Numerical Methods for Engineers
Edition: 6th 2010
List price: $239.67
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Description: Instructors loveNumerical Methods for Engineersbecause it 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. ..Approximately 20% of the problems are new or revised in 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, Excel with VBA and Mathcad. This includes material on developing MATLAB m-files and VBA macros. . . .
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All the information you need in one place! Each Study Brief is a summary of one specific subject; facts, figures, and explanations to help you learn faster.
List price: $239.67
Copyright year: 2010
Publisher: McGraw-Hill Higher Education
Publication date: 4/20/2009
Size: 8.25" wide x 9.25" long x 1.75" tall
Steven C. Chapra (Medford, MA) is Professor of Civil and Environmental Engineering, Tufts University.
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