International Journal of Modeling, Simulation, and Scientific Computing

In this paper, 188 definitions of aware, awareness, conscious, and consciousness, classified in different categories including cognitive science, computation, medicine, neurology, and philosophy, are reviewed. Based on this systematic review, desirable features of computationally aware systems (CASs) are gleaned and reported. A discussion about the relevance of computational awareness to advanced simulation is also outlined.

This paper presents a discrete event simulation model to help improving healthcare service provided by an emergency department at a private hospital at Zagazig, Egypt. We construct a patient flow division model by dividing patients according to their severity level. Although patients division and routing have significant evidence in improving health service in terms of waiting times and Length of Stay (LoS), there is a lack in a detailed system evaluation and implementation under this configuration. Based on system observation and health care provider’s interviews, a comprehensive and clear picture of the system has been drawn along with a conceptual model showing different patient flows through the studied system. A discrete event simulation model of the Emergency Department is built using collected data. Different operational scenarios were tested against the baseline scenario to study the impact of patient flow division, including different staff capacities and different patient magnitudes. Results indicate that waiting times and length of patient stay can be significantly improved under the proposed system configuration.

Copper pyrometallurgy has been holding a special place in the copper smelting industry. However, it is hard to explore the effect of parameters on production effectively due to the inoperable practice in the factory. The physical and chemical changes during the metallurgical process of copper smelting are also too complex to be observed. Therefore, we designed and built a virtual factory for copper pyrometallurgy, copper pyrometallurgy virtual simulation system (CPVSS), to simulate the copper smelting plant. The entire technical routes, system function, the main productive principle, technological process, and conditional tests were fully simulated in the CPVSS. It also provided a solution for the observation of internal phenomena in this paper. Moreover, sample computations were provided in this paper to illustrate the parameter simulation of the smelting process. A novel interactive experimental model was also constructed with virtual simulation technology and network multimedia technology, which provides powerful support for copper pyrometallurgy learning.

In this paper, we modeled a prey–predator system with interference among predators using the Crowley–Martin functional response. The local stability and existence of Hopf bifurcation at the coexistence equilibrium of the system in the absence of diffusion are analyzed. Further, the stability of bifurcating periodic solutions is investigated. We derived the conditions for which nontrivial equilibrium is globally asymptotically stable. In addition, we study the diffusion driven instability, Hopf bifurcation of the corresponding diffusion system with zero flux boundary conditions and the Turing instability region regarding parameters are established. The stability and direction of Hopf bifurcation are determined by applying the normal form theory and the center manifold theorem. Numerical simulations are performed to illustrate the theoretical results.

In this paper, a method is proposed to deal with factors affecting the fuzzy time series forecasting. A new fuzzification process is used by considering all the fuzzy sets with nonzero membership values corresponding to the data points. A strong alpha-cut based method is presented to select appropriate fuzzy logical relationships that carry importance in analyzing the trend of time series. Further, a unique defuzzification approach based on weights is proposed to get crisp variation. This obtained variation is finally converted to the forecasted value. The presented method is tested on the benchmark enrolment dataset of Alabama University and seven datasets of the Taiwan Capitalization Weighted Stock Index. On comparing the results, it is observed that the presented method performs better than the existing methods. Also, the statistical measures indicate the good forecasting results of the presented method.

The modeling and simulation of sea clutter are important in detecting radar targets in sea backgrounds. Because the nonstationary property of sea clutter is ignored in traditional statistical models, a new method based on measured sea clutter is proposed in this paper. First, we convert the measured sea clutter data under different sea conditions [$xI,xQ$] into real amplitude $S_M$. Instantaneous phase $𝜃$ is then extracted from the coherent radar’s baseband data. Second, we select a candidate statistic model and estimate its parameters based on $S_M$ by utilizing maximum likelihood estimation. Finally, we generate random series $A$ using corresponding random data generator and then add instantaneous phase $𝜃$ into $A$, i.e., $y=A{e}^{j𝜃}$, to obtain simulated sea clutter series. Through a comparison of simulated sea clutter and measured sea clutter data via histogram, the validity of the proposed method is proved.

The modeling of the controller for quasi Z-Source Cascaded Multilevel Inverter (qZS-CMI)-dependent 3-phase grid-tie Photovoltaic (PV) power system is considered in this paper. The state-of-the-art controller requires precise conceptual models and sophisticated optimization principles based on the derived models. However, such processes are limited to known system models, which are uncertain in future systems. Here, the controller for 3-phase qZS-CMI is modeled based on two phases, and the source PV voltage and output grid current are controlled. In Phase I, optimized Proportional Integral (PI) controller is used for finding out the total PV voltage, and Phase II utilizes the optimized Proportional Resonant (PR) controller enabled with the Artificial Neural Network (ANN) for controlling the grid current. For two phases, the modified optimization algorithm called Fitness Enabled-Rider Optimization Algorithm (FE-ROA) is used. Moreover, in Phase II, ANN is trained in an offline mode with the exact dataset arranged by the proposed FE-ROA, and it guarantees the control of grid current. The two phases plan to optimize the gain of both PI and PR controllers respectively using the same proposed algorithm. The main objective of phase I is to lessen the error among the reference PV voltage, and measured voltage, and phase II is to lessen the error among the reference and measured grid current. Hence, the grid-tie current injection is achieved by the developed module, and system-level control offers independent Maximum Power Point Tracking (MPPT). Lastly, the performance of the proposed controller for qZS-CMI is compared over the other controllers and substantiates the efficacy of the proposed one.

Engineering optimization problems can be always classified into two main categories including the linear programming (LP) and nonlinear programming (NLP) problems. Each programming problem further involves the unconstrained conditions and constrained conditions for design variables of the optimized system. This paper will focus on the issue about the design problem of NLP with the constrained conditions. The employed method for such NLP problems is a variant of particle swarm optimization (PSO), named improved particle swarm optimization (IPSO). The developed IPSO is to modify the velocity updating formula of the algorithm to enhance the search ability for given optimization problems. In this work, many different kinds of physical engineering optimization problems are examined and solved via the proposed IPSO algorithm. Simulation results compared with various optimization methods reported in the literature will show the effectiveness and feasibility for solving NLP problems with the constrained conditions.

Porous fiber materials are the most widely used acoustic absorption materials at present, and they have excellent acoustic absorption performance. This paper uses the finite element method to explore the factors affecting the acoustic absorption performance of porous fiber materials, including flow resistance, thickness of the porous fiber material, incidence angle, and back cavity thickness. Due to the complex acoustic absorption mechanism of porous fiber materials, an equivalent fluid model is used to simulate the acoustic absorption properties of the porous fiber materials. The correlation of acoustic absorption performance and the model of the back cavity was analyzed. An impedance tube test was implemented to verify the simulation results.

In geotechnical engineering, modeling geo-structures is challenging, particularly in cases where the interaction between the structures and soil or rock is complex. Most well-known commercial modeling software is based on homogenous and isotropic materials. However, soil and rock are often modeled in heterogeneous and anisotropic media because of the inherent anisotropy of sedimentary rock masses and their stratified structure. In recent decades, coupled hydro-mechanical (HM) interactions in isotropic porous media have been studied; however, the behavior of transversely isotropic porous media is rarely considered. In addition, it is difficult for commercial software such as Plaxis and Flac3D to express complex rock formation where the anisotropy of the material and the associated cracks and fractures could be assembled into a single model. In this study, a finite element implementation using Differential Equation Analysis Library (DEAL.II), an open-source library of finite element codes, was developed to model the fully coupled HM behavior of transversely isotropic porous media. The proposed implementation can be applied to both isotropic and transversely isotropic porous media based on Biot’s theory. The developed code can be used to model poroelastic media with (1) equations of linear elasticity for the solid matrix and (2) diffusion equations for fluid flow based on mass and linear-momentum conservation laws. We verified the performance and accuracy of the code through two examples, i.e., Mandel’s problem with a compared analytical solution and a tunnel excavation process with the Flac3D software. On the basis of these numerical applications, we present the code to model the behavior of various geo-structures such as tunnels and pile–soil interactions with anisotropic materials.

In this paper, we propose and analyze a fractional-order SIS epidemic model with the saturated treatment and disease transmission. The existence and uniqueness, nonnegativity and finiteness of solutions for our suggested model have been studied. Different equilibria of the model are found and their local and global stability analyses are also examined. Furthermore, the conditions for fractional backward and fractional Hopf bifurcation are also analyzed in both the commensurate and incommensurate fractional-order model. We study how the control parameter and the order of the fractional derivative play role in local as well as global stability of equilibrium points and Hopf bifurcation. We have demonstrated the analytical results of our proposed model system through several numerical simulations.

In this paper, a second-order singularly perturbed differential-difference equation involving mixed shifts is considered. At first, through Taylor series approximation, the original model is reduced to an equivalent singularly perturbed differential equation. Then, the model is treated by using the hybrid finite difference scheme on different types of layer adapted meshes like Shishkin mesh, Bakhvalov–Shishkin mesh and Vulanović mesh. Here, the hybrid scheme consists of a cubic spline approximation in the fine mesh region and a midpoint upwind scheme in the coarse mesh region. The error analysis is carried out and it is shown that the proposed scheme is of second-order convergence irrespective of the perturbation parameter. To display the efficacy and accuracy of the proposed scheme, some numerical experiments are presented which support the theoretical results.

In this paper, we have considered the multi-dimensional space fractional diffusion equations with variable coefficients. The fractional operators (derivative/integral) are used based on the Caputo definition. This study provides an analytical approach to determine the analytical solution of the considered problems with the help of the two-step Adomian decomposition method (TSADM). Moreover, new results have been obtained for the existence and uniqueness of a solution by using the Banach contraction principle and a fixed point theorem. We have extended the dimension of the space fractional diffusion equations with variable coefficients into multi-dimensions. Finally, the generalized problems with two different types of the forcing term have been included demonstrating the applicability and high efficiency of the TSADM in comparison to other existing numerical methods. The diffusion coefficients do not require to satisfy any certain conditions/restrictions for using the TSADM. There are no restrictions imposed on the problems for diffusion coefficients, and a similar procedures of the TSADM has followed to the obtained analytical solution for the multi-dimensional space fractional diffusion equations with variable coefficients.