Professor Al Ferri
Office: J. Erskine Love Jr. Manufacturing Building (MRDC-II), Rm
107
Phone: (404)-894-7403, (404)-894-8496 (FAX)
Email Address:
al.ferri@me.gatech.edu
Office
Hours: TBA
Class Time: MWF 11:05-11:55am, Instruction Center Rm 211
Textbook: Numerical Methods for Engineers, 5th Edition, S.C. Chapra and R.P. Canale, McGraw-Hill, 2006. ISBN 0-07-291873-X
Prerequisites:
CS 1371 Introduction to Computing
Math 1502 Calculus II
Math 2403 Differential Equations (co-requisite)
Course Description:
An introduction to the use of computers and MATLAB programming for the solution of mechanical engineering problems. Topics include sources of error in computing, the use of modular software design, basic numerical methods, and signal processing.
Announcements/New Items:
- Announcement 1: Along with e-mail, the announcements section of the website is the primary means by which I will disseminate information to the class.
- Announcement 2: Click on the link to get the program calc_exp.m
- Announcement 3: Homework Assignment #1 is now avaliable in the table below
- Announcement 4: Here is a link to an excellent site that explains Floating Point Numbers. This is the convention that we will be using in this class. Please note that it differs from the explanation of the text AND the convention that you will find in my old tests and exams. The website also explains how "zero" and "infinity" are handled in the IEEE standard.
- Announcement 5:
Assignments:
Over the course of the semester, there will be approximately 12 homework assignments worth 10 points each. I will drop your lowest grade. Working in groups is allowed but each student must turn in their own homework. Attempt each problem on your own first before seeking help from others. Spending quality time working homework is the best way to succeed on the tests and final exam. Each homework assignment will have a Matlab component. In your homework submission, please include: all handwritten material, all Matlab commands, scripts, programs/functions that you write, all tables or plots that you generate. Every test will have a Matlab question or two that asks you to code an algorithm, debug a script, etc.
Links to the solutions are posted in last column when they are available.
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Grading Policy:
Academic Integrity:
Academic honesty is essential to achieve high-quality education and
to maintain the value of a Georgia Tech diploma. While I encourage you to
work together and to form study groups, it is important that you take
responsibility for the content of all assignments. Cheating on tests
and final exams will not be tolerated. When uncovered, violations will be reported to
the Dean of Students immediately. A valuable resource for the Georgia Tech Student Code of
Conduct and the Academic Honor Code is:
http://www.honor.gatech.edu/honorcode/honorcode.html.
Academic honesty is essential to achieve high-quality education and to maintain the value of a Georgia Tech diploma. While I encourage you to work together and to form study groups, it is important that you take responsibility for the content of all assignments. Cheating on tests and final exams will not be tolerated. When uncovered, violations will be reported to the Dean of Students immediately. A valuable resource for the Georgia Tech Student Code of Conduct and the Academic Honor Code is: http://www.honor.gatech.edu/honorcode/honorcode.html.
Sample Tests from Previous Semesters and Quarters:
Course Schedule
Week 1
- Introduction to ME2016
- Review of Matlab environment and commands
- Text coverage: Chapter 2
Week 2
- Approximations and round-off errors
- Computer representation of integers and floating point numbers
- Matlab programs and functions
- Text coverage: Chapter 3
Week 3
- Labor Day
- Truncation errors and the Taylor series
- Finite difference approximation of derivatives
- Bisection method for root solving
- Text coverage: Chapter 4, Section 5.1-5.2
Week 4
- False-position method
- Fixed-point iteration
- Newton-Raphson method
- Secant method
- Text coverage: Chapters 5,6
Week 5
- Applications and review
- Test 1
- Matlab commands useful for matrix manipulation
- Text coverage: Chapter 7
Week 6
- Cramer's Rule
- Naive Gaussian Elimination
- Text coverage: Sections 9.1-9.2
Week 7
- Pitfalls of elimination methods, ill-conditioning
- Effect of scaling
- Partial/Full pivoting
- Gauss-Jordan elimination
- LU decomposition
- Text coverage: 9.2-9.4; 9.7; 10.1-10.1.3
Week 8
- LU-decomposition
- Crout decomposition
- Matrix inverse
- Matrix condition number
- Cholesky decomposition
- Gauss-Seidel and Jacobi iteration
- Drop Day
- Text coverage: 10.1.4-10.3; Chapter 11
Week 9
- Fall Break
- One-dimensional optimization
- Multidimensional unconstrained optimization
- Linear programming
- Text coverage: Chapters 13-15
Week 10
- Curve fitting
- Least-squares regression
- Text coverage: Chapter 17
Week 11
- Interpolation
- Test 2
- Lagrange polynomials
- Splines
- Text coverage: Chapter 18
Week 12
- Fourier Approximations
- Fourier transform, DFT, and FFT
- Text coverage: Sections 19.1-19.6; 19.8.3
Week 13
- Numerical integration
- Trapezoidal, Simpson's rules
- Text coverage: Chapters 21-22
Week 14
- Numerical differentiation
- Ordinary differential equations (ode's)
- Runge-Kutta Methods
- Thanksgiving Break
- Text coverage: Chapters 23 and 25
Week 15
- Systems of ode's
- Finite difference methods
- Boundary-Value Problems
- Text coverage:
Week 16
- Special Topics
- Text coverage: