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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Autorentext

Bouchra Aylaj is an Associate Professor with Habilitation in mathematics at University of Hassan II of Casablanca, Faculty Ain Chock, Morocco. She started her career in 2006 when she was called to develop a research program on mathematical modelling in biology. Her scientific activity has been focused on the following topics: scientific computing and control for risk analysis and analytical and computational problems in epidemiology. Subsequently, she moved her scientific interests to the modeling and related safety problems focused on social behaviors in human crowds.Nicola Bellomo is a distinguished professor at the University of Granada and Professor Emeritus at the Polytechnic University of Torino. He started his career in 1980 when he was called to cover the chair of mathematical physics and applied mathematics due to his scientific achievements on the mathematical theory of the Boltzmann equation and of stochastic differential equations. Subsequently, he moved his scientificinterests to the study of living systems, becoming one of the pioneers of the development of active particles methods to the modeling of large systems of self-propelled interacting entities. He is author of two books published by Birkhauser devoted to this topic. In 2009, he delivered the prestigious Shank Lecture on the modeling of immune competition, and was awarded the "Third Level Honor" in 2016 for scientific merits by the President of the Italian Republic.Livio Gibelli is a Lecturer in Mechanical Engineering at the University of Edinburgh. He received his Ph.D. in applied mathematics from the Politecnico di Milano and, prior to the current position, he worked as Research Fellow at the University of Warwick, Politecnico di Milano, Politecnico di Torino, and University of British Columbia. His main research interests include non-equilibrium multiphase fluid flows, the continuum description of slightly rarefied gases, the numerical methods for solving kinetic equations,and the modeling of crowd dynamics.Damian Knopoff is a chemical engineer and mathematician, holding a Ph.D. in Mathematics from Cordoba National University. Currently, he is an Associate Researcher at the Argentinian Scientific and Technical Research Council. His main research fields include nonlinear dynamical systems and numerical methods for differential equations with applications to the modeling and simulation of complex living systems, including biological phenomena, socio-economic systems, and crowd dynamics.

Inhalt
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.