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The seventh edition of Chapra and Canale's Numerical Methods for Engineers retains the instructional techniques that have made the text so successful. Chapra and Canale's unique approach opens each part of the text with sections called "Motivation," "Mathematical Background," and "Orientation". 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" and "Getting Started with Mathcad" which make excellent references. Numerous new or revised problems are drawn from actual engineering practice. The expanded breadth of engineering disciplines covered is especially evident in these exercises, which now cover such areas as biotechnology and biomedical engineering. Excellent new examples and case studies span all areas of engineering giving students a broad exposure to various fields in engineering. Users will find use of files for many popular software packages, specifically MATLAB[registered], Excel[registered] with VBA, and Mathcad[registered]. There is also material on developing MATLAB[registered] m-files and VBA macros.

Steven C. Chapra (Medford, MA) is Professor of Civil and Environmental Engineering, Tufts University. Retired

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
Appendix C Getting Starte dwith Mathcad Bibliography
Index
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