Computational Methods for Process Simulation

W. Fred Ramirez

• Publisher: Butterworth-Heinemann
• Year: 1997
• Print ISBN: 9780750635417
• eBook ISBN: 9780080529691
• Edition: 2
• Topic: Biological Sciences
• Subtopic: Computer Engineering
• Index: Biological Sciences

Process Modelling and simulation have proved to be extremely successful engineering tools for the design and optimisation of physical, chemical and biochemical processes. The use of simulation has expanded rapidly over the last two decades because of the availability of large high-speed computers and indeed has become even more widespread with the rise of the desk-top PC resources now available to nearly every engineer and student. In the chemical industry large, realistic non-linear problems are routinely solved with the aid of computer simulation. This has a number of benefits, including easy assessment of the economic desirability of a project, convenient investigation of the effects of changes to system variables, and finally the introduction of mathematical rigour into the design process and inherent assumptions that may not have been there before. Computational Methods for Process Simulation develops the methods needed for the simulation of real processes to be found in the process industries. It also stresses the engineering fundamentals used in developing process models. Steady state and dynamic systems are considered, for both spatially lumped and spatially distributed problems. It develops analytical and numerical computational techniques for algebraic, ordinary and partial differential equations, and makes use of computer software routines that are widely available. Dedicated software examples are available via the internet. - Written for a compulsory course element in the US - Includes examples using software used in academia and industry - Software available via the Internet

Chapter 1

DEVELOPMENT OF MACROSCOPIC MASS, ENERGY, AND MOMENTUM BALANCES

In order to mathematically model a physical process, an engineer must write appropriate conservation equations for the process and then incorporate various mechanistic rate and equilibrium relations into those equations. Macroscopic conservation balances are written about a finite control volume and give rise to volume integral expressions for the basic principles of the conservation of mass, the conservation of energy, and the conservation of momentum. Since macroscopic balances are written over a finite control volume, no spatial gradients of the dependent variables appear in the conservation relations. Dependent variables such as temperature and concentration are therefore not differential functions of the spatial independent variables within the control volume, but represent average values over the control volume. The only differential independent variable is time. Therefore, by using the macroscopic conservation principles, mathematical models for unsteady—state processes yield sets of ordinary differential equations, while models for steady—state processes yield sets of algebraic equations. This chapter develops macroscopic mass, energy, and momentum balances and illustrates their use via some classical problems. The information—flow diagram is used to arrange the mathematical relations of these illustrations into solution strategies. Even though, for small problems such as these, we usually perform this function routinely without much thought, the information—flow diagram, or block—diagram approach is introduced here so that the reader may develop competency in using the technique before it is really required in the simulation of more complex problems. Analytical techniques are used to solve the problems presented in this chapter. Appendix A gives a review of analytic methods for the solution of ordinary differential equations.

1.1 CONSERVATIO...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• PREFACE
• ACKNOWLEDGMENTS
• INTRODUCTION
• Chapter 1: DEVELOPMENT OF MACROSCOPIC MASS, ENERGY, AND MOMENTUM BALANCES
• Chapter 2: STEADY-STATE LUMPED SYSTEMS
• Chapter 3: UNSTEADY-STATE LUMPED SYSTEMS
• Chapter 4: REACTION-KINETIC SYSTEMS
• Chapter 5: VAPOR-LIQUID EQUILIBRIUM OPERATIONS
• Chapter 6: MICROSCOPIC BALANCES
• Chapter 7: SOLUTION OF SPLIT BOUNDARY–VALUE PROBLEMS
• Chapter 8: SOLUTION OF PARTIAL DIFFERENTIAL EQUATIONS
• NOMENCLATURE
• Appendix A: ANALYTICAL SOLUTIONS TO ORDINARY DIFFERENTIAL EQUATIONS
• Appendix B: MATLAB REFERENCE TABLES
• Index