## MEC E 390 Numerical Methods of Mechanical Engineers

**Subject & Number:** MEC E 390

**Title:** Numerical Methods of Mechanical Engineers

**Course Career**

**Units**: 3

**Approved Hours:** 3-0-1

**Fee index:** 8

**Faculty:** [Faculty of Engineering]{.mark}

**Department:** Mechanical Engineering

**Typically Offered:** either term or Spring/Summer

### Calendar Description

Application of numerical methods to mechanical engineering problems;
topics include sources and definitions of error, root finding, solutions
of linear and non-linear systems of equations, regression, interpolaton,
numerical integration and differentiation, solution of initial value and
boundary value ordinary differential equations. Applications include
dynamics, solid mechanics, heat transfer and fluid flow. Prerequisites:
MATH 102 and 201.

### Asynchronous & synchronous course content delivery

Please note that this is an in-person course (including lectures, labs,
and exams).

The assignments can be completed asynchronously. The purpose of the labs
is to provide students an opportunity to work on Assignments while
having direct access to a TA who will provide assistance as necessary.
Assignments will be posted on eClass. Assignments 1, 2, and 3 must be
submitted electronically via eClass website as a single PDF file on
Mondays by 12:00 noon. Assignments 4 to 10 (granted for extended
deadline) must be submitted electronically via eClass website as a
single PDF file on Mondays by 11:59 PM. All the other possible
extensions will be announced through eClass page. Submissions will be
accepted in pdf format only. Late assignments may be rejected, and
except in compelling circumstances (please see the university calendar)
will result in a grade of zero.

### 

### Course Objectives & General Content

In this class, you will learn to develop and use algorithms related to
basic numerical methods. You will do this through practice programming
in the MATLAB environment, and apply these methods to mechanical
engineering problems.

### 

### Learning outcomes

1.  [Appreciate the types of errors associated with scientific
    programming]{.mark}

2.  [Critically assess numerical algorithm output for
    reasonableness]{.mark}

3.  [Develop and use algorithms for solving single nonlinear
    equations]{.mark}

4.  [Develop and use algorithms for solving multiple linear and
    nonlinear equations]{.mark}

5.  [Apply curve fits and interpolation using discrete data]{.mark}

6.  [Develop and use algorithms for solving differential equations,
    including initial value problems and linear and nonlinear boundary
    value problems]{.mark}

7.  [Appreciate the relationship between physical phenomenon,
    mathematical model, and numerical model]{.mark}

8.  [Be proficient in the use of numerical computational software (e.g.
    MATLAB) to solve relevant engineering problems]{.mark}

### Textbooks and References

Computational Methods for Engineers - Modeling, Algorithms and Analysis
by J.P. Mmbaga, K.

Nandakumar, R.E. Hayes and M.R. Flynn. Available at the University
Bookstore as well as online (link is available on eClass)

### 

### Assessment Details

+--------------------+--------------------+-------------------+------------+
| **Activity**       | **(A)Synchronous** | **Due/Scheduled** | **Weight** |
+--------------------+--------------------+-------------------+------------+
| > Lab Assignments  | > Asynchronous     | > Due Mondays by  | > 30%      |
|                    |                    | > noon unless     |            |
|                    |                    | > stated          |            |
|                    |                    | > otherwise       |            |
+--------------------+--------------------+-------------------+------------+
| > Mid Term         | > Synchronous      | > 27-October-2023 | > 30%      |
|                    |                    | > (Friday)        |            |
+--------------------+--------------------+-------------------+------------+
| > Final exam       | > Synchronous      | > 19-Dec-2023     | > 40%      |
|                    |                    | > (Tuesday) @     |            |
|                    |                    | > 2:00 p.m.       |            |
+====================+====================+===================+============+

### Course Accreditation Units

The current total and individual Accreditation Unit (AU) counts for this
course are:

  -------------------------------------------------------------
  Total         Math          NS      ES         ED      CS
  ------------- ------------- ------- ---------- ------- ------
  44.1          29.4                  14.7               

  -------------------------------------------------------------

### Course Graduate Attributes

The Graduate Attributes (GAs) developed in this course are:

  ------------------------------------------------------------
  \#    Graduate Attribute                         Level (I,
                                                   D, A)
  ----- ------------------------------------------ -----------
  1     A knowledge base for engineering (KB):     I

  2     Problem analysis (PA):                     D

  3     Investigation (IN):                        

  4     Design (DE):                               

  5     Use of engineering tools (ET):             A

  6     Individual and team work (TW):             

  7     Communication skills (CS):                 

  8     Professionalism (PR):                      

  9     Impact of engineering on society and the   
        environment (IS):                          

  10    Ethics and equity (EE):                    

  11    Economics and project management (EP):     

  12    Life-long learning (LL):                   
  ------------------------------------------------------------

### Course Schedule

\-

### 

# Fall Term 7