François E. Cellier, Jurgen Greifeneder

Continuous System Modeling (eBook, PDF)

• Format: PDF

Produktbeschreibung

Modeling and Simulation have become endeavors central to all disciplines of science and engineering. They are used in the analysis of physical systems where they help us gain a better understanding of the functioning of our physical world. They are also important to the design of new engineering systems where they enable us to predict the behavior of a system before it is ever actually built. Modeling and simulation are the only techniques available that allow us to analyze arbitrarily non-linear systems accurately and under varying experimental conditions. Continuous System Modeling introduces the student to an important subclass of these techniques. They deal with the analysis of systems described through a set of ordinary or partial differential equations or through a set of difference equations. This volume introduces concepts of modeling physical systems through a set of differential and/or difference equations. The purpose is twofold: it enhances the scientific understanding of our physical world by codifying (organizing) knowledge about this world, and it supports engineering design by allowing us to assess the consequences of a particular design alternative before it is actually built. This text has a flavor of the mathematical discipline of dynamical systems, and is strongly oriented towards Newtonian physical science.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 756
• Erscheinungstermin: 14. März 2013
• Englisch
• ISBN-13: 9781475739220
• Artikelnr.: 43988520

Inhaltsangabe

1 Introduction, Scope, and Definitions.- 2 Basic Principles of Continuous System Modeling.- 3 Principles of Passive Electrical Circuit Modeling.- 4 Principles of Planar Mechanical System Modeling.- 5 Hierarchical Modular Modeling of Continuous Systems.- 6 Principles of Active Electrical Circuit Modeling.- 7 Bond Graph Modeling.- 8 Modeling in Nonequilibrium Thermodynamics.- 9 Modeling Chemical Reaction Kinetics.- 10 Population Dynamics Modeling.- 11 System Dynamics.- 12 Naïve Physics.- 13 Inductive Reasoning.- 14 Artificial Neural Networks and Genetic Algorithms.- 15 Automated Model Synthesis.