Published: Sept. 7, 2012

A Model Reduction Algorithm for Computational Electromagnetism

Mahadevan Ganesh


Department of Applied Mathematics & Statistics, Colorado School of Mines


Date and time: 

Friday, September 7, 2012 - 3:30pm


We consider a parameterized multiple electromagnetic scattering wave propagation model in three dimensions. The parameters in the model describe the location, orientation, size, shape, and number of scattering particles as well as properties of the input source field such as the frequency, polarization, and incident direction. The need for fast and efficient (online) simulation of the interacting scattered fields under parametric variation of the multiple particle surface scattering configuration is fundamental to several applications for design, detection, or uncertainty quantification. For such dynamic parameterized multiple scattering models, the standard discretization procedures are prohibitively expensive due to the computational cost associated with solving the full model for each online parameter choice.

In this talk, we discuss an iterative offline/online reduced basis computer model reduction approach for a boundary element method to simulate a parameterized system of surface integral equations reformulation of the multiple particle wave propagation model. The approach includes (i) a greedy algorithm based computationally intensive offline procedure to create a selection of a set of a snapshot parameters and the construction of an associated reduced boundary element basis for each reference scatterer and (ii) an inexpensive online algorithm to generate the surface current and scattered field of the parameterized multiple wave propagation model for any choice of parameters within the parameter domains used in the offline procedure. Comparison of our numerical results with experimentally measured results for some benchmark configuration demonstrate the power of our method to rapidly simulate the interaction of scattered wave fields under parametric variation of the overall multiple particle configuration.