International Journal of Modern Physics C

The numerical modeling of fluid interaction with a bouncing body has many applications in scientific and engineering application. In this paper, the problem of water impact of a body on free-surface is investigated, where the fixed ghost boundary condition is added to the open source code SPHysics2D¹ to rectify the oscillations in pressure distributions with the repulsive boundary condition. First, after introducing the methodology of SPH and the option of boundary conditions, the still water problem is simulated using two types of boundary conditions. It is shown that the fixed ghost boundary condition gives a better result for a hydrostatics pressure. Then, the dam-break problem, which is a bench mark test case in SPH, is simulated and compared with available data. In order to show the behavior of the hydrostatics forces on bodies, a fix/floating cylinder is placed on free surface looking carefully at the force and heaving profile. Finally, the impact of a body on free-surface is successfully simulated for different impact angles and velocities.

Road traffic status is significant for trip decision and traffic management, and thus should be predicted accurately. A contribution is that we consider multi-modal data for traffic status prediction than only using single source data. With the substantial data from Ningbo Passenger Transport Management Sector (NPTMS), we wished to determine whether it was possible to develop Stacked Autoencoders (SAEs) for accurately predicting road traffic status from taxicab operating data and bus smart card data. We show that SAE performed better than linear regression model and Back Propagation (BP) neural network for determining the relationship between road traffic status and those factors. In a 26-month data experiment using SAE, we show that it is possible to develop highly accurate predictions (91% test accuracy) of road traffic status from daily taxicab operating data and bus smart card data.

In this study, the problem of seed selection is investigated. This problem is mainly treated as an optimization problem, which is proved to be NP-hard. There are several heuristic approaches in the literature which mostly use algorithmic heuristics. These approaches mainly focus on the trade-off between computational complexity and accuracy. Although the accuracy of algorithmic heuristics are high, they also have high computational complexity. Furthermore, in the literature, it is generally assumed that complete information on the structure and features of a network is available, which is not the case in most of the times. For the study, a simulation model is constructed, which is capable of creating networks, performing seed selection heuristics, and simulating diffusion models. Novel metric-based seed selection heuristics that rely only on partial information are proposed and tested using the simulation model. These heuristics use local information available from nodes in the synthetically created networks. The performances of heuristics are comparatively analyzed on three different network types. The results clearly show that the performance of a heuristic depends on the structure of a network. A heuristic to be used should be selected after investigating the properties of the network at hand. More importantly, the approach of partial information provided promising results. In certain cases, selection heuristics that rely only on partial network information perform very close to similar heuristics that require complete network data.

The Ising model on all Archimedean lattices exhibits spontaneous ordering. Three examples of these lattices, namely triangular ($3^6$), honeycomb $(6^3)$ and Kagome $(3,6,3,6)$ lattices, are considered to study the kinetic continuous opinion dynamics model (KCOD) through extensive Monte Carlo simulations. The order/disorder phase transition is observed in all lattices for the KCOD. The estimated values of the critical disorder parameter are $p_c=0.123(3)$, $p_c=0.115(4)$, and $p_c=0.068(3)$ for $3^6$, $6^3$ and $(3,6,3,6)$ lattices, respectively. The critical exponents $\beta ∕\nu$, $\gamma ∕\nu$ and $1∕\nu$ for the model are $0.15(5)$, $1.64(5)$, and $0.87(5)$; $0.14(3)$, $1.64(3)$, and $0.86(6)$; $0.12(4)$, $1.59(5)$, and $1.08(6)$, for $(3^6)$, $(6^3)$ and $(3,6,3,6)$ lattices, respectively. These results agree with the majority-vote model on ($3^6$), ($6^3$), and $(3,6,3,6)$ lattices but are different from KCOD model results on square lattices $(4^4)$.

In this paper, we describe our studies of the sigma meson, $f_0(500)$, using two-pion correlation functions. We use lattice quantum chromodynamics in the quenched approximation with so-called clover fermions. By working at unphysical pion masses we are able to identify a would-be resonance with mass less than $2m_{\pi }$, and then extrapolate to the physical point. We include the most important annihilation diagram, which is “partially disconnected” or “single annihilation”. Because this diagram is quite expensive to compute, we introduce a somewhat novel technique for the computation of all-to-all diagrams, based on momentum sources and a truncation in momentum space. In practice, we use only $p=0$ modes, so the method reduces to wall sources. At the point where the mass of the pion takes its physical value, we find a resonance in the $0^{++}$ two-pion channel with a mass of approximately $609\pm 80$ MeV, consistent with the expected properties of the sigma meson, given the approximations we are making.

In this work, a detailed study of the structural, electronic and optical absorption properties of crystalline benzoic acid in the pressure range of 0–300GPa is performed by density functional theory (DFT) calculations. We found that occur complex transformations in benzoic acid under compression occurs, by analyzing the variation tendencies of the lattice constants, bond lengths and bond angles under different pressures. In the pressure range 0–280GPa, repeated formations and disconnections of hydrogen bonds between H1(P1) atom and O1(P1), O2(P4-$x$-$y$-$z$) atoms occur several times, and a new eight-atom ring (benzoic acid dimer) forms at 100GPa and 280GPa. Then, by analyzing the band gap and density of states (DOS) of benzoic acid, it is found that the crystal undergoes a phase transformation from insulator to semiconductor at 240GPa and it even becomes metal phase at 280GPa. In addition, the relatively high optical activity with the pressure increases of benzoic acid is seen from the absorption spectra, and three obvious structural transformations are also observed at 110, 240 and 290GPa, respectively.

In this paper, an improved real-time control model based on the discrete-time method is constructed to control and simulate the movement of high-speed trains on large-scale rail network. The constraints of acceleration and deceleration are introduced in this model, and a more reasonable definition of the minimal headway is also presented. Considering the complicated rail traffic environment in practice, we propose a set of sound operational strategies to excellently control traffic flow on rail network under various conditions. Several simulation experiments with different parameter combinations are conducted to verify the effectiveness of the control simulation method. The experimental results are similar to realistic environment and some characteristics of rail traffic flow are also investigated, especially the impact of stochastic disturbances and the minimal headway on the rail traffic flow on large-scale rail network, which can better assist dispatchers in analysis and decision-making. Meanwhile, experimental results also demonstrate that the proposed control simulation method can be in real-time control of traffic flow for high-speed trains not only on the simple rail line, but also on the complicated large-scale network such as China’s high-speed rail network and serve as a tool of simulating the traffic flow on large-scale rail network to study the characteristics of rail traffic flow.

By using the determined quantum Monte Carlo method, we explore the evolution of the pairing correlation depending on doping and frustration in the two-dimensional Hubbard model on an anisotropic triangular lattice. In the full frustrated system where the nearest hoping term $t$ is equal to the next nearest hoping $t^{\prime }$, the $d_{xy}$-wave pairing dominates over $d_{x^2-y^2}$ as the electron filling $〈n〉>1.20$. The $d_{x^2-y^2}$ superconducting pairing tends to be dominated as the frustration $t^{\prime }∕t$ decreases, and the decreasing electron fillings also push the system into a possible $d_{x^2-y^2}$ superconducting state. Our intensive nonbiased numerical results reveal the competition between $d_{x^2-y^2}$ and $d_{xy}$ superconducting pairing states, clarifying the different pairing symmetries in the $\kappa$-(BEDT-TTF)${}_{2}X$ family of organic charge transfer salts.

Considering the process of pedestrian evacuation as pedestrian walking freely from current position to exit and queuing at the exit, estimated evacuation time model for single pedestrian is established. Based on estimated evacuation time and shortest distance, pedestrian exit choice model is established considering pedestrian preference. Pedestrian exit choice model is added into pedestrian simulation model which is built based on cellular automata. Pedestrian evacuation behavior in multi-exits case is simulated. The simulations indicate that pedestrian evacuation model built in our work describes the pedestrian evacuation behavior well.

In this document, Greenberg’s classical traffic model is analyzed by varying the critical velocity $v_o$ that appears in it as a parameter. This model is transformed as a discrete expression and manipulated by means of isolating variables such as vehicular density $k$, flow $q$ and velocity $v$ that appear in the model. So-called fundamental diagrams are obtained by pairing two out of these three variables, and then they are used to support trajectories of iterated processes depicting distinct behaviors of traffic. As it is shown in this paper, those behaviors have monotonous and stable patterns for some range of values of the parameter $v_o$, but they can change to cyclic and stable trajectories when this parameter is modified. If the modifications of that parameter are taken to a higher range of values, then cycles of different periods appear, reaching chaotic trajectories. These behaviors are analyzed from a dynamical approach, proving their stability conditions, and then they are illustrated with simulations in each case.