Book contents
- Frontmatter
- Contents
- Preface
- 1 Linear algebra
- 2 Nonlinear algebraic systems
- 3 Matrix eigenvalue analysis
- 4 Initial value problems
- 5 Numerical optimization
- 6 Boundary value problems
- 7 Probability theory and stochastic simulation
- 8 Bayesian statistics and parameter estimation
- 9 Fourier analysis
- References
- Index
Preface
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- 1 Linear algebra
- 2 Nonlinear algebraic systems
- 3 Matrix eigenvalue analysis
- 4 Initial value problems
- 5 Numerical optimization
- 6 Boundary value problems
- 7 Probability theory and stochastic simulation
- 8 Bayesian statistics and parameter estimation
- 9 Fourier analysis
- References
- Index
Summary
This text focuses on the application of quantitative analysis to the field of chemical engineering. Modern engineering practice is becoming increasingly more quantitative, as the use of scientific computing becomes ever more closely integrated into the daily activities of all engineers. It is no longer the domain of a small community of specialist practitioners. Whereas in the past, one had to hand-craft a program to solve a particular problem, carefully husbanding the limited memory and CPU cycles available, now we can very quickly solve far more complex problems using powerful, widely-available software. This has introduced the need for research engineers and scientists to become computationally literate – to know the possibilities that exist for applying computation to their problems, to understand the basic ideas behind the most important algorithms so as to make wise choices when selecting and tuning them, and to have the foundational knowledge necessary to navigate independently through the literature.
This text meets this need, and is written at the level of a first-year graduate student in chemical engineering, a consequence of its development for use at MIT for the course 10.34, “Numerical methods applied to chemical engineering.” This course was added in 2001 to the graduate core curriculum to provide all first-year Masters and Ph.D. students with an overview of quantitative methods to augment the existing core courses in transport phenomena, thermodynamics, and chemical reaction engineering.
- Type
- Chapter
- Information
- Numerical Methods for Chemical EngineeringApplications in MATLAB, pp. ix - xiiPublisher: Cambridge University PressPrint publication year: 2006