| dc.contributor |
Batten, Belinda |
|
| dc.contributor |
Higdon, Robert |
|
| dc.contributor |
Liburdy, James |
|
| dc.contributor |
Batten, Belinda |
|
| dc.date |
2007-06-20T16:22:40Z |
|
| dc.date |
2007-06-20T16:22:40Z |
|
| dc.date |
2007-05-09 |
|
| dc.date |
2007-06-20T16:22:40Z |
|
| dc.date.accessioned |
2013-10-16T07:53:06Z |
|
| dc.date.available |
2013-10-16T07:53:06Z |
|
| dc.date.issued |
2013-10-16 |
|
| dc.identifier |
http://hdl.handle.net/1957/5542 |
|
| dc.identifier.uri |
http://koha.mediu.edu.my:8181/xmlui/handle/1957/5542 |
|
| dc.description |
Graduation date: 2008 |
|
| dc.description |
Proper orthogonal decomposition (POD) in conjunction with the Galerkin
projection has been used as a model reduction technique for the tractable
real-time control of high-dimensional systems. While POD based model
reduction may improve the tractability of high-dimensional models, the
nonlinear POD based model may be impractical for control due to the cost
of computing its nonlinear terms. In this work, a new technique designed
to reduce the computational cost of nonlinear POD models is introduced.
This technique extends ideas from the group finite element method to
POD and is called the group POD method. A forced, single variable, two
dimensional Burgers’ equation is used as a model problem to assess group
POD method. Simulations of group POD models for Burgers’ equation are
shown to accurately converge to analytically known benchmark solutions.
For Burgers’ equation, a preliminary mathematical investigation shows the
group POD method may reduce the computational cost of the nonlinear
terms as compared to the standard POD method. |
|
| dc.language |
en_US |
|
| dc.subject |
Proper Orthogonal Decomposition |
|
| dc.subject |
Model Reduction |
|
| dc.subject |
Group Finite Element Method |
|
| dc.title |
Nonlinear model reduction using the group proper orthogonal decomposition method |
|
| dc.type |
Thesis |
|