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E-grāmata: Numerical Methods for Nonlinear Engineering Models

  • Formāts: PDF+DRM
  • Izdošanas datums: 24-Mar-2009
  • Izdevniecība: Springer-Verlag New York Inc.
  • Valoda: eng
  • ISBN-13: 9781402099205
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  • Formāts: PDF+DRM
  • Izdošanas datums: 24-Mar-2009
  • Izdevniecība: Springer-Verlag New York Inc.
  • Valoda: eng
  • ISBN-13: 9781402099205

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This book develops and illustrates some numerical computer-based methods that can be used for engineering models and equations. It emphasizes nonlinear engineering models and provides detailed discussion of computer algorithms for solving nonlinear problems.



There are many books on the use of numerical methods for solving engineering problems and for modeling of engineering artifacts. In addition there are many styles of such presentations ranging from books with a major emphasis on theory to books with an emphasis on applications. The purpose of this book is hopefully to present a somewhat different approach to the use of numerical methods for - gineering applications. Engineering models are in general nonlinear models where the response of some appropriate engineering variable depends in a nonlinear manner on the - plication of some independent parameter. It is certainly true that for many types of engineering models it is sufficient to approximate the real physical world by some linear model. However, when engineering environments are pushed to - treme conditions, nonlinear effects are always encountered. It is also such - treme conditions that are of major importance in determining the reliability or failure limits of engineering systems. Hence it is essential than engineers have a toolbox of modeling techniques that can be used to model nonlinear engineering systems. Such a set of basic numerical methods is the topic of this book. For each subject area treated, nonlinear models are incorporated into the discussion from the very beginning and linear models are simply treated as special cases of more general nonlinear models. This is a basic and fundamental difference in this book from most books on numerical methods.

Recenzijas

From the reviews:

This voluminous book by Hauser covers numerical topics ranging from roots of nonlinear equations to introductory finite element method. The advantage of this work lies in the authors approach of show-and-tell or learning by example. The examples are almost exclusively in the area of nonlinear electronics which may be quite advantageous for electronics engineers. Summing Up: Recommended. Upper-division undergraduate through professional collections. (R. N. Laoulache, Choice, Vol. 47 (3), November, 2009)

The book represents a comprehensive guide for the exploitation of standard numerical tools in nonlinear engineering problems. The presentation style ensures a balanced construction in providing mathematical knowledge illustrated by relevant examples. suitable for self-study and teaching support at the first postgraduate level. The book is recommended to educators interested in preparing or upgrading lecture notes and seminars, students specializing in different fields of engineering, and practitioners working with various types of nonlinear models. (Octavian Pastravanu, Zentralblatt MATH, Vol. 1173, 2009)

Preface xi
1 Introduction to Nonlinear Engineering Problems and Models
1
1.1 Science and Engineering
1
1.2 The Engineering Method
3
1.3 Some General Features of Engineering Models
6
1.4 Linear and Nonlinear Models
8
1.5 A Brief Look Ahead
14
2 Numerical Fundamentals and Computer Programming
17
2.1 Computer Programming Languages
17
2.2 Lua as a Programming Language
19
2.3 Data Representation and Associated Limitations
23
2.4 Language Extensibility
29
2.5 Some Language Enhancement Functions
33
2.6 Software Coding Practices
37
2.7 Summary
40
3 Roots of Nonlinear Equations
43
3.1 Successive Substitutions or Fixed Point Iteration
45
3.2 Newton's Method or Newton-Ralphson Method
51
3.3 Halley's Iteration Method
68
3.4 Other Solution Methods
70
3.5 Some Final Considerations for Finding Roots of Functions
71
3.6 Summary
75
4 Solving Sets of Equations: Linear and Nonlinear
77
4.1 The Solution of Sets of Linear Equations
78
4.2 Solution of Sets of Nonlinear Equations
87
4.3 Some Examples of Sets of Equations
93
4.4 Polynomial Equations and Roots of Polynomial Equations
117
4.5 Matrix Equations and Matrix Operations
131
4.6 Matrix Eigenvalue Problems
140
4.7 Summary
146
5 Numerical Derivatives and Numerical Integration
147
5.1 Fundamentals of Numerical Derivatives
147
5.2 Maximum and Minimum Problems
161
5.3 Numerical Partial Derivatives and Min/Max Applications
164
5.4 Fundamentals of Numerical Integration
169
5.5 Integrals with Singularities and Infinite Limits
178
5.6 Summary
185
6 Interpolation
187
6.1 Introduction to Interpolation – Linear Interpolation
188
6.2 Interpolation using Local Cubic (LCB) Functions
192
6.3 Interpolation using Cubic Spline Functions (CSP)
199
6.4 Interpolation Examples with Known Functions
203
6.5 Interpolation Examples with Unknown Functions
216
6.6 Summary
225
7 Curve Fitting and Data Plotting
227
7.1 Introduction
227
7.2 Linear Least Squares Data Fitting
229
7.3 General Least Squares Fitting with Linear Coefficients
236
7.4 The Fourier Series Method
238
7.5 Nonlinear Least Squares Curve Fitting
253
7.6 Data Fitting and Plotting with Known Functional Foms
264
7.7 General Data Fitting and Plotting
275
7.8 Rational Function Approximations to Implicit Functions
293
7.9 Weighting Factors
306
7.10 Summary
310
8 Statistical Methods and Basic Statistical Functions
313
8.1 Introduction
313
8.2 Basic Statistical Properties and Functions
315
8.3 Distributions and More Distributions
326
8.4 Analysis of Mean and Variance
332
8.5 Comparing Distribution Functions – The Kolmogorov-Smirnov Test
347
8.6 Monte Carlo Simulations and Confidence Limits
355
8.7 Non-Gaussian Distributions and Reliability Modeling
361
8.8 Summary
367
9 Data Models and Parameter Estimation
369
9.1 Introduction
369
9.2 Goodness of Data Fit and the 6-Plot Approach
372
9.3 Confidence Limits on Estimated Parameters and MC Analysis
381
9.4 Examples of Single Variable Data Fitting and Parameter Estimation
397
9.5 Data Fitting and Parameter Estimation with Weighting Factors
429
9.6 Data Fitting and Parameter Estimation with Transcendental Functions
436
9.7 Data Fitting and Parameter Estimation with Piecewise Model Equations
439
9.8 Data Fitting and Parameter Estimation with Multiple Independent Parameters
442
9.9 Response Surface Modeling and Parameter Estimation
452
9.10 Summary
459
10 Differential Equations: Initial Value Problems 461
10.1 Introduction to the Numerical Solution of Differential Equations
461
10.2 Systems of Differential Equations
467
10.3 Exploring Stability and Accuracy Issues with Simple Examples
469
10.4 Development of a General Differential Equation Algorithm
481
10.5 Variable Time Step Solutions
487
10.6 A More Detailed Look at Accuracy Issues with the TP Algorithm
497
10.7 Runge-Kutta Algorithms
515
10.8 An Adaptive Step Size Algorithm
522
10.9 Comparison with MATLAB Differential Equation Routines
536
10.10 Direct Solution of Second Order Differential Equations
541
10.11 Differential-Algebraic Systems of Equations
546
10.12 Examples of Initial Value Problems
551
10.13 Summary
573
11 Differential Equations: Boundary Value Problems 575
11.1 Introduction to Boundary Value Problems in One Independent Variable
575
11.2 Shooting(ST) Methods and Boundary Value Problems(BVP)
577
11.3 Accuracy of the Shooting Method for Boundary Value Problems
592
11.4 Eigenvalue and Eigenfunction Problems in Differential Equations
600
11.5 Finite Difference Methods and Boundary Value Problems
620
11.6 Boundary Value Problems with Coupled Second Order Differential Equations
648
11.7 Other Selected Examples of Boundary Value Problems
681
11.8 Estimating Parameters of Differential Equations
688
11.9 Summary
701
12 Partial Differential Equations: Finite Difference Approaches 705
12.1 Introduction to Single Partial Differential Equations
706
12.2 Introduction to Boundary Conditions
707
12.3 Introduction to the Finite Difference Method
708
12.4 Coupled Systems of Partial Differential Equations
714
12.5 Exploring the Accuracy of the Finite Difference Method For Partial Differential Equations
727
12.6 Some Examples of Partial Differential Equations of the Initial Value, Boundary Value Type
735
12.7 Boundary Value Problems (BVP) in Two Dimensions
793
12.8 Two Dimensional BVPs with One Time Dimension
849
12.9 Some Selected Examples of Two Dimensional BVPs
860
12.10 Summary
879
13 Partial Differential Equations: The Finite Element Method 883
13.1 An Introduction to the Finite Element Method
883
13.2 Selecting and Determining Finite Elements
885
13.3 Shape Functions and Natural Coordinates
890
13.4 Formulation of Finite Element Equations
893
13.5 Interpolation Functions and Integral Evaluation
899
13.6 Boundary Conditions with the Finite Element Method
903
13.7 The Complete Finite Element Method
907
13.8 Exploring the Accuracy of the Finite Element Method
923
13.9 Two Dimensional BVPs with One Time Dimension
925
13.10 Selected Examples of PDEs with the Finite Element Method
935
13.11 Some Final Considerations for the FE Method
984
13.12 Summary
986
Appendix A: A Brief Summary of the Lua Programming Language 989
Appendix B: Software Installation 1001
Subject Index 1009