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Numerical Methods for Engineers, 8th Edition

지은이

Steven Chapra, Raymond Canale

출간일

2021.02.18

레벨

중급

정가

45,000

총 결제 금액

45,000

적립 예정

1,350P

쪽수

1008쪽

ISBN

9781260571387

브랜드

한빛아카데미

본 도서는 연습문제 해답을 제공하지 않습니다.

Steve Chapra and Raymond Canale collaborated on the 1st edition of NUMERICAL METHODS FOR ENGINEERS published by McGraw-Hill in 1985. Now in its 8th edition, it is the most widely used text of this type by colleges and universities around the world and has been translated into 10 languages.

 

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.

 

▶ Hallmark Features of the Text

Theory is included in a practical way

As it provides insights into the strengths and shortcomings of the methods.

 

Emphasis on trade-offs among methods

This helps students understand that several methods are typically available to solve a particular mathematical problem and that there are trade-offs between methods (e.g., speed versus accuracy).

 

Student-oriented pedagogy

This book is written for the student, not the instructor. Features supporting this goal are the overall organisation, 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. The authors have also endeavoured to keep our explanations straightforward and practically oriented.

 

Strong emphasis on both programming and packages

This helps the authorsto apply numerical methods for problem solving. The authors empower students by helping them utilise the numerical problem-solving capabilities of packages like Excel, MATLAB, and Mathcad software. However, students are also shown how to develop simple, well-structured programs to extend the base capabilities of those environments.

 

Engineering and science examples, case studies, and end-of-chapter problems

Drawing from engineering and scientific problem-solving contexts this enlivens the student experience by 

emphasising how the methods will help them in practice.

 

▶ Overall Changes and New Topics

New and revised problems

Numerous new or revised end-of chapter problems and case studies are drawn from actual 

Engineering practice.

 

New, improved formulation for cubic splines

Easier to understand than the previous version and compatible with MATLAB algorithm.

 

Monte Carlo integration

Increasingly used in engineering and science.

 

Supplementary material on hyperbolic partial differential equations (PDEs)

Together with existing material on Elliptic & Parabolic PDEs, makes the part of the book on PDEs more complete.

 

▶ For Students & Instructors 

https://www.mheducation.com/highered/support.html

 

저자

목차

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 Started with Mathcad

Bibliography

Index

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