International Journal of Modern Physics C

In this paper, the flat-plate solar collector with different porosities is considered. The use of perforated absorbers has many advantages, including the diffusion of the absorbed radiation over the entire depth of the absorber, which increases the area of heat transfer and reduces the local flux density on absorbent surfaces. A parametric study based on numerical simulation is carried out by varying the absorber plate perforation diameter and fixing its spacing. The inlet mass flow rate is changed in a large interval in order to determine the optimal operating points. The heat diffusion and energy balance equations are formulated to be suitable to analyze the influence of the absorber plates’ perforation on the GTC thermal performance. That is why, the necessary basic assumptions are developed to simulate the heat exchange mechanism as accurate as possible. Therefore, the heated air thermal conductivity is neglected against that of the absorber which allows that constant surface heat flux condition to be applied at its outer well as well as at glazing cover. The methodology of simulation is completed by aided flowchart to handle the radiation loss and pressure drops’ validation.

In this paper, a cellular automata model with dual cruise-control limit is refined where the length of each cell is set to 1.5 m and each vehicle can still occupy five cells. The prominent feature of this new model is that these vehicles with low-speed and high-speed are not affected by noise and the slow start rule of the Takayasu and Takayasu model is introduced if there is an empty cell in front of the stationary vehicle. Based on the computer simulation results, one obtains that the new refined model can successfully reproduce the empirical characteristics of three-phase traffic flow theory. In the fundamental diagram, there are three-phase traffic states: Free flow, synchronized flow and wide moving jam. In particular, 2$Z$-characteristic for phase transitions can be presented. Furthermore, the propagation speed of the downstream front of the moving synchronized pattern (MSP) and wide moving jam is within the range of empirical observation data or close to the range of empirical observation data.

Practical synchronization between two $n$-dimensional nonautonomous chaotic systems is achieved by the method of event-triggered control in the case of parameter mismatch. This study focuses on parameter mismatch and its effect on synchronization performance. The synchronization criterion is deduced in the form of linear matrix inequality. The synchronization error bound is analytically estimated, which can reveal the relationships between the synchronization error and the parameters. It is proven that there exists a lower bound for the inter-event times between two event-triggered moments, which means no Zeno behavior will occur in this control scheme. The obtained results are applied to a gyrostat system. Subsequently, numerical simulations demonstrate the effectiveness of the control strategy.

In dealing with the problems of nonlinear and non-Gaussian systems, the Kalman particle filter (KPF) algorithm has been widely used for the aerial and underwater target tracking system, which is vulnerable to environmental interference in recent years, especially in military fields. However, in most of the target tracking research, the indexes used by researchers to evaluate tracking algorithms are usually limited to the state difference or the root mean square error in the tracking process, and the overall tracking effect is only evaluated by the tracking time. These indexes cannot be evaluated for the algorithm that does not have obvious error optimization performance in the tracking process but actually improves the overall tracking effect. Therefore, this paper proposes to evaluate the tracking effect of different tracking algorithms by using the mean square error of relative points in the plane control network of engineering survey. Simulation results show that the proposed performance index combined with the tracking sampling time and the mean square error of tracking position can effectively evaluate the local and global tracking performance of different algorithms.

Based on the multi-color contact process and the oriented percolation, this paper develops a novel statistical physics financial price model with jumps to simulate and understand the price fluctuation characteristics in the real market. In this model, the interaction between investors and the dynamic changes of their investment attitudes and strategies are simulated by the complex interactions between different states of particles in the multi-color contact process. This is considered to lead to the rise and fall of the prices of financial products and affect the financial market price fluctuations. In addition, the herd behavior of investors facing sudden information outside the market also leads to dramatic price jumps. The model uses the oriented percolation combined with the Poisson process to describe those sudden fluctuations, in which the magnitude of the price jump of financial product is reconstructed by the clusters of partial interactions in the system. Therefore, the model constructs a total price process by considering both normal price fluctuations caused by the interaction of investor attitudes and sudden price jump fluctuations caused by the herd behavior. Based on the proposed model, this paper selects different parameter sets to generate the simulated return series and studies some basic descriptive statistics, stylized facts, multi-fractal property and complexity behavior of the simulated return series. To verify the rationality of the model, this paper conducts the same analysis and comparison on the return series of the real financial market. The outcomes of analysis indicate that the model proposed in this paper can reproduce the main fluctuation characteristics in the real financial market to a certain extent.

Many factors can lead to ship collision accidents, and identifying the importance of these factors is crucial for marine safety management and risk assessment. Are there rooted factors that are responsible for the presence of other factors? Notably, it is hard to analyze the causal relationship between these factors, due to the diversity and the interwoven of factors, especially when the size of the accident sample is small. To address this problem, an accident-cause network and a cause-inducing chain network are constructed in this paper by extracting 98 causes from 300 ship collision accidents. Our results show that there are six hidden rooted causes, i.e. the captain did not give any orders of night, the navigation alarm on the bridge was not on, communication failure between the officer on duty and the sailor on duty, no vessel traffic service was established, the shipping company does not fully grasp the navigation management regulations which is important to ship safety, and defects in bridge resource management, responsible for the presence of others among 98 causes. Our findings may shed some new lights on how to avoid ship collision accidents.

Sales per capita (per number of employees) of the 2000 Forbes Magazine top publicly-traded companies (G-2000) and some of the world’s leading state-owned enterprises (SOE) are statistically analyzed. This hybrid or combined cumulative probability sales distribution per capita exhibits a two-class structure: a Pareto power law in the higher part and exponential in the lower part resembling a Boltzmann–Gibbs distribution, where money is conserved in economic trade like energy is conserved in elastic collisions. This global per capita sales two-class distribution is qualitatively similar to income and wealth distributions in many countries around the world.

The contact behaviors of rough surfaces, which consist of asperities with random geometric properties at small length scale, have been extensively investigated on contact behaviors in engineering and scientific research. Due to the complexity of loading condition and surface topography, the limitation of traditional statistical model leads to the inaccuracy of prediction for rough surface contact behaviors. Starting from the multi-asperity contact theory, we release the restrictions of classical GW model and propose an elastic-plastic interacting model to investigate the coalescence effect of neighboring asperities in this paper. Through numerous simulations and analyses, the results show that the plasticity can be measured by material and morphology parameters. With the increasing of plasticity and the decreasing of asperity peak distance, the contact interface transits from interaction dominated to coalescence dominated contact relationships. With the increasing of loading, the shape of contact zone changes from two independent circles with expanding radius to a joint point, and finally the contact zone becomes a single ellipse. The coalescence status of neighboring asperities is influenced by the plasticity and the initial distance between asperity peaks. Our study provides some basis for establishing a statistical or discrete rough surface model considering merging, predicting the contact behaviors between solids, and revealing the evolution of contact spot information.

Given an elementary cellular automaton (ECA) with local transition rule $R$, two different types of local transitions are identified: the ones in which a cell remains in its current state, called inactive transitions, and the ones in which the cell changes its current state, which are called active transitions. The number of active transitions of a rule is called its activity value. Based on latter identification, a rule $R_1$ is called a sub-rule of $R_2$ if the set of active transitions of $R_1$ is a subset of the active transitions of $R_2$.

In this paper, the notion of sub-rule for elementary cellular automata is introduced and explored: first, we consider a lattice that illustrates relations of nonequivalent elementary cellular automata according to nearby sub-rules. Then, we introduce statistical measures that allow us to compare rules and sub-rules. Finally, we explore the possible similarities in the dynamics of a rule with respect to its sub-rules, obtaining both empirical and theoretical results.

From the official report of narco-war-related casualties in Mexico from December 2006 to September 2011, we show that the inter-event time distribution (calculated for a range of minimum sizes) approximately obeys simple scaling laws similar to violent conflicts in Iraq (2003–2005), Afghanistan (2008–2010) and Northern Ireland (1969–2001). Furthermore, normalizing deaths by population municipalities (the smallest Mexican political entities) yields even better fitting results.

In this paper, the structural, electronic and optical absorption properties of $m$-aminobenzoic acid crystals (hereinafter referred to as $m$-amino) in the pressure range of 0–300GPa are calculated by density functional theory (DFT). The changing trend of the lattice constant of $m$-amino under different pressures is analyzed. We find that the crystal undergoes complex transformation. Furthermore, it can be seen that the structure of $m$-amino along the $b$-axis is stiffer than that along the $a$-axis and $c$-axis, suggesting that the crystal has anisotropic compressibility. Through the analysis of the band gap and density of states of $m$-amino, it is found that the electronic properties of $m$-amino are transformed from semiconductor phase to metal phase at 100GPa, then jump into the semiconductor phase and maintain the metal phase again in the pressure range of 150–250GPa. Repeated phase transitions indicate that the structure of $m$-amino becomes more unstable as the pressure increases. Besides, from the absorption spectra, the optical activity of $m$-amino is relatively high with the increase of pressure, and two obvious structural transitions are observed at 70 and 270GPa, respectively.

In the current study, a well-known fractional nonlinear differential equation called Zakharov–Kuznetsov equation which has many applications in engineering and physics is investigated. An effective computational techniques namely Daftardar–Jafari Method (DJM) and He’s fractional derivative are employed to model the problem for obtaining a high accuracy of the analytical solution. The governing equations are solved and comparison of the results with exact solutions is presented to evaluate the precision of the presented method. The outcomes reveal that the DJM is efficient and easy to utilize. Further, three-dimensional contour plots are depicted according to the suitable parameters values.

This theoretical thermal continuation deals with the radiative flow of Williamson nanofluid subject to the inclusion of microorganisms. The further modification in the bio-convective model is done by incorporating the heat source/sink and activation energy phenomenon. The motivation for the choice of Williamson nanofluid is referred to multidisciplinary rheological impact which may enhance the heating phenomenon upon inclusion of nanoparticles. A bidirectional moving surface is the source of inducing flow patterns. The governing expressions which result via thermal model are numerically simulated with a shooting scheme. The impact of flow parameters is identified for velocity change, heat transfer rate, concentration, and microorganism profile. Moreover, the numerical results in terms of different tables are framed out for observing the fluctuated pattern of heat transfer, concentration impact, and microorganism change. The outcomes simulated from the model reflect that a lower velocity rate is results for the velocity ratio parameter. The external heat source attributed the enhancement of heat transfer. Moreover, the concentration profile improves with activation energy and convection constant.

The bifurcation phenomenon generated in neurons is considered to be the cause of many neurological diseases, thus, lots of investigators have been dedicated to bifurcation control, but most of them only focus on the integer-order neuronal models and control methods. Recently, increasing number of research works have shown that the differential equations of fractional-order are more appropriate for description of the electrical properties of certain nerve cell membranes. In this paper, we employ a fractional-order washout filter to realize bifurcation control for fractional-order Morris–Lecar neuronal model. Computer simulation verifies the effectiveness and improved performance of the proposed method than the integer-order washout filter. In addition, the analysis of the fractional-order controller’s impacts on the model is also presented.