README.md

# Computational Mechanics
## ME 3255 Spring 2017
### Github page: [https://github.uconn.edu/rcc02007/ME3255S2017.git]

### Course Description
This course introduces students to scientific programming utilizing Matlab/Octave.
Numerical methods, best programming practices and version control are introduced. These
methods will be applied to a number of physics-based problems.

### Course Expectations
Students are expected to create numerical approximations for linear and nonlinear
problems, understand approximations due to floating point operations and numerical
approaches and solve differential equations using numerical differentiation and
integration. Students are also expected to learn basics of git version control,
matlab/octave functions and programming best practices. 


**Lectures**: TTh 9:30-10:45 AM, Francis L. Castleman bdg (CAST) room 212

**Instructor**: Prof. Ryan C. Cooper (ryan.c.cooper@uconn.edu)

**Office hours**: Mon 2:30-4:30pm and Thur 11am-1pm in Engineering II room 315

## Teaching Assistants:
- Graduate: Peiyu Zhang <peiyu.zhang@uconn.edu>
- Office hours: Friday 9:00-11:00am in Engineering II room 315

## Course Information
**Prerequisite:** CE 3110, MATH 2410Q 

**Textbook:** Chapra, Steven, *Applied Numerical Methods with MATLAB for Engineers and
Scientists* 3rd edition. 

**Tools used:** [Matlab](https://www.mathworks.com/products/matlab.html), 
[Octave](https://www.gnu.org/software/octave/) , [Github](https://github.com). 

**Recommended tools:** Github Desktop, git, Atom (text editor), Vim (text editor), 
Jupiter notebook (with matlab or octave kernel) 

## Grading

| Item | Percent | Requirement |
|---|---|---------------------------|
| Homework | 50 % | Turn in homeworks by assigned due date|
| Midterm Exam | 10 % | One midterm exam |
| Final Project | 30 % | A final project that will consist of code and documentation |
| Participation | 10 % | During class online form will be sent out, you must submit form with your user ID to get credit |

### Note on Homework and online forms

The Homeworks are graded based upon effort and completeness. The forms are not graded at
all, if they are completed you get credit. It is *your* responsibility to make sure your
answers are correct. Use the homeworks and forms as a study guide for the exams. In
general, I will not post homework solutions. 


## Academic Integrity: 
- The instructors of this class have a zero-tolerance policy for academic misconduct, that
  is copying others' work either in the lab, field, or on an exam.  Any student work that
  is found to be in violation of the university policy regarding academic misconduct
   will be assigned a grade of zero at a
  minimum.
- Read and understand [The UConn Student Code of
  Conduct](http://www.community.uconn.edu/student_code.html "The Student Code for Academic
  Integrity"). Students will follow all University regulations concerning the final exam.

## Course Schedule (which is subject to change based upon feedback and pace of course)
| Week | Date |Chapter| Topic |
|---|---|---|---|
|1|1/17|1|Introduction to Numerical Methods and Github|
|   |1/19|4|Intro con’d and Roundoff/Truncation Errors|
|2|1/24|2|Intro to Matlab/Octave| 
|   |1/26|3|Intro to m-files|
|3|1/31||Consistent Coding habits|
|   |2/2|5|Root Finding| 
|4|2/7|6|Root Finding con’d|      
|   |2/9|7| **Snow Day**|      
|5|2/14|| Optimization |
|   |2/16|8|Linear Algebra|
|6|2/21|9|Linear systems: Gauss elimination|
|   |2/23|10|Linear Systems: LU factorization|
|7|2/28|11|Linear Systems: Error analysis|
|   |3/2|12|Eigenvalues|
|8|3/7|1-10 |Midterm Review|
|   |3/9|1-10|Midterm|
|9|3/14| N/A |Spring Break!|
|   |3/16| N/A |Spring Break!|
|10|3/21|12|Linear Systems: Iterative methods|
|   |3/23|14|Curve fitting: linear regression|
|11|3/28|15|Curve fitting: least squares and nonlinear regression|
|   |3/30|17|Polynomial interpolation|
|12|4/4|18|Splines and Piecewise Interpolation|
|   |4/6|19|Numerical Integration Formulas|
|14|4/11|20|Numerical Integration of Functions|
|   |4/13|21|Numerical Differentiation|
|15|4/18|22|ODEs: Initial value problem|
|   |4/20|23|ODEs: Adaptive methods and stiff systems|
|16|4/25|24|ODEs: Boundary value problems|
|   |4/27||Wrap up and final project discussions|
|17| 5/1  |Finals| Finals Best of Lucks!|