9781461271017-1461271010-Mechanics and Dynamical Systems with Mathematica® (Modeling and Simulation in Science, Engineering and Technology)

Mechanics and Dynamical Systems with Mathematica® (Modeling and Simulation in Science, Engineering and Technology)

ISBN-13: 9781461271017
ISBN-10: 1461271010
Edition: Softcover reprint of the original 1st ed. 2000
Author: Antonio Romano, Nicola Bellomo, Luigi Preziosi
Publication date: 2012
Publisher: Birkhäuser
Format: Paperback 432 pages
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Book details

ISBN-13: 9781461271017
ISBN-10: 1461271010
Edition: Softcover reprint of the original 1st ed. 2000
Author: Antonio Romano, Nicola Bellomo, Luigi Preziosi
Publication date: 2012
Publisher: Birkhäuser
Format: Paperback 432 pages

Summary

Mechanics and Dynamical Systems with Mathematica® (Modeling and Simulation in Science, Engineering and Technology) (ISBN-13: 9781461271017 and ISBN-10: 1461271010), written by authors Antonio Romano, Nicola Bellomo, Luigi Preziosi, was published by Birkhäuser in 2012. With an overall rating of 3.9 stars, it's a notable title among other books. You can easily purchase or rent Mechanics and Dynamical Systems with Mathematica® (Modeling and Simulation in Science, Engineering and Technology) (Paperback) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Modeling and Applied Mathematics Modeling the behavior of real physical systems by suitable evolution equa tions is a relevant, maybe the fundamental, aspect of the interactions be tween mathematics and applied sciences. Modeling is, however, only the first step toward the mathematical description and simulation of systems belonging to real world. Indeed, once the evolution equation is proposed, one has to deal with mathematical problems and develop suitable simula tions to provide the description of the real system according to the model. Within this framework, one has an evolution equation and the re lated mathematical problems obtained by adding all necessary conditions for their solution. Then, a qualitative analysis should be developed: this means proof of existence of solutions and analysis of their qualitative be havior. Asymptotic analysis may include a detailed description of stability properties. Quantitative analysis, based upon the application ofsuitable methods and algorithms for the solution of problems, ends up with the simulation that is the representation of the dependent variable versus the independent one. The information obtained by the model has to be compared with those deriving from the experimental observation of the real system. This comparison may finally lead to the validation of the model followed by its application and, maybe, further generalization.

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