ISBN-13: 9781119316114 / Angielski / Twarda / 2018 / 304 str.
ISBN-13: 9781119316114 / Angielski / Twarda / 2018 / 304 str.
A comprehensive guide to numerical methods for simulating physical-chemical systems This book offers a systematic, highly accessible presentation of numerical methods used to simulate the behavior of physical-chemical systems. Unlike most books on the subject, it focuses on methodology rather than specific applications.
Preface xi
1 Interpolation 1
1.1 Purpose 1
1.2 Definitions 1
1.3 Example 2
1.4 Weirstraus Approximation Theorem 3
1.5 Lagrange Interpolation 4
1.5.1 Example 6
1.6 Compare P2 (—) and ^ f (—) 8
1.7 Error of Approximation 9
1.8 Multiple Elements 14
1.8.1 Example 17
1.9 Hermite Polynomials 20
1.10 Error in Approximation by Hermites 23
1.11 Chapter Summary 24
1.12 Problems 24
2 Numerical Dierentiation 33
2.1 General Theory 33
2.2 Two–Point Dierence Formulae 34
2.2.1 Forward Dierence Formula 35
2.2.2 Backward Dierence Formula 36
2.2.3 Example 36
2.2.4 Error of the Approximation 36
2.3 Two–Point Formulae from Taylor Series 37
2.4 Three–point Dierence Formulae 40
2.4.1 First–Order Derivative Dierence Formulae 41
2.4.2 Second–Order Derivatives 43
2.5 Chapter Summary 46
2.6 Problems 46
3 Numerical Integration 55
3.1 Newton–Cotes Quadrature Formula 55
3.1.1 Lagrange Interpolation 55
3.1.2 Trapezoidal Rule 56
3.1.3 Simpson s Rule 57
3.1.4 General Form 58
3.1.5 Example using Simpson s Rule 59
3.1.6 Gauss Legendre Quadrature 59
3.2 Chapter Summary 62
3.3 Problems 63
4 Initial Value Problems 67
4.1 Euler Forward Integration Method Example 68
4.2 Convergence 69
4.3 Consistency 72
4.4 St ability 73
4.4.1 Example of Stability 74
4.5 Lax Equivalence Theorem 74
4.6 Runge Kut t a Type Formulae 75
4.6.1 General Form 75
4.6.2 Runge Kut ta First–Order Form (Euler s Method) 75
4.6.3 Runge Kut ta Second–Order Form 75
4.7 Chapter Summary 78
4.8 Problems 78
5 Weight ed Residuals Methods 83
5.1 Finite Volume or Subdomain Method 84
5.1.1 Example 86
5.1.2 Finite Dierence Interpretation of the Finite Volume Method 93
5.2 Galerkin Method for First Order Equations 94
5.2.1 Finite–Dierence Interpretation of the Galerkin Approximation 102
5.3 Galerkin Method for Second–Order Equations 102
5.3.1 Finite Dierence Interpretation of Second–Order Galerkin Method111
5.4 Finite Volume Method for Second–Order Equations 112
5.4.1 Example of Finite Volume Solution of a Second–Order Equation 116
5.4.2 Finite Dierence Representat ion of the Finite–Volume Method for Second–Order Equations 122
5.5 Collocation Method 123
5.5.1 Collocation Method for First–Order Equations 123
5.5.2 Collocation Method for Second–Order Equations 126
5.6 Chapter Summary 133
5.7 Problems 133
6 Initial Boundary–Value Problems 139
6.1 Introduction 139
6.2 Two Dimensional Polynomial Approximat ions 139
6.2.1 Example of a Two Dimensional Polynomial Approximation 140
6.3 Finite Dierence Approximation 141
6.3.1 Example of Implicit First–Order Accurate Finite Dierence Calculation 144
6.3.2 Example of Second Order Accurate Finite Dierence Approximation in Space 146
6.4 St ability of Finite Dierence Approximations 149
6.4.1 Example of Stability 153
6.4.2 Example Simulation 156
6.5 Galerkin Finite Element Approximations in Time 158
6.5.1 Strategy One: Forward Dierence Approximation 160
6.5.2 Strategy Two: Backward Dierence Approximation 161
6.6 Chapter Summary 162
6.7 Problems 162
7 Finite Dierence Methods in Two Space 169
7.1 Example Problem 174
7.2 Chapt er Summary 175
7.3 Problems 176
8 Finite Element Methods in Two Space 181
8.1 Finite Element Approximations over Rectangles 181
8.2 Finite Element Approximations over Triangles 195
8.2.1 Formulation of Triangular Basis Funct ions 196
8.2.2 Example Problem of Finite Element Approximation over Triangles 200
8.2.3 Second Type or Neumann Boundary–Value Problem 206
8.3 Isoparametric Finite Element Approximation 211
8.3.1 Natural Coordinate Systems 211
8.3.2 Basis Functions 217
8.3.3 Calculation of the Jacobian 219
8.3.4 Example of Isoparametric Formulation 223
8.4 Chapter Summary 230
8.5 Problems 230
9 Finite Volume Approximation in Two Space 239
9.1 Finite Volume Formulation 239
9.2 Finite Volume Example Problem 1 246
9.2.1 Problem Definition 246
9.2.2 Weighted Residual Formulation 246
9.2.3 Element Coecient Matrices 248
9.2.4 Evaluation of the Line Integral 249
9.2.5 Evaluation of the Area Integral 256
9.2.6 Global Matrix Assembly 260
9.3 Finite Volume Example Problem Two 262
9.3.1 Problem Denition 262
9.3.2 Weighted Residual Formulation 262
9.3.3 Element Coecient Matrices 263
9.3.4 Evaluation of the Source Term 265
9.4 Chapter Summary 266
9.5 Problems 266
10 Initial Boundary–Value Problems 273
10.1 Mass Lumping 276
10.2 Chapter Summary 276
10.3 Problems 276
11 Boundary–Value Problems in Three Space 279
11.1 Finite Dierence Approximations 279
11.2 Finite Element Approximations 280
11.3 Chapter Summary 285
12 Nomenclature 289
Index 293
George F. Pinder, PhD, is a Distinguished Professor of Civil and Environmental Engineering with a secondary appointments in Mathematics and Statistics and Computer Science at the University of Vermont, Burlington, Vermont. He is the author or co–author of ten books in numerical mathematics and engineering. Dr. Pinder is the recipient of numerous national and international honors and is a member of the National Academy of Engineering.
A comprehensive guide to numerical methods for simulating physical–chemical systems
This book offers a systematic, highly accessible presentation of numerical methods used to simulate the behavior of physical–chemical systems. Unlike most books on the subject, it focuses on methodology rather than specific applications. Written for students and professionals across an array of scientific and engineering disciplines and with varying levels of experience with applied mathematics, it provides comprehensive descriptions of numerical methods without requiring an advanced mathematical background.
Based on its author′s more than forty years of experience teaching numerical methods to engineering students, Numerical Methods for Solving Partial Differential Equations presents the fundamentals of all of the commonly used numerical methods for solving partial differential equations at a level appropriate for advanced undergraduates and first–year graduate students in science and engineering. Throughout, elementary examples show how numerical methods are used to solve generic versions of equations that arise in many scientific and engineering disciplines. In writing it, the author took pains to ensure that no assumptions were made about the background discipline of the reader.
Comprehensive yet accessible to readers with limited mathematical knowledge, Numerical Methods for Solving Partial Differential Equations is an excellent text for advanced undergraduates and first–year graduate students in the sciences and engineering. It is also a valuable working reference for professionals in engineering, physics, chemistry, computer science, and applied mathematics.
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