Engineering Computational Methods
ME 318 - Unique No. 15675
Course Descriptor
Spring 2000
Time MWF 8:00-9:00
Room ETC 2.136
Instructor Dr. Suman Das
e-mail:
Permanent Office ETC 5.142 (phone: 232-5916)
Office Hours MWF 9:00-10:00
Teaching Graders and Computer Laboratory:
Assistants Yeong-Jun Choi – e-mail:
Aniket Murarka – e-mail:
Sapan Shah – e-mail:
Computer ETC 2.144 HP Lab (PC) – PRIMARY LAB (Schedule Posted on Website)
Labs ETC 3.128 Undergraduate Lab (Mac and PC)
ETC 3.130 Undergraduate Lab (Mac and PC)
Student Microcomputer Facility (SMF) at the Undergraduate Library (Mac and PC) - You may obtain an account on the SMF at the service desk by presenting your UT student ID.
Textbook Applied Numerical Analysis Using MATLABâ
Author: Laurene V. Fausett
Prentice Hall, Inc., 1999.
Supplemental MATLABâ for Engineering Applications
Author: William J. Palm III
WCB/McGraw-Hill, 1999.
Suggested S. C. Chapra and R. P. Canale, Numerical Methods for Engineers
References W. Cheney and D. Kincaid, Numerical Mathematics and Computing
F. Scheild, Numerical Analysis, Schaum's Outline Series
Software MATLABâ
Homework Typically assigned once a week and due the following week. Absolutely no late homework will be accepted.
Grades Computer & Written Assignments 35%
Exams 45% (15% each)
Final 20%
Prerequisites ME 202, ME 210, M 408C, and M 408D with a grade of at least C in each and credit or registration for M 427K. Unless you have taken M 427 (or an equivalent course) or you are currently enrolled in such a course, I strongly recommend that you drop ME 318.
Additional See Course Policy Supplement for additional rules and grading policy.
Rules
Course Common University Evaluation Form.
Evaluation
Absences Although attendance will not be taken during class, if you miss a class you are still responsible for any material covered or assignments made. No make-ups for missed exams and no late homework assignments will be accepted. Failure to attend class regularly will almost always result in a poor performance on your part.
Dropping Courses An undergraduate student may not drop a course after the fourth day except for good cause (health or serious personal problems, or a demonstrated need to work more hours).
Students With The University of Texas at Austin provides upon request appropriate academic
Disabilities adjustments for qualified students with disabilities. For more information, contact the Office of the Dean of Students at 471-6259, 471-4241 TDD or the College of Engineering Director of Students with Disabilities at 471-4382.
Scholastic Scholastic dishonesty will not be tolerated and incidents of scholastic dishonesty
Dishonesty will be reported. Scholastic dishonesty is any act designed to give an unfair academic advantage to a student, or the attempt to commit such an act.
For More Consult the Course Schedule, General Information Bulletin and the
Information Undergraduate Catalog.
Last Class Friday, May 5, 2000.
ME 318 Course Outline
1. Introduction (Chapter 1)
1.1. Course Organization
1.2. Numerical Methods in Engineering
1.3. Overview of Modern Computational Tools
MATLAB
Signing-on, Environment, Editor
2. Linear Algebra and Matrices
2.1. Introduction to Matrix Theory
2.2. Matrix Properties
2.3. Matrix Computations
MATLAB
Basic Operations, Arrays, Matrix Operations
3. Systems of Linear Equations (Chapters 2, 3)
3.1. Direct Elimination
3.2 Gaussian Elimination
3.3 Gauss-Jordan Reduction
3.4. Matrix Inverse
MATLAB
Files, Functions
4. Iterative Methods (Chapter 4)
4.1 Jacobi Method
4.2 Gauss-Seidel Method
MATLAB
Data Structures
Exam 1 (Friday, February 18)
5. Roots of Nonlinear Equations (Chapter 5)
5.1. Bisection Method
5.2. Newton's Method
5.3. Successive Substitution
MATLAB
Relational Operators, Conditional Statements, Loops
6. Curve Fitting and Polynomial Interpolation (Chapter 8)
6.1. Line Fitting and Nonlinear Fitting
6.2. Polynomial Interpolation with Power Series
6.3. Lagrange Interpolation Polynomials
6.4. Newton Interpolation Polynomials
MATLAB
Loops, Program Flow
Exam 2 (Friday, March 10)
7. Numerical Integration (Chapter 11)
7.1. Newton-Cotes Formulae
7.2 Trapezoidal Rule
7.2. Simpson's Rule
MATLAB
Plotting
8. Numerical Differentiation (Chapters 11,12)
8.1. Difference Approximations
8.2. Taylor Expansion Method
MATLAB
Numerical Integration, Numerical Differentiation
9. Initial Value Problems (Chapter 12,13)
9.1. Order Reduction
9.2. Euler Method
9.3 Runge-Kutta Methods
MATLAB
ODE Solvers, Extensions to Higher-Order Equations
Exam 3 (Friday, April 28)
10. Boundary Value Problems (Chapter 14)
10.1. Finite Difference Method
11. Review
Final Exam (Tuesday, May 16, 2-5 PM)
1