parametric values are determined analytically for testing and cleaning the virus-contaminated surfaces. The impact of various parameters over the epidemic spread is analyzed numerically. Through numerical illustrations, the effect of early identification of exposed people and immediate cleaning of virus-contaminated surfaces over $R_0$ studied. The sensitivity analysis is performed to show the importance of wearing face-mask, following social distancing, washing hands frequently and, avoiding unnecessary travel. Through numerical simulations, the results obtained coincide with real data of COVID-19 spreading in the city Chennai, India. The results obtained show that in order to control or discard the spreading of COVID-19, each people should follow the self-preventive measures without relaxation till the epidemic comes nearer to the disease free state.

In this paper, porous chamber with considering nanomaterial as operating fluid has been scrutinized. The transportation of nanopowder was controlled by magnetic force and insert of porous media boosts the cooling rate. Such zone needs special model to involve the impact of porous media and in this paper, non-Darcy technique was utilized. Low fraction of hybrid nanomaterial leads to good accuracy of homogeneous model and empirical correlations have been employed to forecast the features of operating fluid. Entropy generation was studied to find the influence of each term on irreversibility of unit. Also, two significant functions were calculated, namely, Be and Nu. Influences of Ra, Da and Ha on contours plots were reported in outputs. As Ra augments, the convection becomes stronger and augmentation of $\mathrm{\Psi }$ proves this fact. Also, temperature of elliptic surface declines about 48% with intensifying Ra. Temperature of elliptic surface augments about 34.6% with augment of Ha while it declines about 25.7% considering greater permeability. Nu augments about 238%, 11.49% with rise of Ra, Da but it declines about 28.3% with rise of Ha. Be intensifies with rise of Ha about 7.76% while it reduces about 75.2% with augmentation of Ra.

Bangladesh has been combating the COVID-19 pandemic with limited financial resources and poor health infrastructure since March, 2020. Although the government has imposed several restricted measures to curb the progression of the outbreak, these arrays of measures are not sustainable in the long run. In this paper, we use a data-driven forecasting model considering susceptible, exposed, infected, recovered and deaths status through time to assess the impact of lift of flexible lockdown on the COVID-19 dynamics in Bangladesh. Our analysis demonstrates that the country might experience second infection peak in six to seven months after the withdrawal of current lockdown. Moreover, a prolonged restrictions until January, 2021 will shift the infection peak towards August, 2021 and reduce approximately 20% COVID-19 cases in Bangladesh.

A comparative analysis of the COVID-19 diffusion in North African countries, Algeria, Egypt, Morocco and Tunisia has been carried out with the aim to study the effects of the containment efforts in different nations and the reliability of the predictions based on the data fits by macroscopic growth laws with a small number of free parameters. The comparison with data shows that the Coronavirus spreading has often different phases: an initial exponential behavior, followed by a Gompertz one and/or by a logistic phase, due to containment effort. The study of the growth phases permits to verify the restarting of the disease spreading after a stationarity period due to new outbreaks or to the weakness of the social control measures. The response of the National Health Systems to the emergency is discussed and some short-term predictions on the cumulative number of confirmed infected, on the hospitalizations and on the total number of deaths is done. The possible correlation with immigration in other Mediterranean Countries has been analyzed. Stable (or unstable) condition of the spreading can quickly change due to a stronger or weaker application of the lockdown measures and short-term predictions turn out to be reliable.

In this study, wall modeled large-eddy simulations (LES) were performed with a finite volume method for a 25^∘ compression-expansion ramp to investigate the different aspects of the 3D interaction of shock wave with a turbulent boundary layer. The hybrid initialization and dynamic grid adaption techniques were employed to decrease the computational cost and numerical errors. Shadowgraph contours, presenting Laplacian of density, were used to analyze structures of fine flow to have a distinct illustration of shock-wave structures. The simulated results were validated against experimental data in the same geometrical and boundary conditions. According to wall pressure distribution and averaged velocity profiles, there was a good agreement between current numerical results and available data. After validating the numerical methodology, the effects of arched and curved surfaces as passive control methods on shock wave boundary layer interaction (SBLI) were investigated. The results showed that using arched and curved surface, the separation zone can diminish; therefore, these two ways are the efficient passive control methods to reduce the strength of the shock waves.

Marangoni surface tension forcing soap film is numerically solved by Lattice Boltzmann Method (LBM). A delicate false force term in the LBM equation is proposed to describe the Marangoni forcing soap film. The validity of LBM is elucidated by the linear theory of surface tension profile as a function of the vertical position of the soap film. The effect of thickness on the statistical behaviors of the Marangoni forcing soap film is discussed from three aspects: the energy spectrum, energy transfer and intermittency. It is found that the scaling behavior of energy spectrum is independent of the scaling constant of thickness $\alpha$ where the range of $\alpha$ is from 0.2 to 0.3. The scaling behavior of energy spectrum is $k^{-5∕3}$, which is in accordance with the Kraichnan theory in the inverse cascade. In the large-scale range, the energy flux cascades to the small scale which is called as a forward cascade process. In this scale range, more energy flux cascades to the small scale when the value of $\alpha$ becomes larger. On the contrary, the backward cascade is involved in the small-scale range of the thinned film where more energy transfers to the large scale as the value of $\alpha$ is smaller. The intermittency measured by PDF of the velocity increment exists in the turbulent soap film. The universal scaling law of the velocity structure function is identical with the 3D S-L intermittency model and our 2D intermittency theory.

In this paper, an improved evolutionary prisoner’s dilemma (PD) game model is proposed by considering the weighting effect. Taking into account individual’s perceived payoff (benefits), the evolutionary tendency of the cooperators and three equilibrium points of the proposed model are obtained. We then numerically investigate how different exterior and interior factors influence on individuals’ cooperative behavior and their payoff both in the ER random network and the BA scale-free network. Our results reveal that the heterogeneous network structure is conducive to cooperation. In addition, the existence of leader nodes is an important driving force for promoting individuals’ cooperation. By further analyzing the rationality coefficient which appears in the weighting function, we obtain that a greater of irrationality could lead more people to take cooperative strategies. Finally, two indicators which are used to measure the real average payoff and perceived average payoff are defined. The results show that the real average payoff and perceived average payoff are larger in the heterogeneity network than that in homogeneous network.

The motion of a neutrally buoyant circular particle in a parallel double-lid-driven square cavity is studied with the lattice Boltzmann method. To understand, predict and control the motion of the circular particle, the effects of the initial position and particle size are studied. If the circular particle is placed at the centerline of the square cavity, at the steady state, it is confined at the bottom left corner, otherwise, the circular particle is stabilized at the 8-like trajectory, which is created by both the inertia of the circular particle and the confinement of the boundaries of the square cavity. The effect of the particle size on the motion of the circular particle is obvious, with the increase of the particle size, the confinement of the boundaries of the square cavity becomes stronger, and the 8-like trajectory shrinks toward the center. Furthermore, if the particle size is large enough, the centrifugal motion of the circular particle becomes weaker, and the circular particle cannot cross the centerline of the square cavity.

The impetus of this study is to evaluate the performance of the anisotropic minimum-dissipation (AMD) subgrid-scale model (SGS) for flow over a gently-curved backward-facing step (BFS) at a Reynolds number of 13 700. Minimum-dissipation sub-grid models were developed as simple alternatives to the dynamic eddy-viscosity SGS models. AMD model is a static type of eddy-viscosity SGS model incorporating anisotropic SGS effects into numerical predictions through the large-eddy simulation (LES) approach. The open-source CFD package of OpenFOAM was used to implement the AMD model. Before focusing on the BFS flow, we investigated the impact of the AMD model coefficient magnitude on the numerical predictions of the decaying isotropic turbulence flow. In the next step, numerical solutions were obtained for the curved backward-facing step using the AMD model and Dynamic Smagorinsky model (DSM). The curved backward-facing step was considered here for the evaluation of the SGS model predictions due to its weak adverse pressure gradient and high sensitive flow mechanism. The rescaling/recycling method was employed as a turbulent inflow generation technique. The AMD model results were compared with the prediction of the DSM and Vreman model. Moreover, AMD model predictions were compared with the reported solutions obtained using different turbulent inflow generation methods. The assessments revealed the high capability of the AMD model to capture decaying turbulence and predict velocity profiles and resolved flow statistics turbulent parameters in the gently-curved backward step flow.

We have developed a probabilistic model to quantify the risks of COVID-19 explosion in Brazil, the epicenter of COVID-19 in Latin America. By explosion, we mean an excessive number of new infections that would overload the public health system. We made predictions from July 12th to Oct 10th, 2020 for various containment strategies, including business as usual, stay at home (SAH) for young and elderly, flight restrictions among regions, gradual resumption of business and the compulsory wearing of masks. They indicate that: if a SAH strategy were sustained, there would be a negligible risk of explosion and the public health system would not be overloaded. For the other containment strategies, the scenario that combines the gradual resumption of business with the mandatory wearing of masks would be the most effective, reducing risk to considerable category. Should this strategy is applied together with the investment in more Intensive Care Unit beds, risk could be reduced to negligible levels. A sensitivity analysis sustained that risks would be negligible if SAH measures were adopted thoroughly.

Air transportation networks play important roles in human mobility. In this paper, from the perspective of multilayer network mechanism, the dynamics of the Chinese air transportation network are extensively investigated. A multilayer-based passengers re-scheduling model is introduced, and a multilayer cooperation (MC) approach is proposed to improve the efficiency of network traffic under random failures. We use two metrics: the success rate and the extra transfer number, to evaluate the efficiency of re-scheduling. It is found that a higher success rate of passengers re-scheduling can be obtained by MC, and MC is stronger for resisting the instability of the capacity of links. Furthermore, the explosion of the number of extra transfer can be well restrained by MC. Our work will highlight a better understanding of the dynamics and robustness of the Chinese air transportation network.

In this paper, group consensus of second-order multi-agent systems with nonlinear dynamics is investigated. First, we design the distributed protocols for achieving group consensus, in which the strengths of the interactions among the agents are enhanced through tuning the coupling strengths. Further, taking the difference of the edges among agents into account, edge-based distributed protocols through tuning coupling weights of a fraction of edges are designed. Remarkably, only the edges of spanning tree in each group are pinned and the coupling strengths or weights of pinned edges are enhanced according to the updated laws. Both the types of distributed protocols are proved analytically and verified by numerical illustrations.