By Peter A. Markowich

ISBN-10: 3540346457

ISBN-13: 9783540346456

This publication provides chosen themes in technological know-how and engineering from an applied-mathematics standpoint. The defined usual, socioeconomic, and engineering phenomena are modeled by means of partial differential equations that relate kingdom variables comparable to mass, pace, and effort to their spatial and temporal diversifications. ordinarily, those equations are hugely nonlinear; in lots of circumstances they're platforms, and so they signify demanding situations even for the main sleek and complicated mathematical and numerical-analytic strategies. the chosen issues mirror the longtime clinical pursuits of the writer. They contain flows of fluids and gases, granular-material flows, organic methods akin to development formation on animal skins, kinetics of rarified gases, loose obstacles, semiconductor units, and socioeconomic methods. each one subject is in brief brought in its medical or engineering context, by means of a presentation of the mathematical versions within the kind of partial differential equations with a dialogue in their uncomplicated mathematical houses. the writer illustrates each one bankruptcy by means of a sequence of his personal fine quality images, which display that partial differential equations are strong instruments for modeling a wide number of phenomena influencing our day-by-day lives.

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**Extra resources for Applied Partial Differential Equations: A Visual Approach**

**Sample text**

6 Turbulent flows14 are charcacterized by seemingly chaotic, random changes of velocities, with vortices appearing on a variety of scales, occurring at sufficiently large Reynolds number15 . Non-turbulent flows are called laminar, represented by streamline flow, where different layers of the fluid are not disturbed by scale interaction. Simulations of turbulent flows are highly complicated and expensive since small and large scales in the solutions of the Navier–Stokes equations have to be resolved contemporarily.

Patlak [7] and then in 1970 by E. A. Segel [4]. Meanwhile, this so called Keller–Segel model has become one of the most well analyzed systems of partial differential equations in mathematical biology, giving many insights into cell biology as well as into the analysis of nonlinear partial differential equations. The main unknowns of the Keller–Segel system are the nonnegative cell density r = r(x, t) and the chemical concentration S = S(x, t), where x denotes the one, two or three dimensional space variable and t > 0 the time variable.

E. grad Z has to be small. Clearly, this restricts the applicability of the model, in particular its use for waterfall modelling. Recently, an extension of the Saint–Venant system was presented in [1], which eliminates all assumptions on the bottom topography. There the curvature of the river bottom is taken into account explicitely in the derivation from the hydrostatic Euler system (assuming a small fluid velocity in orthogonal direction to the fluid bottom). We remark that extensions of the Saint–Venant models to granular flows (like debris avalanches) exist in the literature, see also [1].

### Applied Partial Differential Equations: A Visual Approach by Peter A. Markowich

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