It is well-known that the use of numerical methods for the analysis,
simulation, and design of engineering processes and industrial
systems has been increasing at a rapid rate. Therefore, this course
is intended to better prepare future engineers and computational
scientists (as well as to assist practicing engineers and
computational scientists), in understanding the fundamentals of
numerical methods, especially their application, limitations, and
potentials. This course is designed as an introductory course in
computational techniques for solving problems from science and
engineering with emphasis on applications. The course will cover the
classical fundamental topics in numerical methods such as,
approximation, numerical integration, numerical linear algebra,
solution of nonlinear algebraic systems and solution of ordinary and
partial differential equations. The viewpoint will be modern, with
connections made between each topic and a variety of applications.
By the end of the course, the student should not only be familiar,
but more confident, in effectively using numerical tools to solve
problems in their own field of interest.
Lectures: M (4:30 pm - 7:10 pm)
Venue: Robinson Hall B208
Dr. Padmanabhan Seshaiyer
Office Hours: M W (2:00 pm - 3:30 pm) and by appointment
Sufficient recall of undergraduate linear algebra, differential equations
and computer literacy including familiarity with MATLAB.
EXPECTED LEARNING OUTCOMES
this course, the emphasis will be to apply well-know numerical
techniques to solve engineering problems and evaluate the results.
The objective will be to train students to understand why the
methods work, what type of errors to expect, and when an application
might lead to difficulties. In particular, the students will become
Understanding the theoretical and practical aspects of the use of
Implementing numerical methods for a variety of
Establishing the limitations, advantages, and disadvantages
of numerical methods
expected learning outcomes for the course will be assessed through:
Exams, homeworks, in-class activities and class discussions. Problem-based
learning will be an integral part of the course.
package MATLAB will be used for scientific computation, analysis and
presentation of data. MATLAB is an interactive programming language
for general scientific and technical computation with powerful
graphics and library functions.
MATLAB is installed in the computer labs in the Johnson Center in rooms 340, 341, and 343 and in
Innovation Hall in room 301. Check the following
website for hours of operations.
MATLAB is also installed on the Mason cluster (osf1). To use this version of MATLAB, you must
activate your account on the Mason cluster (osf1). If you haven't done this before, you must activate
your mason account.
See the web page below for instructions to activate your account and set up a
Evaluation for the course will be based on the following criteria:
There will be five homework assignments during the semester each
worth 6%. There will also be computer projects which is worth 30%. These
items should be written up and handed in on time to receive full credit as
they add towards 60 % of the total grade.
There will be one midsemester exam and one comprehensive final exam
in this course.
The Final Exam will be on Monday, May 14, 2012 from
4:30 PM - 7:15 PM and will be comprehensive.
Make-up exams may be possible only in the case of documented
Problem-based learning (both in and out of class) will be an integral part
of the course. The primary reference will be "Classical
and Modern Numerical Analysis",
by A. Ackleh, E. Allen, R. Kearfott and P. Seshaiyer. Lecture notes will
also be provided by the instructor that will be posted on the course
website on a regular basis.
All students will be expected to abide by the Honor Code: Student
members of the George Mason University
community pledge not
to cheat, plagiarize, steal, or lie in matters related to academic
Any student who, because of a disability, may require some special
arrangements in order to meet course requirements should contact the
instructor as soon as possible to make such accommodations as may be