# CHEN 2450 – Numerical Methods SYLLABUS (FALL 2017)

Phone Number:
Office Hours:
Office Location: MEB 3290H

## Course Catalog Description

Applications of numerical methods to interpolation, differentiation, integration, and the solution of systems of linear, nonlinear, and differential equations in chemical engineering.

## Course Objectives & Topics:

The primary goal of this course is to provide engineering students with a basic working knowledge of numerical methods. In addition, this course aims at developing an appreciation of programming and how computers can be an asset for the modern-day engineer.

My goals in this class are:

1. Teach you the importance of numerical methods
2. Introduce you to the skills needed by modern engineers
3. Emphasize the importance of knowing a few programming languages
4. Emphasize learning and critical thinking

Matlab is the standard software environment used for implementation and application of numerical methods.

By the end of this class, students will have a working knowledge of the following:

• Solution of linear systems of equations
• Interpolation
• Regression
• Solution of nonlinear equations
• Numerical differentiation
• Numerical integration
• Solution of ordinary differential equations (ODEs).
• Solution of elliptic and parabolic partial differential equations.

The following are listed as prerequisites and corequisites for ChEn 2450:

• Prerequisites:  ChEn 1703,  Algebra & calculus
• Corequisite: Math 2250 – Ordinary differential equations & Linear Algebra

There is no textbook for this class. Material presented in this class will be based on the following resources:

• Numerical Computing with MATLAB by Cleve Moler
• Hoffman, J. D. (2001). Numerical methods for engineers and scientists. New York: Marcel Dekker.
• Chapra, S. C., & Canale, R. P. (2010). Numerical methods for engineers . Boston: McGraw-Hill Higher Education.

## Tentative Lectures

Lecture ID Date Lecture Notes (PDF/Web) Goals Screencast Other HW
1 Monday, 08/21/2017 Introduction Introduction, Accuracy, Precision, Types of Errors
2 Wednesday, 08/23/2017 Python Primer Learn basic Python programming HW1 Assigned: Programming Warmup
3 Monday, 08/28/2017 Linear systems: direct solvers 1 Learn how to solve a linear system of equations
4 Wednesday, 08/30/2017 Linear system: direct solvers 2 continuation of previous lecture HW1 Due. HW2 Assigned: Direct Linear Solvers
Monday, 09/04/2017 NO CLASS – LABOR DAY
5 Wednesday, 09/06/2017 Linear systems: iterative solvers 1 Learn how iterative solvers work, their advantages and disadvantages HW2 Due
6 Monday, 09/11/2017 Linear systems: iterative solvers 2 Continuation of previous lecture HW3 Assigned: Iterative Linear Solvers
7 Wednesday, 09/13/2017 Interpolation 1 Learn about linear and polynomial interpolation to approximate functions at new points
8 Monday, 09/18/2017 Interpolation 2 HW3 Due. HW4 Assigned: Interpolation
9 Wednesday, 09/20/2017 Regression 1 Learn about regression and data fitting
10 Monday, 09/25/2017 Regression 2 HW4 Due
11 Wednesday, 09/27/2017 Regression 3
Monday, 10/02/2017 MIDTERM 1
12 Wednesday, 10/04/2017 Numerical Integration 1 Learn about numerical integration to approximate the area under a curve and more HW5 Assigned: Regression
Monday, 10/09/2017 NO CLASS – Fall Break
Wednesday, 10/11/2017 NO CLASS – Fall Break HW5 Due
13 Monday, 10/16/2017 Numerical Integration 2
14 Wednesday, 10/18/2017 Numerical Differentiation Learn the art of numerical differentiation, a fundamental aspect of high performance computing HW6 Assigned
15 Monday, 10/23/2017 Nonlinear Equations 1 Learn about nonlinear and transcendental equations
16 Wednesday, 10/25/2017 Nonlinear Equations 2 Bisection method and Regula-Falsi HW6 Due
17 Monday, 10/30/2017 Nonlinear Equations 3 Secant & Newton’s methods
18 Wednesday, 11/01/2017 Nonlinear Equations 4 Nonlinear systems of equations HW7 Assigned
Monday, 11/06/2017 MIDTERM 2
19 Wednesday, 11/08/2017 ODEs 1 Introduction to ODEs and their numerical solution
20 Monday, 11/13/2017 ODEs 2 Explicit time integration methods: Forward Euler HW7 Due
21 Wednesday, 11/15/2017 ODEs 3 Implicit time integration method: Backward Euler and Crank-Nicholson
22 Monday, 11/20/2017 ODEs 4 Systems of ODEs
23 Wednesday, 11/22/2017 ODEs 5 Boundary value problems in ODEs
24 Monday, 11/27/2017 PDEs 1 Introduction to numerical partial differential equations with examples
25 Wednesday, 11/29/2017 PDEs 2 Introduction to numerical partial differential equations with examples
26 Monday, 12/04/2017
27 Wednesday, 12/06/2017
Tuesday, 12/12/2017, 8:00 AM to 10:00 AM FINAL EXAM

See here for fall semester schedule: http://registrar.utah.edu/academic-calendars/fall2017.php

Event Date

Classes begin Monday, August 21
Last day to add without a permission code Friday, August 25
Last day to wait list Friday, August 25
Last day to add, drop (delete), elect CR/NC, or audit classes Friday, September 1
Last day to withdraw from classes Friday, October 20
Last day to reverse CR/NC option Friday, December 1
Classes end Thursday, December 7
Final exam period Mon.-Fri., Dec. 11-15
• Getting Help: Meeting times: coming soon
• Discussion sections: coming soon
• Teaching Assistants: coming soon
• College of engineering guidelines discusses withdrawal policies, ADA policies, etc.
• Attend the discussion section you are registered for.  You may attend other ones in addition for extra help.
• Use the course website, lectures, and online resources.
• If all the above fails, then feel free to stop by and we can discuss any gaps in your understanding of the subject matter.

## MATLAB and/OR PYTHON

This class will start your transition to the Python programming language. Homework is accepted in either Matlab or Python (or your other preferred language). While every effort will be made to give you templates and hints on solving problems using Matlab, in-class illustrations will be conducted using Python.

### Accessing Matlab

There are several options for accessing MATLAB.

• The most convenient for ChEn students is probably via the ICC (MEB 2285), which is a Chemical Engineering computer lab.  To set up an account, follow this link.  You can also gain remote access to this lab from any computer with a (fast) network connection.
• You can purchase the student version of MATLAB.  There are also several free MATLAB alternatives, including Octave and FreeMAT.  These don’t have all of the features of MATLAB, but are probably sufficient for what you will need in this class.
• The CADE lab in WEB has Windows (WEB 210), Mac (WEB 210) and Linux (WEB 246) computers. Walk in and find one of the system administrators to get set up with an account.  Also, you can access the Linux machines remotely if you have a fast internet connection.  Only try this if you are familiar with X-windows and SSH.
• Library computers running Windows.  (I don’t think that MATLAB is installed on the Mac computers in the library)

## Homework

• Homework is a fundamental piece of the learning process. It will help you strengthen the concepts you learned in class and apply them to new problems.
• The goal of homework is to get you to familiarize yourself with the nomenclature and the types of problems that can be solved with numerical methods.
• Homework assignments will be posted on the homework page of the course web site. Unless otherwise stated, homework is due by the beginning of class on the date indicated on the schedule.
• Solutions will be posted on the class web site shortly after the due date.
• Feel free to “work together” on homework assignments. Discuss the various solutions methods and attempt to learn or fill deficits in your understanding of the subject matter. However, you must submit your own original work. Please do not cross the line of plagiarism and cheating. Such behavior will not be tolerated.
• Homework assignments must be submitted electronically via the course web page. You should write a report describing the problem, your solution, and presenting your results. Submit your report in either PDF or MS Word format. Any Excel or Matlab files that you used to solve the homework problem should also be submitted with your solution. For more information, see the Homework page.

## In-Class comprehension quizzes

Every week, on the first day of class, I will give you a short “comprehension” quiz. The quiz should take no more than five minutes to complete and will address the comprehension aspect of numerical methods. For example: What do you use interpolation for? Give an example of where linear systems arise?

The quiz will also challenge your critical thinking. For example, if the temperature at 8 AM was 25 degrees and at 9 AM it was 35 degrees. An engineer estimated the temperature at 8:30 AM to be 55 degrees. Does this make sense?

These quizzes are aimed to test your understanding of the subject matter in “words”.

• 20% each midterm exam (two midterms)
• 30% Homework
• 5% In-Class comprehension quizzes (1 quiz each week)
• 25% Final exam

Grades will be assigned on the following scale, normalized to the highest student in the class (who, by definition, is 100%)

• 92< A ≤ 100,   89 < A- ≤ 92
• 86 < B+ ≤ 89,   81 < B ≤ 86,   78 < B- ≤ 81
• 75 < C+ ≤ 78,   70 < C ≤ 75,   67 < C- ≤ 70
• 64 < D+ ≤ 67,   59 < D ≤ 64,   56 < D- ≤ 59
• E ≤ 56

I reserve the right to adjust this scale downward if I deem it necessary.

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• System of Linear Equations: The admission fee at a small fair is $1.50 for children and$4.00 for adults. On a certain day, 2200 people enter the fair and \$5050 is collected. How many children and how many adults attended?