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Scattered Data Approximation and Meshfree Galerkin Methods
Applied Math| Speaker: | N. Sukumar, University of California - Davis |
| Location: | 693 Kerr |
| Start time: | Fri, Oct 21 2005, 4:10PM |
Description
In the talk, I will present the basic principles that have
guided the development of meshfree approximation schemes.
Over the past decade, with an aim towards alleviating the
need to remesh in moving boundary and large deformation
problems, there has been significant interest
in the application of meshfree methods for the
solution of partial differential equations. Meshfree approximations
have also generated interest in the
computer graphics and geometric modeling communities
for surface parametrization and volume visualization of
large data sets. As opposed to finite elements,
in meshfree methods, the approximation is built without
the explicit connectivity information between the nodes.
I will place emphasis on moving-least squares, radial basis functions,
natural neighbor and polygonal interpolants, and maximum entropy
approximation schemes. The pros and cons of using these
approximation schemes in a Galerkin procedure for the
solution of partial differential equations will be discussed.