If you are not familiar with Matlab, please start reviewing this now. We will use this extensively throughout the course. My wiki page may be useful to help you learn Matlab.
- Classes will be recorded, and streaming video of lectures will be made available within ~2 days of the lecture. See the schedule page for streaming video and lecture notes.
- Instructor: , Assistant Professor of Chemical Engineering
- Office: INSCC 360
- (801) 585-1246
- Required Text: Multicomponent Mass Transfer, Ross Taylor & R. Krishna, ISBN: 0471574171 NOTE: this text book is out of print. If you are unable to obtain a copy for a reasonable cost, I will provide supplemental information to you. Also note that portions of this book are available on google books.
- Supplemental text books:
- Transport Phenomena – Bird, Stewart & Lightfoot
- Mass Transfer in Multicomponent Mixtures – Wesselingh & Krishna
- College of engineering guidelines discusses withdrawal policies, ADA policies, etc.
- Understand the origins of mass transfer and its relationship to the equations governing conservation of mass, momentum, and energy.
- Provide students with a sound background in the fundamentals of multicomponent mass transfer.
- Provide exposure to simplified models for mass transfer in laminar and turbulent flows, along with algorithms to implement such models.
- A working knowledge of vector calculus, particularly gradient and divergence operators.
- A working knowledge of fluid mechanics including the Navier Stokes equations.
- Knowledge of equations of state, thermodynamics, and chemical kinetics.
- Many homework assignments will involve a significant amount of linear algebra as well as systems of ODEs.
- This class covers coupled physical problems that often preclude simple analytic solutions. For this reason, we will make use of software packages to help solve problems. Students should be proficient in a software package such as MATLAB (preferred) or Python to use for homework, projects, and exams.
- In-class examples as well as solutions to homework will be posted in MATLAB.
- I maintain a wiki that discusses how to use Matlab as well as several basic concepts of numerical analysis. Feel free to visit and contribute to the content there.
Teaching / Learning Philosophy
I have high expectations of all students, but particularly of graduate students. I expect that you will work hard to learn the material, and take personal responsibility for your learning.
I am here to help you learn the material, and will do my best in that regard. I am happy to meet with you outside of class, and strongly encourage you to ask questions in and out of class on any concepts that are unclear to you.
- Homework assignments are intended to help students solidify concepts discussed in class, or explore concepts not fully addressed in class. I expect that you will put significant effort into completing homework assignments, and encourage you to ask questions in and out of class.
- Assignments are due by the beginning of class on the day indicated.
- Homework solutions should be written up well, with a concise description of the problem as well as the full solution procedure. Include assumptions made in formulating the solution as well as a concise outline of the algorithm for numerically intensive homework problems.
- You are encouraged to work together and discuss problems, but each student must submit his/her own work. Copying others’ work is plagiarism and will not be tolerated. Consequences of cheating and plagiarism include failure in this class and possible dismissal from the university. Anything you use in your solution for homework should be properly cited if it does not represent your own work.
- LaTeX is a very good (and free) typesetting package that is ideal for many equations, cross-references, etc. I highly suggest using it for your dissertation and any technical papers you write. You may also want to consider using it for your homework. See here for an example. Also, LyX is a very good GUI front-end for LaTeX. If you are a bit intimidated by LaTeX, try LyX.
Tentative grading policy:
- Homework – 35%
- Midterm exams – 20% each
- Final Exam – 25%