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Summary
Summary
Instructors love "Numerical Methods for Engineers" because it makes teaching easy Students love it because it is written for them--with clear explanations and examples throughout. The text features a broad array of applications that span all engineering disciplines.
The sixth edition retains the successful instructional techniques of earlier editions. Chapra and Canale's unique approach opens each part of the text with sections called Motivation, Mathematical Background, and Orientation. This prepares the student for upcoming problems in a motivating and engaging manner. Each part closes with an Epilogue containing Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more advanced methods. Helpful separate Appendices. "Getting Started with MATLAB" abd "Getting Started with Mathcad" which make excellent references.
Numerous new or revised problems drawn from actual engineering practice, many of which are based on exciting new areas such as bioengineering. The expanded breadth of engineering disciplines covered is especially evident in the problems, which now cover such areas as biotechnology and biomedical engineering. Excellent new examples and case studies span asll areas of engineering disciplines; the students using this text will be able to apply their new skills to their chosen field.
Users will find use of software packages, specifically MATLAB(R), Excel(R) with VBA and Mathcad(R). This includes material on developing MATLAB(R) m-files and VBA macros.
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 |