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Engineers require a solid knowledge of the relationship between engineering applications and underlying mathematical theory. However, most books do not present sufficient theory, or they do not fully explain its importance and relevance in understanding those applications.
Advanced Engineering Mathematics with Modeling Applications employs a balanced approach to address this informational void, providing a solid comprehension of mathematical theory that will enhance understanding of applications – and vice versa. With a focus on modeling, this book illustrates why mathematical methods work, when they apply, and what their limitations are. Designed specifically for use in graduate-level courses, this book:
Emphasizes mathematical modeling, dimensional analysis, scaling, and their application to macroscale and nanoscale problems
Explores eigenvalue problems for discrete and continuous systems and many applications
Develops and applies approximate methods, such as Rayleigh-Ritz and finite element methods
Presents applications that use contemporary research in areas such as nanotechnology
Apply the Same Theory to Vastly Different Physical Problems
Presenting mathematical theory at an understandable level, this text explores topics from real and functional analysis, such as vector spaces, inner products, norms, and linear operators, to formulate mathematical models of engineering problems for both discrete and continuous systems. The author presents theorems and proofs, but without the full detail found in mathematical books, so that development of the theory does not obscure its application to engineering problems. He applies principles and theorems of linear algebra to derive solutions, including proofs of theorems when they are instructive. Tying mathematical theory to applications, this book provides engineering students with a strong foundation in mathematical terminology and methods.
Foundations of mathematical modeling
Engineering analysis
Conservation laws and mathematical modeling
Problem formulation
Nondimensionalization
Scaling
Linear algebra
Introduction
Three-dimensional space
Vector spaces
Linear independence
Basis and dimension
Inner products
Norms
Gram-Schmidt orthonormalization
Orthogonal expansions
Linear operators
Adjoint operators
Positive definite operators
Energy inner products
Ordinary differential equations
Linear differential equations
General theory for second-order differential equations
Differential equations with constant coefficients
Differential equations with variable coefficients
Singular points of second-order equations
Bessel functions
Differential equations whose solutions are expressible in terms of Bessel functions
Legendre functions
Variational methods
Introduction
The general variational problem
Variational solutions of operator equations
Finite-element method
Galerkin’s method
Eigenvalue problems
Eigenvalue and eigenvector problems
Eigenvalues of adjoint operators
Eigenvalues of positive definite operators
Eigenvalue problems for operators in finite-dimensional vector spaces
Second-order differential operators
Eigenvector expansions
Fourth-order differential operators
Differential operators with eigenvalues in boundary conditions
Eigenvalue problems involving Bessel functions
Eigenvalue problems in other infinite-dimensional vector spaces
Solvability conditions
Asymptotic approximations to solutions of eigenvalue problems
Rayleigh’s quotient
Rayleigh-Ritz method
Green’s functions
Partial differential equations
Homogeneous partial differential equations
Second-order steady-state problems, Laplace’s equation
Time-dependent problems: Initial value problems
Nonhomogeneous partial differential equations
Problems in cylindrical coordinates
Problems in spherical coordinates
Index