John Wiley & Sons Computer Models of Process Dynamics Cover COMPUTER MODELS OF PROCESS DYNAMICS Comprehensive overview of techniques for describing physical ph.. Product #: 978-1-119-88565-8 Regular price: $120.56 $120.56 Auf Lager

Computer Models of Process Dynamics

From Newton to Energy Fields

Rubin, Olis Harold

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1. Auflage Oktober 2022
320 Seiten, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-119-88565-8
John Wiley & Sons

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COMPUTER MODELS OF PROCESS DYNAMICS

Comprehensive overview of techniques for describing physical phenomena by means of computer models that are determined by mathematical analysis

Computer Models of Process Dynamics covers everything required to do computer based mathematical modeling of dynamic systems, including an introduction to a scientific language, its use to program essential operations, and methods to approximate the integration of continuous signals.

From a practical standpoint, readers will learn how to build computer models that simulate differential equations. They are also shown how to model physical objects of increasing complexity, where the most complex objects are simulated by finite element models, and how to follow a formal procedure in order to build a valid computer model. To aid in reader comprehension, a series of case studies is presented that covers myriad different topics to provide a view of the challenges that fall within this discipline. The book concludes with a discussion of how computer models are used in an engineering project where the readers would operate in a team environment.

Other topics covered in Computer Models of Process Dynamics include:
* Computer hardware and software, covering algebraic expressions, math functions, computation loops, decision-making, graphics, and user-defined functions
* Creative thinking and scientific theories, covering the Ancients, the Renaissance, Galileo, Newton, electricity and magnetism, and newer sciences
* Uncertainty and softer science, covering random number generators, statistical analysis of data, the method of least squares, and state/velocity estimators
* Flight simulators, covering the motion of an aircraft, the equations of motion, short period pitching motion, and phugoid motion

Established engineers and programmers, along with students and academics in related programs of study, can harness the comprehensive information in Computer Models of Process Dynamics to gain mastery over the subject and be ready to use their knowledge in many practical applications in the field.

Preface xiii

1 Introduction 1

1.1 Engineering uses of computer models 1

1.1.1 Mission statement 2

1.2 The subject matter 3

1.3 Mathematical material 4

1.4 Some remarks 5

Bibliography 5

2 From Computer Hardware to Software 7

2.1 Introduction 7

2.2 Computing machines 7

2.2.1 The software interface 8

2.3 Computer programming 9

2.3.1 Algebraic expressions 10

2.3.2 Math functions 13

2.3.3 Computation loops 14

2.3.4 Decision making 16

2.3.5 Graphics 17

2.3.6 User defined functions 17

2.4 State transition machines 17

2.4.1 A binary signal generator 18

2.4.2 Operational control of an industrial plant 24

2.5 Difference engines 25

2.5.1 Difference equation to calculate compound interest 26

2.6 Iterative programming 27

2.6.1 Inverse functions 29

2.7 Digital simulation of differential equations 30

2.7.1 Rectangular integration 31

2.7.2 Trapezoidal integration 33

2.7.3 Second-order integration 35

2.7.4 An Example 36

2.8 Discussion 37

Exercises 38

References 41

3 Creative thinking and scientific theories 43

3.1 Introduction 43

3.2 The dawn of astronomy 44

3.3 The renaissance 45

3.3.1 Galileo 45

3.3.2 Newton 46

3.4 Electromagnetism 49

3.4.1 Magnetic fields 50

3.4.2 Electromagnetic induction 50

3.4.3 Electromagnetic radiation 51

3.5 Aerodynamics 52

3.5.1 Vector flow fields 53

3.6 Discussion 54

References 56

4 Calculus and the computer 57

4.1 Introduction 57

4.2 Mathematical solution of differential equations 58

4.3 From physical analogs to analog computers 60

4.4 Picard's method for solving a nonlinear differential equation 61

4.4.1 Mechanization of Picard's method 62

4.4.2 Feedback model of the differential equation 62

4.4.3 Approximate solution by Taylor series 64

4.5 Exponential functions and linear differential equations 65

4.5.1 Taylor series to approximate exponential functions 66

4.6 Sinusoidal functions and phasors 67

4.6.1 Taylor series to approximate sinusoids 69

4.7 Bessel's equation 70

4.8 Discussion 72

Exercises 73

Bibliography 74

5 Science and computer models 75

5.1 Introduction 75

5.2 A planetary orbit around a stationary Sun 76

5.2.1 An analytic solution for planetary orbits 79

5.2.2 A difference equation to model planetary orbits 80

5.3 Simulation of a swinging pendulum 81

5.3.1 A graphical construction to show the motion of a pendulum 83

5.3.2 Truncation and roundoff errors 84

5.4 Lagrange's equations of motion 85

5.4.1 A double pendulum 87

5.4.2 A few comments 90

5.4.3 Modes of motion of a double pendulum 90

5.4.4 Structural vibrations in an aircraft 91

5.5 Discussion 94

Exercises 94

Bibliography 95

6 Flight simulators 97

6.1 Introduction 97

6.2 The motion of an aircraft 98

6.2.1 The equations of motion 99

6.3 Short period pitching motion 101

6.3.1 Case study of short period pitching motion 104

6.3.2 State equations of short period pitching 105

6.3.3 Transfer functions of short period pitching 107

6.3.4 Frequency response of short period pitching 108

6.4 Phugoid motion 110

6.5 User interfaces 111

6.6 Discussion 112

Exercises 113

Bibliography 114

7 Finite element models and the diffusion of heat 115

7.1 Introduction 115

7.2 A thermal model 117

7.2.1 A finite element model based on an electrical ladder network 118

7.2.2 Free settling from an initial temperature profile 119

7.2.3 Step response test 121

7.2.4 State space model of diffusion 126

7.3 A practical application 129

7.4 Two-dimensional steady-state model 131

7.5 Discussion 132

Exercises 134

Bibliography 135

8 Wave equations 137

8.1 Introduction 137

8.2 Energy storage mechanisms 138

8.2.1 Partial differential equation describing propagation in a transmission line 140

8.3 A finite element model of a transmission line 141

8.4 State space model of a standing wave in a vibrating system 145

8.4.1 State space model of a multiple compound pendulum 147

8.5 A two-dimensional electromagnetic field 148

8.6 A two-dimensional potential flow model 151

8.7 Discussion 155

Exercises 156

Bibliography 159

9 Uncertainty and softer science 161

9.1 Introduction 161

9.2 Empirical and "black box" models 162

9.2.1 An imperfect model of a simple physical object 163

9.2.2 Finite impulse response models 164

9.3 Randomness within computer models 166

9.3.1 Random number generators and data analysis 167

9.3.2 Statistical estimation and the method of least squares 168

9.3.3 A state estimator 171

9.3.4 A velocity estimator 175

9.3.5 An FIR filter 176

9.4 Economic, Geo-, Bio-, and other sciences 179

9.4.1 A pricing strategy 181

9.4.2 The productivity of money 184

9.4.3 Comments on business models 187

9.5 Digital images 189

9.5.1 An image processor 190

9.6 Discussion 193

Exercises 194

Bibliography 196

10 Computer models in a development project 197

10.1 Introduction 197

10.1.1 The scope of this chapter 198

10.2 A motor drive model 198

10.2.1 A conceptual model 200

10.2.2 The motor drive parameters 202

10.2.3 Creating the simulation model 203

10.2.4 The electrical and mechanical subsystems 204

10.2.5 System integration 206

10.2.6 Configuration management 208

10.3 The definition phase 208

10.3.1 Selection of the motor 209

10.3.2 Simulation of load disturbances 210

10.4 The design phase 213

10.4.1 Calculation of frequency response 213

10.4.2 The current control loop 214

10.4.3 Design review and further actions 217

10.4.4 Rate feedback 219

10.5 A setback to the project 222

10.5.1 Elastic coupling between motor and load 222

10.6 Discussion 227

Exercises 229

Bibliography 230

11 Postscript 231

11.1 Looking back 231

11.2 The operation of a simulation facility 233

11.3 Looking forward 234

Bibliography 235

Appendix A Frequency response methods 237

Appendix B Vector analysis 261

Appendix C Scalar and vector fields 269

Appendix D Probability and statistical models 287

Index 297
Olis Rubin, DSc. Eng., has held many positions in control engineering throughout his career including at Denel, PBMR, ContrOlis, Kentron, and CSIR. He was also an honorary post graduate professor in Control Systems at the University of Pretoria. He previously published Control Engineering in Development Projects (2016) and The Design of Automatic Control Systems (1986) with Artech House.

O. H. Rubin, Brooklyn, Pretoria, South Africa