MTH
453-
552
: NUMERICAL PDEs - Spring 2018
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Instructor:
Malgorzata Peszynska
Contact information including office hours is on
instructor's department website.
Class: MWF 10:00-10:50 STAG 161. Grader: TBA
Course content:
Numerical PDEs course is an introduction to the theory and
implementation of numerical algorithms for partial differential
equations (PDEs). We will consider first order PDEs as well as
selected second order linear PDEs such as Poisson's equation, heat
equation, and wave equation, with applications to mass and energy
transport such as advection-diffusion-reaction. Students will study
theory of numerical schemes, implement their own code in MATLAB (based
on templates provided), and experiment with some of the applications.
We will focus on finite differences, but perspectives on other methods
such as finite elements and spectral methods will be provided.
Textbook and resources:
Finite Difference Methods for Ordinary and Partial Differential Equations, Steady State and Time Dependent Problems
by Randall J. LeVeque,
SIAM, 2007 (Chapters 2,3,9-11). Paperback: ISBN 978-0-898716-29-0.
See also Exercises and m-files to accompany the book.
MATLAB will be used for implementation of algorithms. If you
need a refresher, search, e.g., for "matlab tutorial free". See also
my old worksheet lab.txt.
Prerequisites:
Students will be expected to know the material on finite difference
schemes for IVP and BVP covered
in MTH
452/552.
Exams: There will be two midterms scheduled outside class
meetings; each will count as 30% of the grade, on Friday May 4, 4:00-6:00, and Thursday May 31, 4:00-6:00.
(We meet as usual in STAG 161).
Homework will count as 40% of the grade, with the lowest score
dropped. It will be assigned weekly; see schedule and required format
at Assignments page). The HW will be
collected in class. Additional practice problems will be recommended
but not graded.
Extra credit projects will be posted
on Assignments page for those
interested in developing further skills. Up to 5% of the grade can
come from extra credit projects, and worksheets given in class.
Course Learning Outcomes:
A successful student who completed MTH 453 will be able to
- Implement and follow the analysis of basic finite difference schemes
for selected partial differential equations
- Determine stability, accuracy, and convergence of an algorithm
theoretically and experimentally
- Propose an appropriate method for a given PDE from a selected class
A successful student who completed MTH 553 will be able to
- Analyse and implement basic and intermediate finite difference schemes
for selected partial differential equations
- Determine stability, accuracy, and convergence of an algorithm
theoretically and experimentally
- Propose an appropriate method for a given PDE from a selected class
Statement Regarding Students with Disabilities:
Accommodations for students with disabilities are determined and
approved by Disability Access Services (DAS). If you, as a student,
believe you are eligible for accommodations but have not obtained
approval please contact DAS immediately at 541-737-4098 or at
http://ds.oregonstate.edu. DAS notifies students and faculty members
of approved academic accommodations and coordinates implementation
of those accommodations. While not required, students and faculty
members are encouraged to discuss details of the implementation of
individual accommodations. The DAS Statement is posted online at:
ds.oregonstate.edu/faculty-advisors (4/14/16).
Link to Statement of Expectations for Student Conduct, i.e., cheating policies
http://oregonstate.edu/studentconduct/offenses-0
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