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Introduction to Numerical Methods for Time Dependent Differential Equations


Introduction to Numerical Methods for Time Dependent Differential Equations


1. Aufl.

von: Heinz-Otto Kreiss, Omar Eduardo Ortiz

82,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 24.04.2014
ISBN/EAN: 9781118838914
Sprache: englisch
Anzahl Seiten: 192

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Beschreibungen

<p><b>Introduces both the fundamentals of time dependent differential equations and their numerical solutions</b></p> <p><i>Introduction to Numerical Methods for Time Dependent Differential Equations </i>delves into the underlying mathematical theory needed to solve time dependent differential equations numerically. Written as a self-contained introduction, the book is divided into two parts to emphasize both ordinary differential equations (ODEs) and partial differential equations (PDEs).</p> <p>Beginning with ODEs and their approximations, the authors provide a crucial presentation of fundamental notions, such as the theory of scalar equations, finite difference approximations, and the Explicit Euler method. Next, a discussion on higher order approximations, implicit methods, multistep methods, Fourier interpolation, PDEs in one space dimension as well as their related systems is provided.</p> <p><i>Introduction to Numerical Methods for Time Dependent Differential Equations </i>features:</p> <ul> <li>A step-by-step discussion of the procedures needed to prove the stability of difference approximations</li> <li>Multiple exercises throughout with select answers, providing readers with a practical guide to understanding the approximations of differential equations</li> <li>A simplified approach in a one space dimension</li> <li>Analytical theory for difference approximations that is particularly useful to clarify procedures</li> </ul> <p><i>Introduction to Numerical Methods for Time Dependent Differential Equations </i>is an excellent textbook for upper-undergraduate courses in applied mathematics, engineering, and physics as well as a useful reference for physical scientists, engineers, numerical analysts, and mathematical modelers who use numerical experiments to test designs or predict and investigate phenomena from many disciplines.</p>
<p>Preface xiii</p> <p>Acknowledgments xv</p> <p><b>PART I ORDINARY DIFFERENTIAL EQUATIONS AND THEIR APPROXIMATIONS</b></p> <p><b>1 First Order Scalar Equations 3</b></p> <p>1.1 Constant coefficient linear equations 3</p> <p>1.1.1 Duhamel’s principle 8</p> <p>1.1.2 Principle of frozen coefficients 10</p> <p>1.2 Variable coefficient linear equations 10</p> <p>1.2.1 The principle of superposition 10</p> <p>1.2.2 Duhamel’s principle for variable coefficients 12</p> <p>1.3 Perturbations and the concept of stability 13</p> <p>1.4 Nonlinear equations: the possibility of blowup 17</p> <p>1.5 The principle of linearization 20</p> <p><b>2 The Method of Euler 23</b></p> <p>2.1 The explicit Euler method 23</p> <p>2.2 Stability of the explicit Euler method 25</p> <p>2.3 Accuracy and truncation error 27</p> <p>2.4 Discrete Duhamel’s principle and global error 28</p> <p>2.5 General onestep methods. 31</p> <p>2.6 How to test the correctness of a program 32</p> <p>2.7 Extrapolation 34</p> <p><b>3 Higher Order Methods 37</b></p> <p>3.1 The secondorder Taylor method 37</p> <p>3.2 Improved Euler’s method 39</p> <p>3.3 Accuracy of the computed solution 40</p> <p>3.4 RungeKutta methods 44</p> <p>3.5 Regions of stability 48</p> <p>3.6 Accuracy and truncation error 51</p> <p>3.7 Difference approximations for unstable problems 52</p> <p><b>4 The Implicit Euler Method 55</b></p> <p>4.1 Stiff equations 55</p> <p>4.2 The implicit Euler method 58</p> <p>4.3 A simple variable step size strategy 63</p> <p><b>5 Two Step and Multistep Methods 67</b></p> <p>5.1 Multistep methods 67</p> <p>5.2 The leapfrog method 68</p> <p>5.3 Adams methods 72</p> <p>5.4 Stability of multistep methods 74</p> <p><b>6 Systems of Differential Equations 77</b></p> <p><b>PART II PARTIAL DIFFERENTIAL EQUATIONS AND THEIR APPROXIMATIONS</b></p> <p><b>7 Fourier Series and Interpolation 83</b></p> <p>7.1 Fourier expansion 83</p> <p>7.2 The L2norm and scalar product 89</p> <p>7.3 Fourier interpolation 92</p> <p>7.3.1 Scalar product and norm for 1periodic grid functions 93</p> <p><b>8 1periodic Solutions of Time Dependent PDE... 95</b></p> <p>8.1 Examples of equations with simple wave solutions 95</p> <p>8.1.1 The oneway wave equation 95</p> <p>8.1.2 The heat equation 96</p> <p>8.1.3 The wave equation 97</p> <p>8.2 Discussion of well posed problems for time dependent PDE... 98</p> <p>8.2.1 First order equations 98</p> <p>8.2.2 Second order (in space) equations 100</p> <p>8.2.3 General equation 101</p> <p>8.2.4 Stability against lower order terms and systems of equations 102</p> <p><b>9 Approximations of 1periodic Solutions of PDE 105</b></p> <p>9.1 Approximations of space derivatives 105</p> <p>9.1.1 Smoothness of the Fourier interpolant 108</p> <p>9.2 Differentiation of Periodic Functions 109</p> <p>9.3 The method of lines 110</p> <p>9.3.1 The oneway wave equation 110</p> <p>9.3.2 The heat equation 113</p> <p>9.3.3 The wave equation 115</p> <p>9.4 Time Discretizations and Stability Analysis 116</p> <p><b>10 Linear InitialBoundary Value Problems 119</b></p> <p>10.1 Well Posed InitialBoundary Value Problems 119</p> <p>10.1.1 The heat equation on a strip 120</p> <p>10.1.2 The oneway wave equation on a strip 122</p> <p>10.1.3 The wave equation on a strip 124</p> <p>10.2 The method of lines 126</p> <p>10.2.1 The heat equation 126</p> <p>10.2.2 Finite differences algebra 130</p> <p>10.2.3 General parabolic problem 131</p> <p>10.2.4 The oneway wave equation 134</p> <p>10.2.5 The wave equation 135</p> <p><b>11 Nonlinear Problems 137</b></p> <p>11.1 Initialvalue problems for ODE 138</p> <p>11.2 Existence theorems for nonlinear PDE 141</p> <p>11.3 A nonlinear example: Burgers’ equation 145</p> <p><b>A Auxiliary Material 149</b></p> <p>A.1 Some useful Taylor series 149</p> <p>A.2 The “O” notation 150</p> <p>A.3 The solution expansion 150</p> <p><b>B Solutions to Exercises 153</b></p> <p>References 171</p> <p>Index 173</p>
<p><b>HEINZ-OTTO KREISS, P<small>H</small>D,</b> is Professor Emeritus in the Department of Mathematics at the University of California, Los Angeles and is a renowned mathematician in the field of applied mathematics.</p> <p><b>OMAR EDUARDO ORTIZ, P<small>H</small>D,</b> is Professor in the Department of Mathematics, Astronomy, and Physics at the National University of Córdoba, Argentina. Dr. Ortiz’s research interests include analytical and numerical methods for PDEs applied in physics.</p>
<p><b>Introduces both the fundamentals of time dependent differential equations and their numerical solutions</b></p> <p><i>Introduction to Numerical Methods for Time Dependent Differential Equations</i> delves into the underlying mathematical theory needed to solve time dependent differential equations numerically. Written as a self-contained introduction, the book is divided into two parts to emphasize both ordinary differential equations (ODEs) and partial differential equations (PDEs).</p> <p>Beginning with ODEs and their approximations, the authors provide a crucial presentation of fundamental notions, such as the theory of scalar equations, finite difference approximations, and the Explicit Euler method. Next, a discussion on higher order approximations, implicit methods, multistep methods, Fourier interpolation, PDEs in one space dimension as well as their related systems is provided.</p> <p><i>Introduction to Numerical Methods for Time Dependent Differential Equations</i> features:</p> <ul> <li>A step-by-step discussion of the procedures needed to prove the stability of difference approximations</li> <li>Multiple exercises throughout with select answers, providing readers with a practical guide to understanding the approximations of differential equations</li> <li>A simplified approach in a one space dimension</li> <li>Analytical theory for difference approximations that is particularly useful to clarify procedures</li> </ul> <p><i>Introduction to Numerical Methods for Time Dependent Differential Equations</i> is an excellent textbook for upper-undergraduate courses in applied mathematics, engineering, and physics as well as a useful reference for physical scientists, engineers, numerical analysts, and mathematical modelers who use numerical experiments to test designs or predict and investigate phenomena from many disciplines.</p>

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