- Hardcover: 488 pages
- Publisher: Cambridge University Press; 1 edition (October 30, 2006)
- Language: English
- ISBN-10: 0521859719
- ISBN-13: 978-0521859714
- Product Dimensions: 6.8 x 1.3 x 9.7 inches
- Shipping Weight: 2.4 pounds (View shipping rates and policies)
- Average Customer Review: 5 customer reviews
- Amazon Best Sellers Rank: #723,845 in Books (See Top 100 in Books)
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter your mobile phone number.
Numerical Methods for Chemical Engineering: Applications in MATLAB 1st Edition
Use the Amazon App to scan ISBNs and compare prices.
All Books, All the Time
Read author interviews, book reviews, editors picks, and more at the Amazon Book Review. Read it now
Frequently bought together
Customers who bought this item also bought
Suitable for a first year graduate course, this textbook unites applications of numerical mathematics and scientific computing to the practise of chemical engineering. The methods are developed at a level of mathematics suitable for graduate engineering. MATLAB is integrated within each chapter and numerous examples in chemical engineering are provided.
About the Author
Kenneth J Beers has been Assistant Professor at MIT since the year 2000. He has taught extensively across the engineering discipline at both the undergraduate and graduate level. This book is a result of the sucessful course the author devised at MIT for numerical methods applied to chemical engineering.
Discover books for all types of engineers, auto enthusiasts, and much more. Learn more
Top customer reviews
There was a problem filtering reviews right now. Please try again later.
Practice problems are somewhat helpful -- however, they lack in-depth solutions and are often significantly harder than the examples that are provided.
Very broad in scope; covers multiple linear equations, multiple nonlinear equations, optimization w/ gradient search and stochastic search, and monte-carlo methods.
The section on stochastic differential equations is somewhat lacking though.
To be fair, writing a good numerical methods textbook is tough. Numerical methods is a required course in many graduate chemical engineering programs, and other programs elect to give their students course notes (the University of Wisconsin and the University of Delaware are two examples I know of). Beers made an admirable attempt, and specifically includes chemical engineering applications, but the factual errors in an important, foundational subject in numerical methods make it difficult for me to recommend this book.