Numerical Methods for Engineers – Steven C. Chapra, Raymond P. Canale – 6th Edition


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 for upcoming in a motivating and engaging manner.

Each part closes with an Epilogue containing -Offs, Important Relationships and Formulas, and and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more . Helpful separate Appendices. “Getting Started with MATLAB” abd “Getting Started with Mathcad” which make excellent references.

Numerous new or revised problems drawn from actual , many of which are based on exciting new areas such as bioengineering. The expanded breadth of disciplines covered is especially evident in the problems, which now cover such areas as biotechnology and biomedical . Excellent new examples and case studies span asll areas of 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®, Excel® with VBA and Mathcad®. This includes material on developing MATLAB® 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
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