Large Time Asymptotics for Solutions of Nonlinear Partial Differential Equations - Hardcover

by P. L. Sachdev (Author), Ch Srinivasa Rao (Author)

A large number of physical phenomena are modeled by nonlinear partial

differential equations, subject to appropriate initial/ boundary conditions; these

equations, in general, do not admit exact solution. The present monograph gives

constructive mathematical techniques which bring out large time behavior of

solutions of these model equations. These approaches, in conjunction with modern

computational methods, help solve physical problems in a satisfactory manner. The

asymptotic methods dealt with here include self-similarity, balancing argument,

and matched asymptotic expansions. The physical models discussed in some detail

here relate to porous media equation, heat equation with absorption, generalized

Fisher's equation, Burgers equation and its generalizations. A chapter each is

devoted to nonlinear diffusion and fluid mechanics. The present book will be found

useful by applied mathematicians, physicists, engineers and biologists, and would

considerably help understand diverse natural phenomena.

Back Jacket

A large number of physical phenomena are modeled by nonlinear partial differential equations, subject to appropriate initial/ boundary conditions; these equations, in general, do not admit exact solution. The present monograph gives constructive mathematical techniques which bring out large time behavior of solutions of these model equations. These approaches, in conjunction with modern computational methods, help solve physical problems in a satisfactory manner.

The asymptotic methods dealt with here include self-similarity, balancing argument, and matched asymptotic expansions. The physical models discussed in some detail here relate to porous media equation, heat equation with absorption, generalized Fisher's equation, Burgers equation and its generalizations.

A chapter each is devoted to nonlinear diffusion and fluid mechanics. The present book will be found useful by applied mathematicians, physicists, engineers and biologists, and would considerably help understand diverse natural phenomena.