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Numerical Methods for Nonlinear Engineering Models - John R. Hauser
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Numerical Methods for Nonlinear Engineering Models - neues Buch

2009, ISBN: 9781402099199

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 ra… Mehr…

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Numerical Methods for Nonlinear Engineering Models - John R. Hauser
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John R. Hauser:

Numerical Methods for Nonlinear Engineering Models - neues Buch

2009, ISBN: 9781402099199

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 ra… Mehr…

Nr. 16849363. Versandkosten:, Sofort lieferbar, DE. (EUR 0.00)
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Numerical Methods for Nonlinear Engineering Models - neues Buch

ISBN: 9781402099199

Mixed media product, [PU: Springer-Verlag New York Inc.], There are many books on the use of numerical methods for solving engineering problems and for modeling of engineering artifacts. … Mehr…

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Hauser, John R.:
Numerical Methods for Nonlinear Engineering Models - Taschenbuch

2009, ISBN: 1402099193

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Details zum Buch
Numerical Methods for Nonlinear Engineering Models

This text emphasizes the general area of nonlinear engineering models with an in-depth discussion of computer algorithms for solving nonlinear problems coupled with appropriate examples of such nonlinear engineering problems. The present book is a balance of numerical theory applied to nonlinear or linear engineering models with many examples taken for typical engineering type problems. This book is for the engineer who wants to learn the basics of the theory but who wishes to rapidly get to solving real nonlinear engineering type problems with modern desktop computers.

Detailangaben zum Buch - Numerical Methods for Nonlinear Engineering Models


EAN (ISBN-13): 9781402099199
ISBN (ISBN-10): 1402099193
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2009
Herausgeber: Springer
1014 Seiten
Gewicht: 1,864 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2009-03-25T09:05:28+01:00 (Zurich)
Detailseite zuletzt geändert am 2023-03-11T15:15:39+01:00 (Zurich)
ISBN/EAN: 9781402099199

ISBN - alternative Schreibweisen:
1-4020-9919-3, 978-1-4020-9919-9
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: hauser
Titel des Buches: hauskreisbibel, numeri, new york, numerical methods, engineering engineering, nonlinear


Daten vom Verlag:

Autor/in: John R. Hauser
Titel: Numerical Methods for Nonlinear Engineering Models
Verlag: Springer; Springer Netherland
1013 Seiten
Erscheinungsjahr: 2009-03-26
Dordrecht; NL
Gedruckt / Hergestellt in Niederlande.
Gewicht: 1,700 kg
Sprache: Englisch
267,49 € (DE)
274,99 € (AT)
295,00 CHF (CH)
POD
XIII, 1013 p. With CD-ROM.

SF; BB; DB; Computational Intelligence; Hardcover, Softcover / Technik/Allgemeines, Lexika; Künstliche Intelligenz; Verstehen; Simulation; algorithm; algorithms; calculus; computational methods; development; linear optimization; model; modeling; nonlinear engineering models; numerical methods; parameter estimation; partial differential equation; partial differential equations; programming; Numerical and Computational Physics, Simulation; Math. Appl. in Environmental Science; Mathematical and Computational Engineering; Computational Science and Engineering; Computational Intelligence; Theoretical, Mathematical and Computational Physics; Mathematical Applications in Environmental Science; Mathematical and Computational Engineering Applications; Computational Science and Engineering; Mathematische Physik; Umwelt; Angewandte Mathematik; Mathematik für Ingenieure; Numerische Mathematik; EA; BC

Preface; 1 Introduction to Nonlinear Engineering Problems and Models; 1.1 Science and Engineering ; 1.2 The Engineering Method; 1.3 Some General Features of Engineering Models ; 1.4 Linear and Nonlinear; 1.5 A Brief Look Ahead ; 2 Numerical Fundamentals and Computer Programming; 2.1 Computer Programming Languages; 2.2 Lua as a Programming Language; 2.3 Data Representation and Associated Limitations; 2.4 Language Extensibility; 2.5 Some Language Enhancement Functions; 2.6 Software Coding Practices; 2.7 Summary; 3 Roots of Nonlinear Equations; 3.1 Successive Substitutions or Fixed Point Iteration; 3.2 Newton’s Method or Newton-Ralphson Method; 3.3 Halley’s Iteration Method; 3.4 Other Solution Methods; 3.5 Some Final Considerations for Finding Roots of Functions; 3.6 Summary; 4 Solving Sets of Equations: Linear and Nonlinear; 4.1 The Solution of Sets of Linear Equations; 4.2 Solution of Sets of Nonlinear Equations; 4.3 Some Examples of Sets of Equations; 4.4 Polynomial Equations and Roots of Polynomial Equations; 4.5 Matrix Equations and Matrix Operations; 4.6 Matrix Eigenvalue Problems; 4.7 Summary; 5 Numerical Derivatives and Numerical Integration; 5.1 Fundamentals of Numerical Derivatives; 5.2 Maximum and Minimum Problems; 5.3 Numerical Partial Derivatives and Min/Max Applications; 5.4 Fundamentals of Numerical Integration; 5.5 Integrals with Singularities and Infinite Limits; 5.6 Summary; 6 Interpolation; 6.1 Introduction to Interpolation – Linear Interpolation; 6.2 Interpolation using Local Cubic (LCB) Functions; 6.3 Interpolation using Cubic Spline Functions (CSP); 6.4 Interpolation Examples with Known Functions; 6.5 Interpolation Examples with Unknown Functions; 6.6 Summary; 7 Curve Fitting and Data Plotting; 7.1 Introduction; 7.2 Linear Least Squares Data Fitting; 7.3 General Least Squares Fitting with Linear Coefficients; 7.4 The Fourier Series Method; 7.5 Nonlinear Least Squares Curve Fitting; 7.6 Data Fitting and Plotting with Known Functional Foms;7.7 General Data Fitting and Plotting; 7.8 Rational Function Approximations to Implicit Functions; 7.9 Weighting Factors; 7.10 Summary; 8 Statistical Methods and Basic Statistical Functions; 8.1 Introduction; 8.2 Basic Statistical Properties and Functions; 8.3 Distributions and More Distributions; 8.4 Analysis of Mean and Variance; 8.5 Comparing Distribution Functions – The Kolmogorov-Smirnov Test; 8.6 Monte Carlo Simulations and Confidence Limits; 8.7 Non-Gaussian Distributions and Reliability Modeling ; 8.8 Summary; 9 Data Models and Parameter Estimation; 9.1 Introduction; 9.2 Goodness of Data Fit and the 6-Plot Approach; 9.3 Confidence Limits on Estimated Parameters and MC Analysis; 9.4 Examples of Single Variable Data Fitting and Parameter Estimation; 9.5 Data Fitting and Parameter Estimation with Weighting Factors; 9.6 Data Fitting and Parameter Estimation with Transcendental Functions; 9.7 Data Fitting and Parameter Estimation with Piecewise Model Equations; 9.8 Data Fitting and Parameter Estimation with Multiple Independent Parameters; 9.9 Response Surface Modeling and Parameter Estimation; 9.10 Summary; 10 Differential Equations: Initial Value Problems; 10.1 Introduction to the Numerical Solution of Differential Equations; 10.2 Systems of Differential Equations; 10.3 Exploring Stability and Accuracy Issues with Simple Examples; 10.4 Development of a General Differential Equation Algorithm; 10.5 Variable Time Step Solutions; 10.6 A More Detailed Look at Accuracy Issues with the TP Algorithm; 10.7 Runge-Kutta Algorithms; 10.8 An Adaptive Step Size Algorithm; 10.9 Comparison with MATLAB Differential Equation Routines; 10.10 Direct Solution of Second Order Differential Equations; 10.11 Differential-Algebraic Systems of Equations; 10.12 Examples of Initial Value Problems; 10.13 Summary; 11 Differential Equations: Boundary Value Problems ; 11.1 Introduction to Boundary Value Problems in One Independent Variable; 11.2 Shooting(ST) Methods and Boundary Value

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