Chemical Engineering Analysis and Optimization Using MATLAB - Richard Davis

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Résumé :

Preface xi

About the Companion Website xiii

1 Introduction to Modeling 1

1.1 Numerical Methods 3

1.1.1 Linear vs. Nonlinear Equations 5

1.1.2 Standard Features of Numerical Methods 6

1.1.3 Significant Figures and Computer Round-Off Error 7

1.2 Mathematical Model Building 12

1.2.1 Laws of Conservation 14

1.2.2 Lumped vs. Distributed Systems 16

1.2.3 Degrees of Freedom 23

1.2.4 Dimensionless Equations 23

1.2.5 Stochastic vs. Deterministic Modeling 24

1.2.6 Model Verification and Validation 24

1.3 Expert Problem-Solvers 25

2 MATLAB Skill Preparation 27

2.1 Introduction 27

2.1.1 MATLAB User Interface 27

2.1.2 MATLAB File Extensions 29

2.2 Some Useful MATLAB Commands and Functions 33

2.2.1 MATLAB Commands 33

2.2.2 MATLAB Functions 33

2.3 Vector and Matrix Operations 39

2.3.1 Vector Operations 39

2.3.2 Matrix Operations 40

2.4 Loops & Conditional Statements 42

2.5 Solving Equations 43

2.5.1 Linear and Nonlinear Equations and Systems 44

2.6 Optimization Toolbox 46

2.6.1 Minimization vs. Maximization Problems 46

2.6.2 Optimization Solvers 46

Problems 49

3 Model Fitting and Spline Functions 51

3.1 Introduction 51

3.1.1 Linear Equations 52

3.1.1.1 Linear Models 52

3.1.1.2 Model Linearization 52

3.1.2 Algebraic Nonlinear Models 53

3.1.2.1 Nonlinear Models 53

3.1.2.2 Solution Methods for Nonlinear Problems 53

3.1.3 Model Fitting 55

3.1.3.1 Least Squares Procedure 55

3.1.3.2 Regression Analysis 55

3.1.4 Spline Functions 57

3.1.4.1 Linear Interpolation 57

3.1.4.2 Polynomial Interpolation 57

3.1.4.3 Cubic Spline Interpolation 58

3.2 Curve Fitting Toolbox in MATLAB 58

3.2.1 Two Ways to Curve Fitting 58

3.2.2 An Example of Using Curve Fitting App 59

3.2.2.1 Open the Curve Fitting App in Command Window 59

3.2.2.2 Selecting Data and the Default Linear Model 60

3.2.2.3 Selecting Better Models 60

3.3 Model Fitting via Optimization Algorithms 65

3.4 Spline Functions for Complex Models 65

3.4.1 Spline Interpolation in MATLAB - interp1 66

3.4.2 Spline Interpolation in MATLAB - interp2 68

3.5 Application in Chemical Engineering 69

3.5.1 Using Linear Equations 69

3.5.2 Using Nonlinear Equations 72

3.6 Summary 75

Problems 76

4 Optimization 79

4.1 Optimization Overview and Solver Options 79

4.1.1 What Is Optimization? 79

4.1.2 Built-In Function and MATLAB's Toolbox for Optimization 80

4.2 Extreme Value Problem 82

4.2.1 Unconstrained Functions 82

4.2.2 Constrained Functions 92

4.3 Linear Programming 93

4.3.1 Standard Procedure of Linear Programming 94

4.3.2 Solving Linear Programming in MATLAB 95

4.4 Quadratic Programming 96

4.4.1 Standard Procedure of Quadratic Programming 96

4.4.2 Solving Quadratic Programming in MATLAB 97

4.5 Nonlinear Programming 98

4.6 Application in Chemical Engineering 100

4.6.1 Reaction Kinetics Optimization 100

4.6.2 Reaction Productivity Optimization 101

4.6.3 Refinery Economics 103

4.6.4 Chemical Production Optimization 105

4.6.5 Productivity Profit Optimization 107

4.6.6 Catalyst System Design Optimization 108

4.6.7 Reaction Kinetic 109

4.7 Summary 110

Problems 110

5 Enhanced Optimization 115

5.1 Introduction 115

5.1.1 Differences Among Optimization Solvers in MATLAB 115

5.1.2 The D...

Biographie:
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Sommaire:

Weiguo Xie, PhD, is a Professor of Chemical Engineering at the University of Minnesota, Duluth, MN, USA. He has previously held faculty appointments in UK and Australian universities. He has authored over 100 scientific publications, with particular expertise in mathematical modeling, simulation, optimization, and related subjects.

Sam Toan, PhD, is an Associate Professor of Chemical Engineering at the University of Minnesota, Duluth, MN, USA. He has nearly a decade of experience teaching engineering courses focused on MATLAB and has authored over 60 scientific publications.

Richard Davis, PhD, is a Jean G. Blehart Distinguished Professor of Chemical Engineering at the University of Minnesota, Duluth, MN, USA. He has over three decades of experience teaching and researching computational methods, focusing on process modeling and simulation, energy conversion, chemical process safety, and environmental management....