Buch, Englisch, 193 Seiten, Format (B × H): 156 mm x 235 mm, Gewicht: 422 g
Buch, Englisch, 193 Seiten, Format (B × H): 156 mm x 235 mm, Gewicht: 422 g
ISBN: 978-1-4822-2944-8
Verlag: CRC Press
Solve Developed Models in a Numerical Fashion
Designed as an introduction to numerical methods for students, A Numerical Primer for the Chemical Engineer explores the role of models in chemical engineering. Combining mathematical correctness (model verification) with numerical performance (model validation), this text concentrates on numerical methods and problem solving, rather than focusing on in-depth numerical analysis. It applies actual numerical solution strategies to formulated process models to help identify and solve chemical engineering problems.
Describe Motions with Accuracy
The book starts with a recap on linear algebra, and uses algorithms to solve linear equations, nonlinear equations, ordinary differential equations, and partial differential equations (PDEs). It includes an introductory chapter on MATLAB® basics, contains a chapter on the implementation of numerical methods in Excel, and even adopts MATLAB and Excel as the programming environments throughout the text.
The material addresses implicit and explicit schemes, and explores finite difference and finite volume methods for solving transport PDEs. It covers the methods for error and computational stability, as well as curve fitting and optimization. It also contains a case study chapter with worked out examples to demonstrate the numerical techniques, and exercises at the end of each chapter that students can use to familiarize themselves with the numerical methods.
A Numerical Primer for the Chemical Engineer lays down a foundation for numerical problem solving and sets up a basis for more in-depth modeling theory and applications. This text addresses the needs of senior undergraduates in chemical engineering, and students in applied chemistry and biochemical process engineering/food process engineering.
Zielgruppe
Senior undergraduates in chemical engineering, students in applied chemistry, biochemical process engineering/food process engineering.
Autoren/Hrsg.
Weitere Infos & Material
The role of models in chemical engineering
Introduction
The idea of a model
Model building
Model analysis
Model solution strategies
Summary
Exercises
Errors in computer simulations
Introduction
Significant digits
Round off and truncation errors
Break errors
Loss of digits
Ill conditioned problems
(Un-)stable methods
Summary
Exercises
Linear equations
Introduction
MATLAB
Linear systems
The inverse of a matrix
The determinant of a matrix
Useful properties
Matrix ranking
Eigenvalues and eigenvectors
Spectral decomposition
Summary
Exercises
Elimination methods
Introduction
MATLAB
Gaussian elimination
LU factorization
Summary
Exercises
Iterative methods
Introduction
Laplace’s equation
LU factorization
Iterative methods
The Jacobi method
Example for the Jacobi method
Summary
Exercises
Non linear equations
Introduction
Newton’s method D
Newton’s method D
Reduced Newton step method
Quasi Newton’s method
Summary
Exercises
Ordinary differential equations
Introduction
Euler’s method
Accuracy and stability of Euler’s method
The implicit Euler method
Stability of the implicit Euler method
Systems of ODE’s
Stability of ODE systems
Stiffness of ODE systems
Higher order methods
Summary
Exercises
Partial differential equations
Introduction
Types of PDE’s
The method of the lines
Stability
Summary
Exercises
Partial differential equations
Introduction
Transport PDE’s
Finite Volumes
Discretizing the control volumes
Transfer of heat to fluid in a pipe
Simulation of the heat PDE
Summary
Exercises
Data regression and curve fitting
Introduction
The least squares method
Residual analysis
ANOVA analysis
Confidence limits
Summary
Exercises
Optimization
Introduction
Linear programming
Nonlinear programming
Integer programming
Summary
Exercises
Basics of Matlab
Introduction
The Matlab user interface
The array structure
Basic calculations
Plotting
Reading and writing data
Functions and m-files
Repetitive operations
Numerical methods in Excel
Introduction
Basic functions in Excel
The Excel solver
Solving nonlinear equations in Excel
Differentiation Excel
Curve fitting in Excel
Case studies
Introduction
Modeling a separation system
Modeling a chemical reactor system
PVT behavior of pure substances
Dynamic modeling of a distillation column
Dynamic modeling of an extraction cascade (ODE’s)
Distributed parameter models for a tubular reactor
Modeling of an extraction column
Fitting of kinetic data
Fitting of NRTL model parameters
Optimizing a crude oil refinery
Planning in a manufacturing line
Bibliography
