Synopses & Reviews
The fifth edition of Numerical Methods for Engineers continues its tradition of excellence.
Instructors love this text because it is a comprehensive text that is easy to teach from. Students love it because it is written for them--with great pedagogy and clearexplanations and examples throughout. The text features a broad array of applications, including all engineering disciplines.
The revision retains the successful pedagogy of the prior editions. Chapra and Canale's unique approach opens each part of the text with sections called Motivation,Mathematical Background, and Orientation, preparing the student for what is to come in a motivating and engaging manner. Each part closes with an Epilogue containingsections called Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepensunderstanding of what has been learned and provides a peek into more advanced methods.
Approximately 80% of the end-of-chapter problems are revised or new to this edition. The expanded breadth of engineering disciplines covered is especially evident in the problems, which now cover such areas as biotechnology and biomedical engineering.
Users will find use of software packages, specifically MATLAB and Excel with VBA. This includes material on developing MATLAB m-files and VBA macros.
About the Author
Steven C. Chapra (Medford, MA) is Professor of Civil and Environmental Engineering, Tufts University. Retired
Table of Contents
Part 1 Modeling, Computers, and Error Analysis
1 Mathematical Modeling and Engineering Problem Solving
2 Programming and Software
3 Approximations and Round-Off Errors
4 Truncation Errors and the Taylor Series
Part 2 Roots of Equations
5 Bracketing Methods
6 Open Methods
7 Roots of Polynomials
8 Case Studies: Roots of Equations
Part 3 Linear Algebraic Equations
9 Gauss Elimination
10 LU Decomposition and Matrix Inversion
11 Special Matrices and Gauss-Seidel
12 Case Studies: Linear Algebraic Equations
Part 4 Optimization
13 One-Dimensional Unconstrained Optimization
14 Multidimensional Unconstrained Optimization
15 Constrained Optimization
16 Case Studies: Optimization
Part 5 Curve Fitting
17 Least-Squares Regression
18 Interpolation
19 Fourier Approximation
20 Case Studies: Curve Fitting
Part 6 Numerical Differentiation and Integration
21 Newton-Cotes Integration Formulas
22 Integration of Equations
23 Numerical Differentiation
24 Case Studies: Numerical Integration and Differentiation
Part 7 Ordinary Differential Equations
25 Runge-Kutta Methods
26 Stiffness and Multistep Methods
27 Boundary-Value and Eigenvalue Problems
28 Case Studies: Ordinary Differential Equations
Part 8 Partial Differential Equations
29 Finite Difference: Elliptic Equations
30 Finite Difference: Parabolic Equations
31 Finite-Element Method
32 Case Studies: Partial Differential Equations
Appendix A The Fourier Series
Appendix B Getting Started with Matlab
Bibliography
Index