International Journal of Modeling, Simulation, and Scientific Computing

The discrete event simulation with simultaneous events is discussed. Discrete models are treated as some points in the general space of models. The main topic of this paper is the convergence of sequences of continuous models to the corresponding discrete event model. It is pointed out that the discrete event models may represent some singularities in the space of models. This fact is related to the problem of validity of discrete event simulation. The models presented here are not the topic of the paper. These are known models, used as examples. The model of the “chicken game” and multiple elastic collisions are considered. It is shown that if a discrete event model is some special limit case of a sequence of continuous models with finite event duration, then that limit model is a singularity. It may provide results very different from the expected limit value of the results from the converging sequence of models.

Electrical Discharge Machining (EDM) is considered as the much traditional, adaptable and unconventional machining process that is proficient in generating complicated structures. Further, it is self-sufficient over the mechanical properties of workpiece materials only if it is conductive. The viability of the EDM process regarding the application types might get considerably improved with the constant enhancement in the personification of numerical control and the metal removal efficacy. This survey intends to make a review of 65 papers related to the optimization and modeling of EDM process machining. The analysis is thus made with regards to the following factors like Al alloy composite in Die Shrinking EDM, Optimization and Al metal matrix composites. Particularly, the hybrid optimization models in various papers are analyzed concerning their logic. Further, the algorithmic and parametric analysis is also made with the contributed papers. Finally, the research gaps and challenges in this EDM processing are discussed, which would pave the way for efficient research works in this area.

To design and check the strength of the Z-type guide arm of interconnected air suspensions for semi-trailers rapidly and effectively, this paper proposes the analytical calculation methods of its deformation and stress. First, based on the guide arm structure, it is marked as two parts by its mountpoint on the axle as the boundary. The part containing the eye was marked as Arm-1. The other part was marked as Arm-2. Then the analytical formulas of their stiffness and stress were derived, respectively. With a case study, the deformation and the stress were computed and simulated. The results show that the values computed are close to those simulated. The relative deviations are not more than 5.0%. The results show that the analytical formulas are acceptable. Moreover, it can be seen that for the superimposed Arm-1, when the other structural parameters are fixed, the position of the maximum stress is affected by the thickness ratio of the end thickness to the root thickness for each piece. Finally, a stiffness test was performed on the Z-type guide arm. The results show that the computed stiffness values are closed to those tested and the relative deviations are not more than 3.5%. This further verified the validity of the established model and methods.

Schistosomiasis is a parasitic disease from the family of Schistosomatidae and genus Schistosoma, which is caused by blood flukes. The disease is endemic in many countries and still a serious threat to global public health and development. In this paper, a new deterministic model is designed and analyzed qualitatively to explore the dynamics of schistosomiasis transmission in human, cattle and snail populations. Results from our mathematical analysis show that the model has a disease-free equilibrium (DFE) which is locally asymptotically stable (LAS) whenever a particular epidemiological threshold quantity, also known as basic reproduction number ($R_0$) is less than unity. Further analysis shows that the model has a unique endemic equilibrium (EE) which is globally asymptotically stable whenever $R_0>1$ and unstable when $R_0<1$. Furthermore, we adopt partial rank correlation coefficient for sensitivity analysis to reveal the most important parameters for effective control and mitigation of schistosomiasis disease in a community. Finally, we obtain some numerical results by simulating the entire dynamics of the model, which show that the infections in the compartments of each population decrease with respect to time. This further indicates that avoiding contact with infected human, cattle or infested water is vital to prevent the spread of schistosomiasis disease infection.

This study investigates the use of interactions as a metric to detect emergent phenomena in the ongoing agent-based simulations. The proposed algorithm aims to detect the flocking behavior in the Boids model. Boids model is simple to understand and to use and always verifies emergence. In recent years, several metrics have been proposed to investigate emergent behaviors in complex systems. Two main limitations of these studies are, how to choose a proper metric to avoid a high coast of computation, and how to detect emergence as it happens, i.e., live detection. In this paper, we propose an interaction-based algorithm to detect emergent behavior in Boids model. The three main contributions of this work are: (1) using interaction as metric, (2) detect emergence when it happens, (3) no need to store simulation data for post-mortem analysis. A prior interactions analysis was done to classify the system interactions. The results show that the algorithm was able to detect the rise of the flocking, i.e., emergence in the Boids model. Simulation results are provided to illustrate the effectiveness of the proposed approach.

The main purpose of this paper is to explore the influence of predation on the spread of a disease developed in the prey population where we assume that the prey has a social behavior. The memory of the prey and the predator measured by the time fractional derivative plays a crucial role in modeling the dynamical response in a predator–prey interaction. This memory can be modeled to articulate the involvement of interacting species by the presence of the time fractional derivative in the considered models. For the purpose of studying the complex dynamics generated by the presence of infection and the time-fractional-derivative we split our study into two cases. The first one is devoted to study the effect of a non-selective hunting on the spread of the disease, where the local stability of the equilibria is investigated. Further the backward bifurcation is obtained concerning basic reproduction rate of the infection. The second case is for explaining the impact of selecting the weakest infected prey on the edge of the herd by a predator on the prevalence of the infection, where the local behavior is scrutinized. Moreover, for the graphical representation part, a numerical simulation scheme has been achieved using the Caputo fractional derivative operator.

In this paper, a modified sinusoidal pulse width modulation (MSPWM) technique and a modified single-phase H-bridge seven-level inverter is proposed. The switching pulses for the proposed seven-level inverter are generated using a single triangular carrier waveform, a fully rectified sinusoidal signal, and three stepped reference signals (Uref1, Uref2 and Uref3). Using optimization technique, the magnitude of the stepped reference signal is determined so that the total harmonic distortion (THD) of the output voltage waveform is minimum and the fundamental component, RMS value of the voltage is improved for a given modulation index Ma as compared to the sinusoidal pulse width modulation (SPWM). By the implementation of the new scheme, the seven-level of the inverter output voltage level (+Vdc, +2Vdc/3, +Vdc/3, 0, −Vdc, −2Vdc/3, −Vdc) is obtained for any given modulation index. Similarly, if only two stepped reference signals are used then the inverter will act as a five-level inverter for any modulating index Ma. The proposed MSPWM and seven-level inverter are simulated on MATLAB/SIMULINK for R, R-L load and on a single-phase capacitor-start and capacitor-start-run Induction Motor.

Quickly matching the related primitive events for multiple complex events from the massive event streams usually faces with a great challenge due to the single-pattern characteristics of the existing complex event matching models. Aiming to solve the problem, a multiple-pattern complex event matching model based on merge sharing is proposed in this paper. The achievement of the paper lies in the fact that a multiple-pattern complex event matching model based on merge sharing is presented to successfully realize the quick matching of related primitive events for multiple complex events from the massive event streams. Specifically, in our scheme, we successfully use merge sharing technology to merge all the same prefixes, suffixes or subpatterns existing in single-pattern matching models into shared ones and to construct a multiple-pattern complex event matching model. As a result, our proposed matching model in this paper can effectively solve the above problem. The experimental results show that our proposed matching model in this paper outperforms the existing single-pattern matching models in model construction and related events matching for massive event streams.

The problem of decision-making when evaluating alternatives according to several quality criteria is considered. Information is used about the pairwise comparison of alternatives by criteria: how many times one alternative is preferable to the other. The criteria may have nonuniform scales. The method to form preferences matrices for representing numerical estimates of alternatives in attitude scales is proposed. The properties of the constructed relation are investigated. The algorithms for constructing the relation with the minimum distance from the preferences by criteria are developed. An algorithm for constructing an aggregated relation based on the summation of preferences by criteria is developed. Aggregate relation depends on the method of specifying the distance between the matrices of preferences. The proposed algorithms for constructing an aggregated relation can use coefficients of importance of criteria. The method can be applied in collective choice problems when assigning estimates to alternatives by experts. A comparison of the proposed algorithms with each other and with known decision-making methods is carried out. The software system of multi-criteria choice is developed. The task of choosing start-up projects for the purpose of investing by a venture fund has been solved.

In this paper, a mathematical model of a twin-inverted pendulum on a moving cart has been derived. This is done using the Lagrange–Euler method and, hence, a highly nonlinear mathematical model is resulted from this derivation. These nonlinear and unstable dynamics are written in a simple matrix form. For this challenging system, we use two types of efficient control approaches to treat the control problem of the twin inverted pendulum, namely, linear quadratic regulator (LQR) and nonlinear model predictive control (NMPC). Simulations with several scenarios are also presented to demonstrate the control performances and the model validity.

With technology scaling, stability, power dissipation, and device variability, the impact of process, voltage and temperature (PVT) variations has become dominant for static random access memory (SRAM) analysis for productivity and failure. In this paper, ten-transistors (10T) and low power eight-transistors SRAM cells are redesigned using floating-gate MOS transistors (FGMOS). Power centric parameters viz. read power, write power, hold power and delay are the performance analysis metrics. Further, the stochastic parameter variation to study the variability tolerance of the redesigned cell, PVT variations and Monte Carlo simulations have been carried out for 10T FGMOS SRAM cell. Stability has been illustrated with the conventional butterfly method giving read static noise margin (RSNM) and write static noise margin (WSNM) metrics for read stability and write ability, respectively. A comparative analysis with standard six-transistor SRAM cell is carried out. HSPICE simulative analysis has been carried out for 32nm technology node. The redesigned FGMOS SRAM cells provide improved performance. Also, these are robust and reliability efficient with comparable stability.

In this paper, by reshaping the hyperbolic secant distribution using Hermite polynomial, we devise a polynomially-modified hyperbolic secant distribution which is more flexible than secant distribution to capture the skewness, heavy-tailedness and kurtosis of data. As a portfolio possibly consists of multiple assets, the distribution of the sum of independent polynomially-modified hyperbolic secant random variables is derived. In exceptional cases, we evaluate risk measures such as value at risk and expected shortfall (ES) for the sum of two independent polynomially-modified hyperbolic secant random variables. Finally, using real datasets from four international computers stocks, such as Adobe Systems, Microsoft, Nvidia and Symantec Corporations, the effectiveness of the proposed model is shown by the goodness of Gram–Charlier-like expansion of hyperbolic secant law, for performance of value at risk and ES estimation, both in and out of the sample period.

In this work, we use a Predictor–Corrector method to implement and derive an iterative solution of an existing Tuberculosis (TB) model with two fractional derivatives, namely, Caputo–Fabrizio fractional derivative and the new generalized Caputo fractional derivative. We begin by recalling some existing results such as the basic reproduction number ${{ℛ}}_0$ and the equilibrium points of the model. Then, we study the global asymptotic stability of disease-free equilibrium of the fractional models. We also prove, for each fractional model, the existence and uniqueness of solutions. An iterative solution of the two models is computed using the Predictor–Corrector method. Using realistic parameter values, we perform numerical simulations for different values of the fractional order. Simulation results permit to conclude that the new generalized Caputo fractional derivative provides a more realistic analysis than the Caputo–Fabrizio fractional derivative and the classical integer-order TB model.