Modeling and simulation

About: Modeling and simulation is a research topic. Over the lifetime, 10273 publications have been published within this topic receiving 111550 citations.

Modeling and simulation of ion transport in dielectric liquids - Fundamentals and review

Abstract: This review paper introduces fundamental knowledge about and presents recent developments in modeling and simulation of ion transport and electrohydrodynamic flow in dielectric liquids. Starting with the formulation of the governing equations, we introduce background ideas as well as the related modeling of ion dissociation, recombination, injection, and discharge, which play key roles in the charge creation and transport problem. Numerical methods and solutions are then presented for the onedimensional problem over the domain between a pair of parallel electrodes. In particular, we show how the electrical properties of a nonpolar liquid, m-xylene, can be derived from the matching of the numerical solutions with Novotny's experimental data. Two asymptotic solution methods, one for the overlap-layer and the other for the thin-layer regimes, are then presented; in particular, we show a remarkably high accuracy for the solutions. The current-voltage relation with ion dissociation and recombination is shown to be completely different from that without them. A historical review of the modeling and simulation of ion transport and electrohydrodynamic flow is finally touched upon.

SeSAm: implementation of agent-based simulation using visual programming

Abstract: In this paper, we present the most important features of SeSAm, a modeling and simulation platform for multi-agent simulations. Based on a declarative, explicit model representation and visual programming, it allows implementing models on specification level. Optimizing compilation allows efficient simulation of the explicit model representation. It was successfully applied in different areas, like biology, traffic or logistics simulation.

Using simulation to analyze supply chains

Abstract: Supply Chain management, the management of the flow of goods or services from materials stage to the end user, is a complex process because of the level of uncertainty at each stage of the supply chain. Computer simulation, because it can be applied to operational problems that are too difficult to model and solve analytically, is an especially effective tool to help analyze supply chain logistical issues.While most engineers have had some exposure to the tools and technology of computer modeling and simulation, the use of simulation for supply chain analysis has not been prevalent until recently. The software tool, Supply Solver, was developed in an effort to provide supply chain solutions using simulation as the foundation. In this paper, the goal will be to show how discrete-event simulation is used to analyze supply chain processes. This paper will also demonstrate what some of the considerations are in using Supply Solver to help solve supply chain design problems.

Modeling and Simulation-Based Systems Engineering Handbook

Abstract: NASA Centers. Aerospace Companies, and Modeling and Simulation Tool Providers Survey of Model Based Systems Engineering Methodologies (6), (7). – e.g. INCOSE (16) INCOSE Systems Engineering Handbook, v. 3.2.2, October. Modeling and Simulation-Based Systems Engineering Handbook. Citation Information. Modeling and Simulation-Based Systems Engineering Handbook. Commercial Modeling and Simulation Tool Providers INCOSE Systems Engineering Handbook (7) CubeSat Mission Design Based on Systems.

The role of bond graph modeling and simulation in mechatronics systems: An integrated software tool: CAMP-G, MATLAB–SIMULINK

Abstract: One of the main and most challenging steps in the design and analysis of a mechatronics system is to generate a computer model. This paper explores the fundamental theory, the methodology and the process from conceptual ideas to practical realization. Using a multienergetic approach that allows the modeling of interdisciplinary models, it explores the theory and method to automate the process of the generation of the differential equations and how to automate the derivation of transfer functions. The approach is discussed for linear and non-linear systems. The generation of a computer model takes new dimensions when that model contains mixed energy domains such as electromechanical, electrohydraulic, thermo-fluid, and electronic control systems all together. These are typical of mechatronics applications. This paper explores the bond graph technique as a modeling tool to generate state space models or non-linear models together with software tools. CAMP-G (Computer Aided Modeling Program with Graphical input) has been developed in order to generate computer models automatically and have them integrated with MATLAB–SIMULINK as simulation tools. Several aspects of mechatronics systems design have been investigated in order to focus on which areas the bond graph modeling technique can help engineers in the process of creating mechatronics systems from scratch. Towards this end, the paper deals with computer-generated models of sensors, actuators, and multidisciplinary complex physical systems.