Syllabus
Computer Methods in Chemical Engineering
Fall 2025
Table of Contents
- Nam Sun Wang
- Class Hour: TuTh 3:30pm-4:45pm; location: Rm 2108 Chemical & Nuclear Engineering Building (CHE)
- Discussion Section Hour: M 1:00-1:50pm; location: 3117 Computer Science Instrunal Center (CSI)
- Office Hours: MW 2-3pm, CHBE TA room (CHE1124)
- Phone: 301-405-1910 (call/email for in-person/Zoom appointment outside the office hours)
- Email: nsw@umd.edu
- Raymond A. Adomaitis
- Office Hours: TBD, 2147 A.V. Williams Bldg.
- Phone: 301-405-2969
- Email: adomaiti@umd.edu
Undergraduate Teaching Fellows:
- Anthony Boscolo
- Office Hour: Th9:30am-10:30am; location: CHBE TA room (CHE1124)
- Other Hours: by appointment
- Email: boscolo@terpmail.umd.edu
- Somiron Kundu
- Office Hour: M3:00pm-3:30pm, W11am-12noon; location: CHBE TA room (CHE1124)
- Other Hours: by appointment
- Email: somironk@terpmail.umd.edu
Required Textbooks:
Recommended Reference Books
- "Applied Numerical Methods With Python, 1st Edition"
Steven C. Chapra and David E. Clough, 2022, McGraw-Hill,
ISBN10: 1266651497 | ISBN13: 9781266651496
- "Applied Numerical Methods W/Matlab, 5th Edition,"
Steven C. Chapra, 2023, McGraw-Hill,
ISBN10: 126416260X | ISBN13: 9781264162604
- Mathematical Application Programs
CHBE101 and ENES100. Some knowledge of computers (beyond gaming), operating
systems, Matlab from previous math courses, and preferably
some exposure to Python --
not strictly required -- we will take you through a crash course.
Some experience with algebraic equations, differential equations,
and preferably linear algebra (vectors & matrices).
Coverage includes numerical methods,
structured programming (Matlab, Python),
and numerical and symbolic computation.
The overall goal of the course is to introduce the use of computers and to
familiarize a student with various computer tools that can aid in
the numerical solution of chemical engineering problems.
Examples will be drawn from chemical engineering.
- Numerical Methods
- Linear Algebraic Equations
- Matrix Inverse
- Nonlinear Algebraic Equations
- Linear and Nonlinear Regression (Data Fitting)
- Differentiation, definite Integral
- Ordinary Differential Equations
- Partial Differential Equations
- Programming
- Python
- Matlab (demo & comparison)
- Spreadsheet (Excel, VBA, demo only)
- Mathematical Packages
- Chemical Engineering Simulation Packages
- Symbolic Computation (in Mathcad and MATLAB), demo only
The primary objective of the course, as implied by the course
content above, is to introduce computer methods to sophomore
students in a hands-on approach. A significant fraction of the
lectures are devoted to the specifics of the major computational
tools introduced in this class:
- Python
- Matlab (demo, comparison)
The other half of the lectures cover the numerical methods.
Examples drawn from the chemical engineering field are solved
with each of the two computational tools by applying appropriate
numerical methods or by calling build-in functions. The course
assumes only minimal computer background and does not assume any
prior programming experience, although it certainly is
advantageous to have prior exposure.
- Programming & coding of numerical algorithms
Distributed throughout
- Call existing/build-in routines
- Solve problems taken from
Material/energy balances
Thermodynamics
Transport
Kinetics
Data fitting & analysis of experimental data
Steady-state & dynamic modeling
This is a required course for all chemical engineering students.
Other engineering students who wish to be computer literate in
the practical application of numerical methods will also benefit
from the course. Upon successful completion of this course, the
student should be able to recognize and solve, manually or with
the help of a computer tool, most of the engineering problems
involving:
- Linear & nonlinear algebraic equations
- Linear & nonlinear regression
- Differentiation & integration
- Ordinary & partial differential equations
Relationship of Course to Program Objectives and 7 ABET Outcomes
In this course, the most relevant program objectives are:
- Outcome #1. the ability to apply knowledge of chemical engineering
fundamentals & STEM to identify and solve complex engineering problems.
- Outcome #2. the ability to perform step-by-step design of
engineered systems and chemical processes.
(Rathan "step-by-step design", we stress "step-by-step problem solving".
Outcome #3. the ability to communicate effectively to a wide range of audience through
oral presentations and written reports
- Outcome #4. Ethical and professional responsibility, contexts (e.g., give proper reference.)
Outcome #5. the ability to successfully participate in teams
- Outcome #6. Experiments, data, analysis, judgment (e.g., regression, data-fitting)
- Outcome #7. Acquire new knowledge, learning strategies (e.g., on-line help, AI)
Student assessment will be based on the following categories,
and semester grade will be assigned based on the following
scheme.
Homework (drop one HW /w lowest score) | 20%
|
Midterm Exam #1 (10/09/25) | 20%
|
Midterm Exam #2 (11/13/25) | 20%
|
Final Exam (12/20/25, 1:30pm-3:30pm) | 40%
|
Students are guaranteed the following letter grades. That means
the instructor will not raise the cut-off points. However,
the instructor shall reserve the right to lower the cut-off
points at the end of the semester.
Students study according to the grades they wish to
receive.
Fraction of Points Earned | Letter Grade
|
---|
0.80- | A (A+, A-)
|
0.67-0.80 | B (B+, B-)
|
0.55-0.67 | C (C+, C-)
|
0.40-0.55 | D
|
0.00-0.40 | F
|
For example, if you earn a total of 250 regular points out of a
possible 300 points on the homework assignments, a total of 150
points out of a possible 200 points on the midterm examination,
and a total of 120 points out of a possible 200 points on the
final examination, your fractional grade at the end of the
semester is:
250/300*0.20 + 150/200*0.40 + 120/200*0.40 = 0.707
Homework Midterm Final Exam
The above lookup table shows that 0.707 translates to a semester
letter grade of "B". For borderline cases, "+" and "-" will be
appended to the letter grade. Thus, you can track your own
letter grade during the semester.
We follow the
University of Maryland Policies.
You can find more information/policies on
academic integrity, code of student conduct, sexual misconduct, non-discrimination procedures,
attendance/absence, medical excuses, etc. at:
University of Maryland Code of Student Conduct from Student Affairs Office and
Course-Related Policies and Resources for Undergraduate Students from the Office of Undergraduate Studies,
Homework is due at the beginning of the class on the specified
date; no late homework will be accepted unless
individually arranged with the instructor before the due
date with a valid excuse. ELMS/CANVAS automatically flags a submission at late even if
it is 0.001 second past the due time. It is the student's responsibility to check the
submitted files are not corrupt. Corrupt submission that cannot be read
will automatically receive no points. Likewise, if a student forgets to
click the "submit" button, the assignment will receive no points.
Strictly follow the required
file naming convention; any deviation will result in a mandatory 1 point
penalty for each file. (Being able to follow instructions strictly is important;
paying close attention down to every single character is critical in coding.)
In solving homework assignments,
students may modify examples already posted on the class web page
or worked out in class, and discussion among classmates is
allowed. Likewise, seeking help from the TA, undergraduate
teaching fellows, graders, and the instructor is certainly
allowed (and highly encouraged).
Search for information seeking help on-line via search engines
(e.g., Google, Bing, etc.) and AI chatbots
(e.g., OpenAI's ChatGPT, Google's Gemini, Microsoft's Copilot, Meta AI's Llama, etc.)
is allowed. In fact, the ability to search on-line is an extremely
critical aspect of being a productive engineer.
However, you must properly reference each source
in the form of specific web URLs, specific journal articles, or
prompts to AI chatbots (google "how to cite AI prompts", "how to reference AI", etc.).
It is emphasized that
each student must ultimately do one's own work
(i.e., absolutely no straight copying of homework from fellow students
nor straight copying from what AI chatbots returns).
It is advised that students first go over the
reading portion of the homework assignments and review the
lecture notes, and subsequently make an honest concerted attempt
at the submission portion of the homework assignments. Do not
develop a habit of automatically and immediately default to
external help; this will not help build your confidence and
competency. A major discrepancy in the homework scores and exam
scores is usually an indication of over-reliance on the help of fellow
students and/or chatbots.
A midterm exam lasting 60 minutes and a final exam lasting 120 minutes
will be given; absolutely no collaboration is allowed in exams.
Plagiarism and academic dishonesty absolutely will NOT be
tolerated, and suspected incidence will be referred to the
Student Honor Council of the Judiciary Programs. I
subscribe to the zero-tolerance principle. It is your
responsibility to consult the instructor whenever there is any
doubt on the definitions of these terms or on the allowable
materials on each specific homework assignments or quizzes/exams.
See Policy on Academic Integrity.
If you have a documented disability and wish to discuss academic
accommodations with the instructor, please do so as soon as
possible.
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Computer Methods in Chemical Engineering -- Syllabus
Forward comments to:
- Nam Sun Wang
- Department of Chemical & Biomolecular Engineering
- University of Maryland
- College Park, MD 20742-2111
- 301-405-1910 (voice)
e-mail: nsw@umd.edu
©2025 by Nam Sun Wang
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