Computational Modeling of Uncertainty in Time-Domain Electromagnetics

Time-Domain Algorithms for Computational Electromagnetics

Uncertainty Quantification in Computational Electromagnetics : The stochastic approach

— Models in electromagnetism are more and more accurate. In some applications, the gap between the experience and the model comes from the deviation on input data of the model which are not perfectly known. The stochastic approach can be used to quantify the effect of these input data uncertainties on the outputs of the model. In this article, the application of such approach in computational e...

Grid Infrastructure for Domain Decomposition Methods in Computational ElectroMagnetics

The accurate and efficient solution of Maxwell’s equation is the problem addressed by the scientific discipline called Computational ElectroMagnetics (CEM). Many macroscopic phenomena in a great number of fields are governed by this set of differential equations: electronic, geophysics, medical and biomedical technologies, virtual EM prototyping, besides the traditional antenna and propagation ...

Distributed Computational Electromagnetics Systems

We describe our development of a \real world" electromagnetic application on distributed computing systems. A computational electromagnetics (CEM) simulation for radar crosssection(RCS) modeling of full scale airborne systems has been ported to three networked workstation cluster systems: an IBM RS/6000 cluster with Ethernet connection; a DEC Alpha farm connected by a FDDI-based Gigaswitch; and...

Nedelec elements for computational electromagnetics