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.

Minimum Information About a Simulation Experiment (MIASE)

Abstract: Reproducibility of experiments is a basic requirement for science. Minimum Information (MI) guidelines have proved a helpful means of enabling reuse of existing work in modern biology. The Minimum Information Required in the Annotation of Models (MIRIAM) guidelines promote the exchange and reuse of biochemical computational models. However, information about a model alone is not sufficient to enable its efficient reuse in a computational setting. Advanced numerical algorithms and complex modeling workflows used in modern computational biology make reproduction of simulations difficult. It is therefore essential to define the core information necessary to perform simulations of those models. The Minimum Information About a Simulation Experiment (MIASE, Glossary in Box 1) describes the minimal set of information that must be provided to make the description of a simulation experiment available to others. It includes the list of models to use and their modifications, all the simulation procedures to apply and in which order, the processing of the raw numerical results, and the description of the final output. MIASE allows for the reproduction of any simulation experiment. The provision of this information, along with a set of required models, guarantees that the simulation experiment represents the intention of the original authors. Following MIASE guidelines will thus improve the quality of scientific reporting, and will also allow collaborative, more distributed efforts in computational modeling and simulation of biological processes.

J-Sim: A Simulation Environment for Wireless Sensor Networks

Abstract: Wireless sensor networks (WSNs) have gained considerable attention in the past few years. As such, there has been an increasing need for defining and developing simulation frameworks for carrying out high-fidelity WSN simulation. In this paper, the authors presented a modeling and simulation framework for WSNs in J-Sim - an open-source, component-based compositional network simulation environment that is developed entirely in Java. This framework is built upon the autonomous component architecture (ACA) and the extensible internetworking framework (INET) of J-Sim, and provides an object-oriented definition of (i) target, sensor and sink nodes, (ii) sensor and wireless communication channels, and (iii) physical media such as seismic channels, mobility model and power model (both energy-producing and energy-consuming components). Application-specific models can be defined by sub-classing classes in the simulation framework and customizing their behaviors. The use of the proposed WSN simulation framework was demonstrated by implementing several well-known localization, geographic routing, and directed diffusion protocols. In addition, performance comparisons were performed (in terms of execution time incurred, and the memory used) in simulating several typical WSN scenarios in J-Sim and ns-2. The simulation study indicates that the proposed WSN simulation framework in J-Sim is much more scalable than ns-2 (especially in memory usage).

Modeling and Simulation of Systems Using MATLAB and Simulink

Abstract: Not only do modeling and simulation help provide a better understanding of how real-world systems function, they also enable us to predict system behavior before a system is actually built and analyze systems accurately under varying operating conditions. Modeling and Simulation of Systems Using MATLAB and Simulink provides comprehensive, state-of-the-art coverage of all the important aspects of modeling and simulating both physical and conceptual systems. Various real-life examples show how simulation plays a key role in understanding real-world systems. The author also explains how to effectively use MATLAB and Simulink software to successfully apply the modeling and simulation techniques presented. After introducing the underlying philosophy of systems, the book offers step-by-step procedures for modeling different types of systems using modeling techniques, such as the graph-theoretic approach, interpretive structural modeling, and system dynamics modeling. It then explores how simulation evolved from pre-computer days into the current science of today. The text also presents modern soft computing techniques, including artificial neural networks, fuzzy systems, and genetic algorithms, for modeling and simulating complex and nonlinear systems. The final chapter addresses discrete systems modeling. Preparing both undergraduate and graduate students for advanced modeling and simulation courses, this text helps them carry out effective simulation studies. In addition, graduate students should be able to comprehend and conduct simulation research after completing this book. AncillariesAccompanying CD-ROM includes simulation code in MATLAB and Simulink, enabling quick and useful insight into real-world systems. A solutions manual is available for qualifying instructors.

Review on Modeling and Simulation of Continuous Casting

Abstract: Continuous casting is a mature, sophisticated technological process, used to produce most of the world’s steel, so is worthy of fundamentally-based computational modeling. It involves many interacting phenomena including heat transfer, solidification, multiphase turbulent flow, clogging, electromagnetic effects, complex interfacial behavior, particle entrapment, thermal-mechanical distortion, stress, cracks, segregation, and microstructure formation. Furthermore, these phenomena are transient, three-dimensional, and operate over wide length and time scales. This paper reviews the current state of the art in modeling these phenomena, focusing on practical applications to the formation of defects. It emphasizes model verification and validation of model predictions. The models reviewed range from fast and simple for implementation into online model-based control systems to sophisticated multiphysics simulations that incorporate many coupled phenomena. Both the accomplishments and remaining challenges are discussed.

Modeling and Simulation of Single-Event Effects in Digital Devices and ICs

Abstract: This paper reviews the status of research in modeling and simulation of single-event effects (SEE) in digital devices and integrated circuits, with a special emphasis on the current challenges concerning the physical modeling of ultra-scaled devices (in the deca-nanometer range) and new device architectures (Silicon-on-insulator, multiple-gate, nanowire MOSFETs). After introducing the classification and the terminology used in this paper, we firstly present the basis of the different transport models used in device-level simulation (drift-diffusion, hydrodynamic, Monte-Carlo and some approximated and exact quantum-mechanical based approaches). We also focus on the main emerging physical phenomena affecting ultra-short MOSFETs (quantum effects, tunneling current, ballistic operation) and the methods envisaged for taking them into account at device simulation level. Several examples of device simulation are given at the end of this first part, including recent results on fully-depleted SOI and multiple-gate devices. In the second part, we briefly survey the different circuit-level modeling approaches (circuit-level simulation, Mixed-Mode, 3-D simulation of portions of circuits) of single-event effects in integrated circuits. The SEU in advanced SRAM and SEE mechanisms in logic circuits are reminded. The production and propagation of digital single-event transients (DSETs) in sequential and combinational logic, as well as the soft error rate trends with scaling are particularly addressed. Recent bibliographical examples of simulation in SRAMs and logic circuits are presented and discussed to illustrate these topics at circuit-level.