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 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®, Excel® with VBA and Mathcad®. This includes material on developing MATLAB® m-files and VBA macros.

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  • 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
  • Citation

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