Description
McGraw Hill Numerical Methods for Engineers 8th Edition 2021 by Steven C. Chapra, Raymond P., Canale
Overview
The eighth edition of Chapra and Canale's ‘Numerical Methods for Engineers’ retains the instructional techniques that have made the text so successful The book covers the standard numerical methods employed by both students and practicing engineers Although relevant theory is covered the primary emphasis is on how the methods are applied for engineering problem solving Each part of the book includes a chapter devoted to case studies from the major engineering disciplines Numerous new or revised end of chapter problems and case studies are drawn from actual engineering practice This edition also includes several new topics including a new formulation for cubic splines Monte Carlo integration and supplementary material on hyperbolic partial differential equations.
Key Features
• Strong emphasis on both programming and packages to apply numerical methods for problem solving.
• Monte Carlo integration, increasingly used in engineering and science, has been added.
• New, improved formulation for cubic splines that is easier to understand & compatible with MATLAB algorithm
• Supplementary material on hyperbolic partial differential equations (PDEs) has been added
• Student oriented pedagogy Features supporting this goal are the overall organization, the use of introductions and
epilogues to consolidate major topics, the extensive use of worked examples and case studies from all areas of
engineering, and liberal use of figures to graphically illuminate concepts and theory.
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-KuttaMethods
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 Started with Mathcad
Bibliography
Index