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El. knyga: Numerical Primer for the Chemical Engineer, Second Edition

(Laboratory of Process Systems Engineering, Institute for Environmental Science & Technology (UFT), Bremen University, Germany)
  • Formatas: 208 pages
  • Išleidimo metai: 16-Aug-2019
  • Leidėjas: CRC Press
  • Kalba: eng
  • ISBN-13: 9780429851445
Kitos knygos pagal šią temą:
Numerical Primer for the Chemical Engineer, Second EditionDidesnis paveikslėlis
  • Formatas: 208 pages
  • Išleidimo metai: 16-Aug-2019
  • Leidėjas: CRC Press
  • Kalba: eng
  • ISBN-13: 9780429851445
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Designed as an introduction to numerical methods for students, this book combines mathematical correctness with numerical performance, and concentrates on numerical methods and problem solving. It applies actual numerical solution strategies to formulated process models to help identify and solve chemical engineering problems. Second edition comes with additional chapter on numerical integration and section on boundary value problems in the relevant chapter. Additional material on general modelling principles, mass/energy balances and separate section on DAE’s is also included. Case study section has been extended with additional examples.

Introduction xiii
Preface xv
1 The role of models in chemical engineering
1(12)
1.1 Introduction
1(1)
1.2 The idea of a model
2(1)
1.3 Model building
3(1)
1.4 Model analysis
4(1)
1.5 Model solution strategies
5(1)
1.6 The seven-step modeling procedure
6(4)
1.7 Ingredients of process models
10(1)
1.8 Summary
10(1)
1.9 Exercises
11(2)
2 Errors in computer simulations
13(8)
2.1 Introduction
13(1)
2.2 Significant digits
13(1)
2.3 Round-off and truncation errors
14(2)
2.4 Break errors
16(1)
2.5 Loss of digits
16(1)
2.6 Ill-conditioned problems
17(2)
2.7 (Un-)stable methods
19(1)
2.8 Summary
20(1)
2.9 Exercises
20(1)
3 Linear equations
21(10)
3.1 Introduction
21(1)
3.2 MATLAB
21(1)
3.3 Linear systems
21(1)
3.4 The inverse of a matrix
22(1)
3.5 The determinant of a matrix
23(1)
3.6 Useful properties
24(1)
3.7 Matrix ranking
25(1)
3.8 Eigenvalues and eigenvectors
26(1)
3.9 Spectral decomposition
27(2)
3.10 Summary
29(1)
3.11 Exercises
29(2)
4 Elimination methods
31(10)
4.1 Introduction
31(1)
4.2 MATLAB
31(1)
4.3 Gaussian elimination
31(5)
4.4 LU factorization
36(3)
4.5 Summary
39(1)
4.6 Exercises
39(2)
5 Iterative methods
41(12)
5.1 Introduction
41(1)
5.2 Laplace's equation
41(3)
5.3 LU factorization
44(1)
5.4 Iterative methods
45(1)
5.5 The Jacobi method
46(3)
5.6 Example for the Jacobi method
49(2)
5.7 Summary
51(1)
5.8 Exercises
51(2)
6 Nonlinear equations
53(10)
6.1 Introduction
53(1)
6.2 Newton method ID
53(2)
6.3 Newton method 2D
55(1)
6.4 Reduced Newton step method
56(3)
6.5 Quasi-Newton method
59(1)
6.6 Summary
60(1)
6.7 Exercises
60(3)
7 Ordinary differential equations
63(18)
7.1 Introduction
63(1)
7.2 Euler's method
63(2)
7.3 Accuracy and stability of Euler's method
65(2)
7.4 The implicit Euler method
67(1)
7.5 Stability of the implicit Euler method
67(1)
7.6 Systems of ODEs
68(1)
7.7 Stability of ODE systems
69(2)
7.8 Stiffness of ODE systems
71(1)
7.9 Higher-order methods
71(3)
7.10 Boundary value problems
74(4)
7.11 Summary
78(1)
7.12 Exercises
78(3)
8 Numerical integration
81(10)
8.1 Introduction
81(1)
8.2 Euler's method
81(4)
8.3 The trapezoid method
85(1)
8.4 Simpson's method
86(1)
8.5 Estimation of errors using numerical integration
87(1)
8.6 The Richardson correction
88(1)
8.7 Summary
89(1)
8.8 Exercises
90(1)
9 Partial differential equations 1
91(8)
9.1 Introduction
91(1)
9.2 Types of PDEs
91(1)
9.3 The method of lines
92(4)
9.4 Stability
96(1)
9.5 Summary
97(1)
9.6 Exercises
97(2)
10 Partial differential equations 2
99(10)
10.1 Introduction
99(1)
10.2 Transport PDEs
99(1)
10.3 Finite volumes
100(1)
10.4 Discretizing the control volumes
101(1)
10.5 Transfer of heat to fluid in a pipe
102(3)
10.6 Simulation of the heat PDE
105(2)
10.7 Summary
107(1)
10.8 Exercises
107(2)
11 Data regression and curve fitting
109(8)
11.1 Introduction
109(1)
11.2 The least squares method
109(3)
11.3 Residual analysis
112(2)
11.4 ANOVA analysis
114(1)
11.5 Confidence limits
114(1)
11.6 Summary
114(1)
11.7 Exercises
115(2)
12 Optimization
117(12)
12.1 Introduction
117(1)
12.2 Linear programming
118(2)
12.3 Nonlinear programming
120(2)
12.4 Integer programming
122(2)
12.5 Summary
124(1)
12.6 Exercises
125(4)
13 Basics of MATLAB
129(8)
13.1 Introduction
129(1)
13.2 The MATLAB user interface
129(1)
13.3 The array structure
130(1)
13.4 Basic calculations
131(2)
13.5 Plotting
133(1)
13.6 Reading and writing data
134(1)
13.7 Functions and m-files
134(1)
13.8 Repetitive operations
135(2)
14 Numerical methods in Excel
137(8)
14.1 Introduction
137(1)
14.2 Basic functions in Excel
137(1)
14.3 The Excel solver
137(2)
14.4 Solving nonlinear equations in Excel
139(2)
14.5 Differentiation in Excel
141(1)
14.6 Curve fitting in Excel
141(4)
15 Case studies
145(32)
15.1 Introduction
145(1)
15.2 Modeling a separation system
145(1)
15.3 Modeling a chemical reactor system
146(2)
15.4 PVT behavior of pure substances
148(3)
15.5 Dynamic modeling of a distillation column
151(2)
15.6 Dynamic modeling of an extraction cascade (ODEs)
153(6)
15.7 Distributed parameter models for a tubular reactor
159(2)
15.8 Modeling of an extraction column
161(4)
15.9 Fitting of kinetic data
165(2)
15.10 Fitting of NRTL model parameters
167(4)
15.11 Optimizing a crude oil refinery
171(2)
15.12 Planning in a manufacturing line
173(4)
Bibliography 177(4)
Index 181
Edwin Zondervan was born and raised in Leeuwarden, the Netherlands. After finishing his bachelor with a specialization in process automation in Leeuwarden he continued in Groningen with a M.Sc. in chemical engineering. Then he moved To Enschede and pursued a Ph.D. on modeling, optimization and control of dead-end membrane filtration of surface water. He defended his doctorate at Groningen in 2007. He worked from 2007 to 2015 at Eindhoven University of Technology. He has been working as associate researcher at the laboratories of Technical University of Catalonia, Carnegie Mellon University, Denmark Technical University and Imperial College . Besides research Edwin Zondervan has been very active in the educational gremials where he trained many generations of students in process design, process control and numerical methods. For the latter one Edwin published a textbook that was released in 2014: A numerical primer for the chemical engineer. Recently Edwin Zondervan joined the Institute for environmental science and Technology of Bremen University, where he obtained a professorship in Process Systems Engineering. The newly established Laboratory of Process Systems Engineering (PSE) at Bremen University (which was established within Bremens Excellence Initiative) will conduct research in the field of sustainable and flexible system design of energy networks. The main objective of the laboratory of PSE is to develop network modeling techniques and dynamic optimization tools and to apply them to the design and operation of complex energy/process systems. The PSE group distinguishes two working areas: i) Novel energy technologies and devices and ii) Energy Efficient production. Where the challenges lie in 1) decisionmaking under uncertainty, 2) sustainable design and 3) managing complexity. In addition the PSE group will be active in the development of an Energy Systems Institute at Bremen University and setup a specialized course program in this field.
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