International Journal of Modeling, Simulation, and Scientific Computing

This paper addresses the issue of managing the traffic flow at traffic-light controlled junctions adopting a mixed, nonlinear programming model. More precisely, we adopt an adaptive, acyclic control system based on the genetic algorithm (GA), a system that allows to accurately decide in real time on the light switching pattern that minimizes the traffic waiting time. Equally importantly, the inherent crossroads constraints, namely, the security of their users and the structure thereof, also referred to as the antagonism principle, are considered in the proceeding of this method.

The implementation of this model on two crossroads significantly decreases the waiting time and regulates the traffic flow. Therefore, the adaptive control system based on the GA proves efficient compared to the nonadaptive system.

The electricity market is a complex system in which participants interact and compete with each other, which makes description of them with mathematical models difficult. To solve these difficulties, computer simulation has become one of the main methods for studying electricity market problems. How to establish a reasonable electricity market has always been a major research issue in the electric power industry, for which a key point is the bidding mechanism. Agent-based modeling and a simulation (ABMS) method are used in this paper to study the imperfect competitive electricity market. An agent-based simulation method of multilateral bargaining game theory in the dynamics of the power bidding market is presented, and a multi-agent power market bidding dynamics simulation model based on game theory is established. The dynamic bidding game behavior among the government, power grid companies, power plant companies, and consumer parties is simulated in the market, and the simulation method is realized by Anylogic software. Finally, an agent-based four-party competitive dynamic game simulation in the electricity market is implemented, which provides a theoretical reference for further understanding resource optimization problems in the electricity market.

Dimensional variation analysis in multistation manufacturing processes (MMPs) is a challenging research topic with great practical significance. Researchers have been focused on constructing various mathematical models to identify the correlations among the huge amounts of collected production data. However, current models have achieved insufficient insights into the variation correlation laws due to the complexity of the data’s mutual relations. In this study, a data-driven modeling method is developed for deep data-mining and dimensional variation analysis. The proposed initial mathematical expression originates from practical engineering knowledge. Through a mathematical treatment, the mathematical expression is transformed into a first-order AR(1) model format, which contains multiple dimensional variations’ interstation and temporal correlating information. To obtain this information, the estimation of the proposed model is discussed in detail. A simulation case involving two key product characteristics of a grinding process is used to demonstrate the effectiveness and accuracy of the proposed method for dimensional variation analysis in MMPs.

Based on traditional continuous control strategy for Continuously Variable Transmission (CVT) ratio, according to the principles of shift control strategy for stepped automatic transmission, the influences of throttle opening and external resistance or vehicle speed on CVT ratio control are analyzed on bumpy road. Under the same variation of external resistance condition, the differences between optimal economic control strategy and optimal dynamic control strategy are discussed. Then, the traditional continuous optimal dynamic and economic control lines are divided into multi-step upshift points. Meanwhile, the corresponding downshift points are set to avoid the interference near shift points. After that, the novel discretized ratio control methods for CVT system are proposed. By respectively discretizing throttle opening and vehicle speed, the discretized ratio control strategy for throttle opening, and the integrated discretized ratio control strategy for throttle opening and vehicle speed are further proposed and simulated. Furthermore, the hardware-in-the-loop (HIL) test system is built to further verify the feasibility and accuracy of discretized ratio control strategies. Both simulation and HIL test results show that the sensitivity of throttle opening and vehicle speed to ratio control is reduced dramatically, the fluctuation of ratio is decreased considerably, the transmission efficiency is increased significantly, and the jerk is declined moderately.

To define the application fields of the traditional cab system model and the seat–cab coupled model, this paper mainly aims to investigate the differences of the vibration characteristics of the two models. First, the two models and their motion equations were introduced. Then, based on the mechanical parameters of the seat and cab system for a truck, the transmissibility characteristics of the two models were analyzed. The results show that the traditional model can relatively accurately predict the pitch and roll vibration characteristics of the real seat–cab system. However, it overvalues the vertical vibration transmitted from the front suspensions of the cab. Third, the typical excitation conditions and the measuring points were selected. Finally, under the typical excitation conditions, the dynamic responses of the measuring points were calculated. The results show that under the vertical excitation condition, the dynamic responses of the two models have obvious differences. Under the roll excitation condition and the pitch excitation condition, the roll responses and the pitch responses of the cab between the two models show almost no obvious difference. Under the random excitation condition, the vertical acceleration responses have relatively larger deviations between the two models, however, the angular acceleration responses are almost the same. For the preliminary design of the cab system, the traditional cab system model can be used. However, for the accurate design and the optimization of the seat–cab system, the seat–cab coupled model is recommended.

The advancements in Mobile Ad-hoc Network (MANET) are suitable to wide applications, which involve military applications, civilian domains, and disaster recovery systems. It is assumed that the nodes present in the routing protocols of MANETs are cooperative and trustworthy. This assumption makes MANET more prone to manipulation and interception, which generates several possibilities of different suspicious attacks, such as Denial of Service (DoS) attacks. Hence, security is considered as an important parameter as the network is fond of suspicious attacks. This paper addresses the security issues by proposing an optimization algorithm, named Jaya Cuckoo Search (JCS) algorithm, which is the combination of Jaya algorithm and Cuckoo Search (CS) algorithm for initiating secure route among the MANET nodes so that the path attained is feasible and secure. The proposed JCS algorithm uses a fitness function, which considers a multiobjective function using parameters, such as distance, link lifetime, delay, energy, trust, along with the reputation factor to select a secured path. The JCS algorithm shows maximum performance with energy, throughput, and PDR values as 27.826J, 0.554, and 0.628, respectively.

In this work, the spread of a contagious disease on a society where the individuals may take precautions is modeled. The primary assumption is that the infected individuals transmit the infection to the susceptible members of the community through direct contact interactions. In the meantime, the susceptibles gather information from the adjacent sites which may lead to taking precautions. The SIR model is used for the diffusion of infection while the Bass equation models the information diffusion. The sociological classification of the individuals indicates that a small percentage of the population takes action immediately after being informed, while the majority expects to see some real advantage of taking action. The individuals are assumed to take two different precautions. The precursory measures are getting vaccinated or trying to avoid direct contact with the neighbors. A weighted average of states of the neighbors leads to the choice of action.

The fully connected and scale-free Networks are employed as the underlying network of interactions. The comparison between the simple contagion diffusion and the diffusion of infection in a responsive society showed that a very limited precaution makes a considerable difference in the speed and the size of the spread of illness. Particularly, highly connected hub nodes play an essential role in the reduction of the spread of disease.

In this paper, a second-order singularly perturbed initial value problem is considered. A hybrid scheme which is a combination of a cubic spline and a modified midpoint upwind scheme is proposed on various types of layer-adapted meshes. The error bounds are established for the numerical solution and for the scaled numerical derivative in the discrete maximum norm. It is observed that the numerical solution and the scaled numerical derivative are of second-order convergence on the layer-adapted meshes irrespective of the perturbation parameter. To show the performance of the proposed method, it is applied on few test examples which are in agreement with the theoretical results. Furthermore, existing results are also compared to show the robustness of the proposed scheme.

In this paper, using the theoretical analysis method, according to the actual structure of the hanging leaf spring of the traction motor mounted on the frame, the lateral force model of the hanging leaf spring of the traction motor was established. Then, through theoretical deduction, the deformation analytical calculation formula and the stress analytical calculation formula of the hanging leaf spring were established. The correctness of the leaf spring’s lateral force model was established and its deformation and stress analytical formulae were verified using ANSYS finite element analysis software. Based on this, according to the deformation analytical formula and the stress analytical formula of the leaf spring established, the influence of the main structural parameters on the mechanical characteristics of the leaf spring was discussed, and the reliability of the analytical analysis method of the lateral mechanical characteristics of the traction motor hanging leaf spring was verified by the loading–unloading test. The results show that the deformation and the load of the leaf spring change linearly. The changes of leaf spring’s stress at different positions can be considered as being composed of three sections: a linear change section in the root, a nonlinear change section in the middle, and a nonlinear change section in the end. In the structural parameters, the end thickness $h_2$ has the greatest influence on the stiffness and the stress of the leaf spring, and the maximum thickness of the leaf spring eye $h_1$ has the least influence on the stiffness and the stress of the leaf spring. The influence degree of other parameters on the stiffness of the leaf spring is $h_3$, $L_1$, $L_3$, $L_2$ in order, and the influence degree on the stress of the leaf spring is $h_3$, $L_1$, $L_2$, $L_3$ in order. In addition, when the root thickness $h_3$ is greater than a certain value, the maximum stress point of the leaf spring appears at the end position $L_2$. This study can provide a useful reference for the intelligent forward design and the rapid analysis of the mechanical characteristics of high-speed train traction motor hanging leaf spring.

Numerical study of ocean eddies has been carried out by using high-resolution ocean general circulation models. In order to understand ocean eddies from the large volume data produced by simulations, visualizing only eddy distribution at each time step is insufficient; time-variations in eddy events and phenomena must also be considered. However, existing methods cannot precisely find and track eddy events such as amalgamation and bifurcation. In this study, we propose an original approach for eddy detection, tracking, and event visualization based on an eddy classification system. The proposed method detects streams and currents as well as eddies, and it classifies discovered eddies into several categories using the additional stream and current information. By tracking how the classified eddies vary over time, detecting events such as eddy amalgamation and bifurcation as well as the interaction between eddies and ocean currents becomes achievable. We adopt the proposed method for two ocean areas in which strong ocean currents exist as case studies. We visualize the detected eddies and events in a time series of images, allowing us to acquire an intuitive understanding of a region of interest concealed in a high-resolution data set. Furthermore, our proposed method succeeded in clarifying the occurrence place and seasonality of each type of eddy event.