by Nicola Bellomo, Luigi Preziosi, Antonio Romano.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Boston, MA :
Name of Publisher, Distributor, etc.
Imprint: Birkhäuser,
Date of Publication, Distribution, etc.
2000.
SERIES
Series Title
Modeling and Simulation in Science, Engineering and Technology,
ISSN of Series
2164-3679
CONTENTS NOTE
Text of Note
I Mathematical Methods for Differential Equations -- 1 Models and Differential Equations -- 2 Models and Mathematical Problems -- 3 Stability and Perturbation Methods -- II Mathematical Methods of Classical Mechanics -- 4 Newtonian Dynamics -- 5 Rigid Body Dynamics -- 6 Energy Methods and Lagrangian Mechanics -- III Bifurcations, Chaotic Dynamics, Stochastic Models, and Discretization of Continuous Models -- 7 Deterministic and Stochastic Models in Applied Sciences -- 8 Chaotic Dynamics, Stability, and Bifurcations -- 9 Discrete Models of Continuous Systems -- Appendix I. Numerical Methods for Ordinary Differential Equations -- 1 Introduction -- 2 Numerical Methods for Initial-Value Problems -- 3 Numerical Methods for Boundary-Value Problems -- Appendix II. Kinematics, Applied Forces, Momentum and Mechanical Energy -- 1 Introduction -- 2 Systems of Applied Forces -- 3 Fundamental of Kinematics -- 4 Center of Mass -- 5 Tensor of Inertia -- 6 Linear Momentum -- 7 Angular Momentum -- 8 Kinetic Energy -- Appendix III. Scientific Programs -- 1 Introduction to Programming -- 2 Scientific Programs -- References.
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SUMMARY OR ABSTRACT
Text of Note
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.